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ServiceNow Acquires Parlo!

By Murali Subbarao on May 3, 2018 1:03:15 PM

 Parlo's NLU Capabilities Coming to the Now Platform


Dear Parlo Family,

We are excited to announce that Parlo is joining forces with ServiceNow!

ServiceNow (NYSE: NOW) is driven by the idea that getting things done at work should be easier. Its Platform and products are used by thousands of organizations around the world, including over 40% of the Global 2000 to simplify workflows across IT, customer service, security operations and HR service delivery. 

Parlo’s advanced AI capabilities will permeate all aspects of ServiceNow’s Now Platform. Therefore, the decision to join ServiceNow was an obvious and important one - it allows Parlo to truly deliver on its mission of democratizing intelligent automation at scale. Our automation technology can scale much faster and farther as a part of ServiceNow. This is indeed exciting. Together the two companies will be focused on leveraging Broca, Parlo’s most advanced NLU, and AI-powered virtual agents to create better experiences for enterprise employees and customers. 

Too many enterprises are still stuck in the past, using hundreds of legacy apps and routine business processes to engage their workforce. However, as employees continue to get more mobile, enterprises must embrace intelligent automation to both enhance the employee experience and improve workplace productivity.

I firmly believe that AI-powered virtual agents will become the front-line of simpler, faster communication between employees and enterprises. This is the exciting future Parlo and ServiceNow will build together.

 CEO Blogpost Picture 2

I want to thank Parlo’s employees and their families, investors, and well-wishers for their support and encouragement over the years. We couldn’t have done it without you! In particular, I’m thankful to have had Edwin and Srini as friends and partners in Parlo’s sometimes winding journey: your creativity, hard work, and bonhomie have been instrumental in getting us to this point.

And a deep “thank you” goes out to you -- our customers and partners. With ServiceNow, we look forward to helping you and your organizations make work simpler, easier, and more enjoyable for all!



Murali Subbarao
Founder & CEO
Parlo, Inc.

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The 3 Evolutions of Bots for IT Service Desk

By Adi Subbarao on Mar 30, 2018 1:06:51 PM


The Modern Era of Intelligent Enterprise Automation

With the rise of chatbots and AI, enterprise tasks and processes which were previously difficult to automate are now experiencing rapid cost and labor efficiencies.

This is largely due to the latest wave of automation taking place within Human Resources (HR), Customer Support, and IT Service Management (ITSM).

In this article, we will discuss the three evolutions of bots for IT Service Desk automation in order of capability from basic to most advanced.

The Automation Spectrum for
IT Service Desk Bots

Timeline@2x-100 - edited

Evolution One - Robotic Process Automation (RPA)



The first evolution of IT Service Desk automation came in the form of robotic process automation (RPA). RPA helped enterprises transition from providing labor services to software-as-a-service.

Repetitive tasks that used to take employees significant time to complete, could now be automated using RPA bots which would mimic a series of human clicks/interactions and put repetitive tasks on cruise control.

IT Process Automation (ITPA) is a form of RPA which is focused specifically on the needs and pain points of an enterprise’s IT infrastructure. Since IT departments rely on multiple IT systems, processes, and workflows, ITPA requires a more intricate level of programming in order to handle more complex tasks (i.e. multi-factor authorization and password resets, virtual server provisioning and configuration, cyber security incidents,  etc).

For Example:
In the case of a password reset, IT service agents would no longer need to login to an application and manually request a password reset. Instead, the agent could utilize ITPA to fully automate the login and password reset process on the backend.

As a result, ITPA gave rise to a virtual workforce which helped enterprises reduce unnecessary human effort and dramatically improve operational efficiency.

Challenges with RPA/ITPA

The biggest drawback with RPA/ITPA is that individual task automation has lower value and a narrow scope whereas automating an entire IT process has higher value and broader scope. This leads us to our first big question:


How do enterprises apply the automation capabilities of RPA/ITPA towards entire IT processes, rather than simple tasks?


This brings us to our second evolution of IT Service Desk automation.


Evolution Two - Intelligent Automation


The second evolution of IT Service Desk automation is bots powered by natural language understanding (NLU).

While ITPA bots can handle repetitive IT tasks with ease, they often stumble and ultimately fail when encountering more complex requests in unstructured formats.

NLU-powered bots maintain all the benefits of RPA/ITPA but are able to understand complex user requests and intelligently automate processes based on the understanding of those requests.



Due to major advances in NLU capabilities over the past decade, enterprises have embraced intelligent automation and have started deploying chatbots which understand human input and connect with ITPA bots to execute tasks.

This results in IT Service Desk bots that can automate the end-to-end interactions between employees/customers and the enterprise.

Challenges with Intelligent Automation

The challenges with intelligent automation revolve around the scalability and consistent accuracy of the IT Service Desk bots over time. Creating, training, and maintaining a bot’s skills is currently a very manual process that does not scale at volume.


Creating and Maintaining an IT Service Desk Bot (Manually)


Here is the 4-step process of creating and maintaining a bot:

  1. Manually identify the service requests that need to be automated
  2. Manually train an NLU model to enable the chatbot’s understanding of each request
  3. Manually build a bot and test it for consistent accuracy and performance
  4. Once in production, repeat steps 1-3 using chat logs to add new skills to the chatbot

Many enterprises have piloted chatbots in narrow areas and are seeing great success, but the number one question they have is - how does this scale?

This leads us to our next big question:


Once you build, train, and deploy an IT Service Desk bot, how do you sustainably scale its capabilities as your enterprise evolves?


This brings us to our final evolution of IT Service Desk automation.


Evolution Three - Intelligent Automation at Scale

The third and most advanced evolution of IT Service Desk automation involves bots that use NLU and can leverage existing enterprise data to automatically maintain and improve their capabilities.

Large enterprises have thousands of recorded employee and customer interactions that are archived in their CRM, Service Desk, or Customer Support systems.

What if you could harness this data to create an out-of-the-box AI-based chatbot customized to your enterprise?

Now that would be super cool! Wouldn’t it?



Well, we have fantastic news. Using existing IT service tickets, enterprises can now use unsupervised learning to automatically extract intents and entities from their tickets, surface the most frequent intents and entities using clustering techniques, and fully automate them.


Creating and Maintaining a Service Desk Bot (Automatically)



Challenges with Intelligent Automation at Scale

Unfortunately, if you want to build these robust and scalable IT Service Desk chatbots in-house, you will need to spend significant engineering resources, utilize immense computing power, and tweak core NLU algorithms on an ongoing basis.

As we discussed in our previous blog post, “The 3 Essentials of Building AI Bots for Enterprise IT Help Desk”, it is critical for enterprises to quickly embrace AI-powered IT Service Desk bots and intelligent cognitive automation. However, the implementation must be done correctly in order to see a quicker resolution of IT service requests and significantly reduced operational costs.This is where Parlo can help.


Introducing Parlo IT Service Desk Bots


At Parlo we believe in democratizing the process of creating intelligent automation at scale by automatically detecting intents from your tickets as a service.

Over the past 2 months, we ran a closed beta with a few customers and the results have been promising. Our beta customers have been able to streamline the process of creating, training, and maintaining a bot for IT service Desk requests. 


Right now we are offering a limited number of enterprises to create, train, and maintain IT Service Desk bots out-of-the-box. If you are interested in this solution for your enterprise, please submit a request to our team.



We’ve come a long way from the days of using human agents to handle routine IT service requests within an enterprise. Here are the three evolutions of IT Service Desk bots being used within enterprises today:

  1. Evolution One - Robotic Process Automation (RPA)

    • RPA bots help enterprises automate routine tasks in order to reduce unnecessary human intervention and improve operational efficiency.
  2. Evolution Two - Intelligent Automation

    • Intelligent automation involves NLU-powered bots that can understand complex user requests and intelligently automate processes based on the understanding of those requests.
  3. Evolution Three - Intelligent Automation at Scale

    • Instead of requiring manual training and maintenance, these NLU-powered bots can leverage existing enterprise data to automatically maintain and improve its capabilities.

The future evolutions of IT Service Desk automation will involve end-to-end deep learning. However, given our current state of AI technology, we are at least 2-3 years from this becoming a reality. Until then, Intelligent Automation at Scale is the most pragmatic approach to achieving IT Service Desk automation.

We are proud to announce that Parlo’s latest IT Service Desk cloud offering is available for customers to use in open beta now! So long as you have CRM or Service Desk data, you should be able to create a sophisticated chatbot in 60 days or less.

So why wait? Check out Parlo’s Open Beta program to learn more.

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If you found this article useful, please let us know your thoughts below. We regularly publish content like this on our blog in our mission to bring smarter AI to smarter enterprises.

Parlo builds smarter bots for smarter enterprises. We build AI chatbots that employ cutting-edge machine learning to seamlessly integrate with your business. They’ll support your human workforce, delight your customers, and save you time and money.

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How to Build a Superhuman HR Team Using AI Chatbots (Part 2)

By Adi Subbarao on Mar 15, 2018 4:00:52 PM


AI Chatbots Are Redefining the Roles Within Human Resources

In Part 1 we addressed why HR teams must embrace AI chatbots in order to be part of strategic business transformation and shape the HR of the Future.

Now let’s take a deeper dive into how HR teams should adapt their key roles, processes, and strategies when introducing AI chatbots as part of the enterprise.

HR Team Today




Today, HR Managers communicate directly with HR specialists and service centers to deliver shared services (employee information, transactions, case/project management, compliance, governance, HR systems, etc) across regional service areas.

If an enterprise does not use a service center, many of their HR specialists must handle routine and low-value Level 1 HR requests.

In other words, these specialists are currently the 1st line of interaction between employees and HR services.

A better approach would be to allow HR specialists to truly specialize by positioning themselves as the 2nd or 3rd line of interaction within the HR process and focusing on complex high-value HR requests.

However, with over 70% of HR time being spent today on administrative and transactional tasks, HR teams must embrace AI chatbots and other innovative technologies to create operational efficiency and excellence.

With the help of AI chatbots, we envision HR teams would become more collaborative and specialized. As a result, enterprises can deliver a highly personalized and flexible HR support experience. We’ve gone ahead and illustrated how AI chatbots can support HR teams in this way:

Build and Train Your AI Workforce

In our previous blog post, we discussed the 7 Ways Chatbots and AI are Disrupting HR. Now imagine introducing AI chatbots for specific HR tasks within your enterprise workforce!

These AI chatbots can be trained to handle multiple skills to elevate internal employee and managerial experiences:

Parlo AI Chatbots for HR Shared Services.jpg

Enterprises can begin building their AI workforce by deploying AI chatbots to automatically fulfill specific Level 1 HR tasks.

Introducing Your HR Chatbot Team!

Once you have selected the specific HR skills and experiences you want to create, AI chatbots can be trained and deployed accordingly as integral members of your HR team:


This HR chatbot team would be robust and scalable since it is continuously learning based on each chatbot interaction. As a result, your existing HR team can confidently shift time away from administrative and transactional HR tasks towards more strategic and transformational HR tasks.

Armed with a fully-trained and integrated HR chatbot team, your enterprise can embrace the HR Team of the Future:

HR Team of the Future


The HR Team of the Future will involve HR Managers working alongside your HR chatbot team to complete managerial tasks (HR system access permissions, employee assignments, worker compensation, performance reviews, etc).

In addition, the HR Team of the Future will consist of HR experts overseeing your HR chatbot team which is already trained to handle specific Level 1 HR shared service requests and actions.

By treating your HR chatbot team as members of your overall HR hierarchy, enterprises would be able to drive efficiency throughout their HR Shared Services and focus more time on improving their centers of operational excellence (CoEs) responsible for handling more complex and high-value HR tasks.

Wrapping Up

It is clear that AI chatbots are redefining traditional roles within Human Resources (HR).

The HR Team of the Future will use AI chatbots as the 1st line of interaction between employees and HR services, allowing existing HR teams to become specialists and focus more time on complex high-value HR requests.  

Enterprises will be able to train AI chatbots to handle multiple skills to elevate internal employee and managerial experiences. As result, these AI chatbots would work together as part of an HR chatbot team responsible for handling Level 1 HR tasks.

Furthermore, HR teams can rely on HR chatbots in order to focus less time on administrative and transactional HR tasks and more strategic and transformational HR tasks. The HR Team of the Future would see HR Managers working alongside HR chatbots and HR experts overseeing HR chatbots in order to dive more operational efficiency and excellence.

All in all, as enterprises continue to build and expand their AI workforce, humans and AI chatbots will collaborate to deliver more personalized and flexible employee HR experiences while creating the superhuman HR Team of the Future.

If you are ready to embrace the HR of the Future using AI chatbots, check out Parlo HR Bots to learn more. We would love to show you a demo of an HR chatbot team in action.

In case you missed it, check out Part 1 of our HR Transformation series.

Request an HR Chatbot


If you found this article useful, please let us know your thoughts below. We regularly publish content like this on our blog in our mission to bring smarter AI to smarter enterprises.

Parlo builds smarter bots for smarter enterprises. We build AI chatbots that employ cutting-edge machine learning to seamlessly integrate with your business. They’ll support your human workforce, delight your customers, and save you time and money.

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How to Build a Superhuman HR Team Using AI Chatbots (Part 1)

By Adi Subbarao on Mar 13, 2018 2:27:00 PM


Moving from Transactional to Transformational HR

Human Resources (HR). We all need it, yet for whatever reason, over the past decade, very little about how we do HR has changed.

While many areas of an enterprise have embraced digital transformation to create better employee experiences, HR remains in the Dark Ages following strict processes and company policies to deliver standardized results. In fact, over 70% of HR time is spent on transactional and administrative requests, leaving very little time for strategy and talent management. This leads us to our big question:


With so much diversion of its time can an HR team really be a part of strategic business transformation?


This is the problem we see today. HR of Today is stuck getting routine tasks completed. To shape the HR of the Future enterprises must embrace new AI technologies to automate routine tasks and free human capital to address the non-routine and high-value HR demands of an enterprise.

The Ulrich Model of HR Delivery

According to David Ulrich, also known as ‘The Father of Modern HR’, there is a New Mandate for HR wherein “CEOs and the upper management team must become HR champions themselves. They must acknowledge that competitive success is a function of organizational excellence. More important, they must hold HR accountable for delivering it.”

Ulrich describes four key roles in which HR can help deliver organizational excellence:

HR Chatbots Strategy Execution.png

Strategy Execution

HR should work in collaboration with senior and line managers in strategy execution, helping to move planning from the conference room to the marketplace. 

HR Experts.png

HR Experts

HR should become experts in the way work is organized and executed, delivering administrative efficiency to ensure that costs are reduced while quality is maintained.

Employee First Mentality.png
Employee First Mentality

HR should become a champion for employees, vigorously representing their concerns to senior management and at the same time working to increase employee contribution; that is, employees’ commitment to the organization and their ability to deliver results.

Continuous Transformation.png

Continuous Transformation

HR should become an agent of continuous transformation, shaping processes and a culture that together improve an organization’s capacity for change

In addition to these roles, as organizations mature, enterprises must demand HR to be a strategic partner that closely monitors the pulse of the company - its employee workforce.

Forward thinking executives and HR leaders must recognize the different demands of a future workforce and workplace, and acknowledge that technology, applied in the right way, is empowering employees and workplaces to be super-agile, and achieve significantly more.”

This leadership will ultimately drive HR transformation and finally turn the Ulrich model into a digital delivery model - a model that pushes HR to the next frontier using people analytics and conversational AI.

AI chatbots are the next generation of strategic HR partners

As the world begins to embrace the benefits of AI and intelligent enterprise automation, chatbots are emerging as an agile solution for elevating employee experiences and optimizing transactional activities within HR.

In our previous blog, we discussed the “7 Ways Chatbots and AI are Disrupting HR”. We also detailed how AI chatbots can be built and extended to complete specific transactional HR inquiries and deliver better employee and managerial experiences.

According to a recent survey of 350 HR leaders, “92% of HR leaders agree that the future of providing an enhanced level of employee service will include chatbots and that over two thirds of HR leaders believe employees are comfortable accessing chatbots to get the information they need.”

ServiceNow Chatbot Survey.jpg

Deepak Bharadwaj, General Manager of HR Product Line at ServiceNow predicts "By 2020, based on the chatbots in our personal lives...penetration in the workplace could reach adoption rates of as high as 75% with employees accessing a chatbot to resolve frequently asked HR questions and access HR solutions anywhere and anytime."

With help from AI chatbots, HR teams will finally be able to move from an operational to a strategic focus and impact organizations on a higher level. Let us illustrate how the HR of Today would compare with the HR of the Future using AI chatbots.

HR Today - current model without AI chatbots

01_HR Today.pngToday, digital HR transformation has revolved around introducing new cloud-based HCM solutions. However, according to Kevin Kramer  - Director of Human Capital at Accenture, HR teams are still focusing 70% of their time on administrative and transactional HR activities - low-value human capital wok. This leaves only 30% of time and focus spent on high-value human capital work such as HR strategy and talent and performance enhancement.

HR Future - new model using AI chatbots

02_HR Future.png

With the introduction of AI chatbots as a part of your team, the paradigm shifts completely towards high-value human capital work, which would make up 70% of your future HR team’s focus.

This doesn’t mean that HR teams can neglect the administrative and transactional activities of their roles. However, HR teams can rely upon AI chatbots to help with a majority of those issues, freeing up time to focus on more strategic value creation.

As a result, the HR of the Future would benefit from becoming more data driven, more focused on employee experiences, and more optimized for scale:


Data Driven HR.png

Data Driven HR -

Using AI chatbots, HR teams will gain visibility into enterprise-wide conversations and become more data driven when improving employee experiences. With this data driven approach, we will see HR managers managing AI chatbots in order to change any complex or confusing company HR policies. 

Employee Experiences.png

Employee Experiences -

Employees can now get answers to their HR questions on-demand using an AI chatbot instead of having to pick up a phone or send an email. They can talk to a chatbot that remembers them and instantly helps them in their preferred mode of communication (mobile, web, voice etc.).

Optimizing Costs & Savings.pngOptimizing Costs -

AI chatbots can be deployed at a fraction of the cost and are available 24/7/365. Any money saved from implementing these chatbots can be reallocated across other HR initiatives which support the enterprise’s strategic goals and deliver an improved employee experience.


In Summary

CEOs and other executives must be forward thinking in their views of HR. They must acknowledge that competitive success is a function of organizational excellence, which is driven by people - an enterprise's greatest asset.

“The Ulrich model of HR delivery has been the cornerstone framework of HR for the past 20 years, but in light of the newly emerging digital world, modern HR must adapt to become agile and remain effective”. Therefore, the transition from transactional to transformational HR requires enterprise leaders to embrace new technologies in order to make business decisions with more high-value strategic impact.

AI chatbots offer a path forward to shape the HR of the Future that is more data driven, more focused on employee experiences, and more optimized for scale.

With help from AI chatbots, HR Managers will be able to reallocate 70% of their time normally spent on administrative and transactional activities, to focus on more strategic value creation in the form of talent management and performance enhancement. For starters, we recommend introducing AI chatbots within HR Shared Services which often involve routine administrative and transactional tasks

If you are ready to build a superhuman HR team using AI chatbots, feel free to contact us or check out Parlo HR Bots to learn more. We are happy to show you a demo of HR chatbots in action

In Part 2 of our HR Transformation series we illustrate and discuss where the role of AI chatbots fit into your existing HR team to answer administrative and transactional HR requests.

Request an HR Chatbot


If you found this article useful, please let us know your thoughts below. We regularly publish content like this on our blog in our mission to bring smarter AI to smarter enterprises.

Parlo builds smarter bots for smarter enterprises. We build AI chatbots that employ cutting-edge machine learning to seamlessly integrate with your business. They’ll support your human workforce, delight your customers, and save you time and money.

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The Future of AI Chatbots and the Millennial Workforce

By Adi Subbarao on Feb 8, 2018 12:46:52 PM


Labor efficiency, cost-savings, and enterprise automation! These are the benefits of enterprise AI chatbots that executives are discussing in boardrooms across the world.

But what if we told you that the real upside to implementing AI chatbots is not in the savings, but rather in the ability to elevate employee experiences (EX) within an enterprise?

While automated AI chatbot solutions do deliver an immediate ROI in the form of cost-savings and labor efficiencies, the number one reason enterprises should adopt chatbots and conversational AI is to create delightful experiences.

We’re talking about conversational experiences that make employees feel as great communicating within an enterprise as they do when texting their closest friends.

According to the Dell Future Workforce Study, ”the future workforce will be more mobile and supported by an array of digital technologies…with Millennials taking the global reins on the introduction and adoption of new technology.” In fact, according to a Brookings Report, Millennials will comprise more than one of three adult Americans by 2020 and 75 percent of the workforce by 2025.

However, despite these shifts in workplace attitudes and trends, the typical enterprise is still not embracing the needs and desires of digital-savvy workers of the future.

Not convinced? Well let’s take a look:

Workplace of Today (Different Apps for Different Tasks)


Today’s workplace is still old-school. In fact, the average enterprise has nearly 700 apps and legacy software systems that are used for employee communication and collaboration with very few, if any, self-service options.

Therefore, navigating an enterprise in search of information has become a maze filled with time-consuming and administrative hurdles.

Employees are forced to follow strict workflows which are tedious, time-consuming, and highly inefficient in order to gather the right information from the right person for the job at hand.

According to a McKinsey report, “employees spend 1.8 hours every day—9.3 hours per week, on average—searching and gathering information. Put another way, businesses hire 5 employees but only 4 show up to work; the fifth is off searching for answers, but not contributing any value.”

Now imagine the enterprise workplace in 2025 when digital-savvy millennials comprise 75% of the workforce. Would you expect employee productivity to be driven by today’s strict and static workflows, or would you opt for an alternative solution where employees can access the information they need in a more nimble, evolving, and intelligent fashion?

As the Future Workforce Study* describes, in order for enterprises to stay competitive they must invest in smarter workplace technologies supporting a future workforce that is:

  1. More Mobile
    • Employees’ in-person interactions will decrease yet collaboration will increase
  2. More Productive
    • Better, faster technology, combined with more digitally-connected employees, will encourage increased productivity
  3. More Capable
    • Employees will understand how to use technology, such as artificial intelligence, to better accomplish workplace goals

Chatbots and conversational AI offer the unique opportunity for enterprises to drive digital transformation across all areas of the workplace (customer support, sales, marketing, human resources, IT help desk, supply chain, payroll, etc). If done properly, enterprises can create a more unified and flexible workplace in the future:

Workplace of the Future (AI Chatbot Trained for Different Tasks)


At Parlo we envision a workplace which relies less on the UI-based legacy apps of the past and more on AI chatbots powered by voice and text. This shift towards conversational AI will provide a unified enterprise view that offers more mobility for employees to communicate and access information across enterprise applications and business processes.

Say goodbye to the days when over 700 different workplace apps were required to accomplish 700 different tasks. The workforce of the future will allow employees to streamline communication across each area of the enterprise to complete daily tasks.

Gone will be the days of exchanging emails about HR related questions (benefits enrollment, PTO requests, vacation policies, etc). There’s an HR bot for that!

Good riddance to spending hours opening cases for daily IT needs (password resets, printer issues, technical support, etc). There’s an IT Help Desk bot for that!

According to the Future Workforce Study, “Employees have seen first-hand the ways new technologies can help them do their jobs better, and are hungry to use the latest advancements to be more productive. While this may seem daunting, it’s a business-critical opportunity for companies to be at the forefront of the future workplace and enable the future workforce.”


Enterprises have a critical choice to make. They can continue building countless mobile apps to support the workplace of today, or they can embrace digital transformation in the form of AI chatbots to elevate employee experiences in the workplace of the future.Workplace-of-today-vs-workplace-of-the-future.png

By embracing conversational AI and a digital-savvy millennial workforce, enterprises will benefit from a workplace that empowers more mobile, more productive, and more capable employees.

With the rise of text and voice-based messaging, employees are now accustomed to using digital applications on-the-go for internal team communication throughout the enterprise. Whether it be customer relationship management, internal sales, order management, accounting, customer support, human resources, or IT, there’s a bot for that!

If you are ready to embrace AI chatbots, elevate employee experiences enterprise-wide, and build the workplace of the future, take our hand. We’ll show you how to quickly get started.

We believe that Human Resources and IT Help Desk are the best places to begin without replacing existing legacy apps and business processes.


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*The Dell Future Workforce Study included a poll of 4,000 full-time employees in small, medium and large businesses, in 10 countries. It says that the way we communicate will be the next thing to change, and AI should reach us ‘sooner than we think’.


If you found this article useful, please let us know your thoughts below. We regularly publish content like this on our blog in our mission to bring smarter AI to smarter enterprises.

Parlo builds smarter bots for smarter enterprises. We build AI chatbots that employ cutting-edge machine learning to seamlessly integrate with your business. They’ll support your human workforce, delight your customers, and save you time and money.

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7 Ways Chatbots and AI are Disrupting HR

By Adi Subbarao on Jan 18, 2018 2:31:01 PM

Chatbots for HR - Blogpost Banner

Enterprises are Embracing AI for Automating Human Resources

Chatbots and AI have become household names and enterprises are taking notice. According to a recent Forrester survey, roughly “85% of customer interactions within an enterprise will be with software robots in five years’ time” and “87% of CEOs are looking to expand their AI workforce” using AI bots.

In an effort to drive increased labor efficiencies, reduce costs, and deliver better customer/employee experiences enterprises are quickly introducing AI, machine learning, and natural language understanding as core elements of their digital transformation strategy in 2018.

Human resources (HR) is one area ripe for intelligent automation within an enterprise. AI-powered bots for HR are able to streamline and personalize the HR process across seasonal, temporary, part-time, and full-time employees.

HR bots are redefining the enterprise employee experience

According to George Elfond, CEO at Rallyware, "due to an increasingly distributed workforce, widespread adoption of mobile technologies and a changing employee demographic, which includes millennial workers, corporate training is getting reshaped and is becoming more data and artificial intelligence driven.”

This same phenomenon is taking place across each area of HR. Whether it’s enrolling in benefits, discussing vacation policies, or completing training, HR bots can assist employees every step of the way, on-demand. We’ve put together the following list of 7 ways in which chatbots and AI are disrupting HR:

HR Bots for Seasonal and Temp Employees

Seasonal and temporary/contract employees typically work 120 days a year or less for the employer.

For example, retailers hire extra workers for the holiday season, tax preparation firms hire employees for tax season, ski resorts hire workers during winter ski season, and amusement parks hire summer seasonal workers.

Usually seasonal employees are hired in volume due to seasonal customer demand spikes which causes a HR scale issue. HR bots can resolve this issue in the following ways:

HR Bot for Recruitment

 1. Recruitment

Hiring in thousands brings scale issues for HR. A chatbot can help in the screening process by not only getting prospective employees information but also performing quick background checks.

HR Bot for On-Boarding


Chatbots make on-boarding truly a self serve process as they have the ability to talk to employees onsite and interact with workforce management softwares like Peoplesoft, Kronos, and Workday.

HR Bot for Company FAQs

 3. FAQs on Company Policies

Having dedicated HR support centers to help seasonal employees access relevant HR information should be a thing of past. Chatbots can serve as a mobile HR assistant that helps employees get answers to FAQs.

HR Bots for Full and Part-Time Employees
For these employees, a breadth of HR functions can be automated using HR bots:

HR Bot for Employee Training

 4. Employee Training

HR training using chatbots is very effective since it involves more interactive participation by employees rather than sitting through a standard training video or watching a powerpoint presentation.


HR Bot for Common Questions

 5. Common Questions

Employees spend many hours each month searching for basic company-related information. HR bots would quickly get employees the answers they are looking for, making them more productive and ultimately more satisfied.

HR Bot for Benefits Enrollment

 6. Benefits Enrollment

Benefits enrollment is one of the most confusing and frustrating pieces of the enterprise HR process. Employees spend a vast amount of time just trying to understand the process, let alone completing the required information.

HR Bot for Employee Reviews

 7. Annual Self Assessment/Reviews

More than 58% of HR leaders say that the traditional review process is outdated and ineffective. Chatbots allow for the instant exchange of feedback and performance insights that allow employees to constantly be the best at what they do.

With so many uses cases and benefits why aren’t HR bots more ubiquitous within the enterprise? Well, in addition to these benefits there are 4 big challenges enterprises must face when developing and implementing a bot for HR.

Challenges of Using Chatbots for HR

Unlike with customer support or IT helpdesk, HR handles personal identification information (PII)/sensitive personal information(SPI) of an employee. Therefore, the following areas should be well-thought-out before fully embracing bots for HR:

HR Bot Challenge - Information Security

Challenge #1: Information Security

Many enterprises using traditional on-premise HR management systems (i.e. Peoplesoft, Workday, SuccessFactors) must ensure their information does not to leave their corporate firewall. All HR data in flight and data at rest should be encrypted and fully secure. Depending on an enterprise's security requirements, HR professionals should look into an on-premise, hybrid, or cloud deployment models for HR chatbots.

HR Bot Challenge - Legal Boundaries

Challenge #2: Legal Boundaries

HR chatbots should strictly operate within its permissible swim lanes.
Let's take an example of an employee question:

"What is the best health plan for my family?
My kid has a health condition."

A chatbot should not provide a specific answer to the above question. Rather, it should defer the employee to a generic link on how to choose plans. HR managers would lose sleep if the bot started recommending health plans on a case-by-case basis. There are various legal and ethical consequences that exist when relying on AI to fully automate such requests.

For this reason, it is imperative that HR bots are built with very strong enterprise NLU capabilities to deal with more complex employee requests.

HR Bot Challenge - Bot Extensibility

Challenge #3: Bot Extensibility

As an enterprise evolves, the skills of HR bots must evolve with it. For this reason, it is important for HR departments to be able to easily extend the bot with more skills and capabilities.

This is only possible if the chatbot platform you select has visual tools to add new skills to a bot without any coding.

HR Bot Challenge - Audit Logging

Challenge #4: Audit Logging

Every interaction a chatbot has with an employee should be vaulted by the bot for any future data-retrieval purposes. This way if an auditor ever comes knocking, the HR bot will be fully prepared with all the HR data you require.

 In Conclusion

As workforce demographics continue to get more distributed and accustomed to mobile communication, enterprises must embrace AI chatbots to streamline their HR processes.

There are 7 ways in which enterprises can use HR bots to drive increased labors efficiencies, reduced costs, and better employee experiences:

  1. Recruitment
  2. Onboarding
  3. Company Policy FAQs
  4. Employee Training
  5. Common Questions
  6. Benefits Enrollment
  7. Annual Self-Assessment/Reviews

AI-driven automation in each of these areas can streamline how enterprises train, manage, and work with seasonal, temporary, part-time, and full-time employees. However, it is important to consider the challenges surrounding information security, legal boundaries, extensibility, and audit logging when making the decision to get started using bots for HR.

It is clear that chatbots and AI will become an integral part of any enterprise digital transformation strategy. Let 2018 be the year when you use HR bots to revolutionize your enterprise HR experience.


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If you found this article useful, please let us know your thoughts below. We regularly publish content like this on our blog in our mission to bring smarter AI to smarter enterprises.

Parlo builds smarter bots for smarter enterprises. We build AI chatbots that employ cutting-edge machine learning to seamlessly integrate with your business. They’ll support your human workforce, delight your customers, and save you time and money.

Topics: AI Enterprise HR
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The 3 Essentials of AI Bots for IT Help Desk

By Adi Subbarao on Dec 14, 2017 1:04:47 PM


IT Help Desk meets Artificial Intelligence

One of the areas within an enterprise ripe for disruption is the traditional IT Help Desk. Over the past decade, enterprises have become more cost-efficient through the outsourcing of Help Desk operations. However, in order to continue driving efficiencies across the enterprise, internal workforce productivity must also rise. This is where Artificial Intelligence (AI) enters the picture.

With recent advancements in infinite computing, natural language understanding (NLU), and deep learning, the application of enterprise AI solutions is more practical than ever before. In fact, with roughly 30-50% of Level 1 Help Desk support cases being repetitive, you can leverage the power of NLU and cognitive automation in the form of AI bots.

AI bots are self-learning software systems that understand the human language without requiring human assistance. They can supercharge your enterprise IT Help Desk causing your team’s productivity to skyrocket, and ultimately drive increased enterprise efficiency.

For starters, we’ve laid out the three essentials of an AI bot for your enterprise IT Help Desk needs:

1. Enterprise Language Understanding

Similar to how IT Help Desk professionals are trained to provide consistent and relevant support handling service requests, AI bots must be trained to understand language specific to your enterprise. AI bots must utilize an Enterprise Language Model (ELM) which resembles an IT service handbook or knowledge base specific to your enterprise.

An ELM represents the language (colloquialism, acronyms, cryptic notations, jargon, company terms, and domain-specific vocabulary) and intentions (or intents for short) which are expressed all the time in IT Help Desk requests. Therefore, having an ELM to understand conversations is the first step to any enterprise application of AI.

Sparse Data vs Dense Data

Sparse data refers to a low volume of data usually in the thousands that can be analyzed by simply using a spreadsheet. If you have sparse data, you should identify high volume issues and create and train intents manually. Any enterprise jargon or internal documents should also be used to quickly build your ELM.

Dense data refers to a large volume of data usually going to hundreds of thousands and even millions of records.  If you have dense data, an AI bot should identify high volume issues and surface intents automatically from your data sets to build your ELM.



The Parlo Broca NLU service is built for enterprises with both sparse and dense data collected from chat logs, CRM, documents, emails, and knowledge bases. Using a combination of machine learning and linguistic engineering, Parlo builds an ELM which accurately detects and classifies IT Help Desk intents of high volume.

With minimal training involved, Parlo can build your ELM and get your Help Desk bot up and running in less than 4 weeks.




 2. Interactions with Users

Once you’ve built a robust ELM, you must decide how your AI bot should interact within your enterprise IT Help Desk environment. AI bots can operate as an AI worker or an AI assistant.

AI Worker vs AI Assistant

An AI Worker does not involve turn-by-turn conversations with users. In fact, it is invisible to the users as the bot is deployed directly on the IT Help Desk software (ServiceNow, Ivanti, Remedy, or even an email server) which is used to capture incidents. AI Workers can be trained to completely resolve an incident/service request, or simply do some pre-processing to help a human agent resolve the ticket.  If the AI Worker is trained to resolve an incident it will act on it. Otherwise, it puts the ticket back in the queue for a human agent to take action.

For example, if a service agent requests IT Help Desk bot to “Increase disk space”, “Unlock my account”, or “Reset password” for a user, the AI Worker will automatically execute those commands on the back-end and update the ticket for the end customer (as shown below).


The advantages of this model are the following:

  • There is no disruption in user behavior, and
  • Works very well with the outsourcing models an enterprise might have as it just involves adding an AI Worker to the workforce.

An AI Assistant indulges in turn-by-turn conversation with users. Think of it functioning as a Level 1 support assistant that interacts with users and solves trained issues right away. If it is not trained for a particular service request, it logs a ticket and assigns it to a human support assistant for follow up (as shown below).



The advantages of this model are the following:

  • Simple issues are immediately resolved directly within the conversation channel (website, mobile app, Slack, Skype, etc), and
  • It helps in reducing MTTR by gathering mandatory information normally done by a human worker

3. Ability to Fulfill Service Requests

Underneath the covers of an AI bot, workflows must be in place to execute relevant tasks and business processes. There are two ways to create these workflows for AI Workers to fulfill back-office requests:

  1. Use an FAQ Knowledge Base
  2. Use Robotic Process Automation(RPA) and APIs

FAQ Knowledge Base vs RPA/API

In order for an AI Bot to truly understand a service request, the ELM alone will not suffice. Many IT Help Desk tickets involve extracting multiple complex entities (parameters associated with the request) from the ticket and calling RPA/APIs to do a backend function.

Here is a service request involving an FAQ knowledge base:
“I need to exchange my phone”

An AI Bot would extract the intent “exchange phone” and provide the relevant support link from the enterprise's knowledge base. The AI Bot can go one step further by extracting phone entities (iPhone, Galaxy S6, Pixel 2, etc) in order to guide the user to more specific support articles or higher level support engineers.

Here is a service request involving RPA:
Please give me access to the channel scrum in slack”

This involves extracting entities "scrum" and "slack" from the request, the username from the ticket, and then calling an RPA to fulfill the request.

Parlo can seamlessly connect with enterprise knowledge bases, RPAs, and APIs to fulfill routine IT Help Desk requests and create the appropriate workflows within our chatbot platform.


AI-powered bots and cognitive automation are quickly becoming the driving force for digital transformation across all enterprises. Now is the time to embrace this technology and use AI bots for IT Help Desk automation.

Getting started is always a challenge, so be sure your AI bot solution covers the three essentials:

  1. Enterprise language understanding using both sparse and dense data
  2. Interactions with users through an independent AI Worker or dialogue with an AI assistant
  3. Ability to fulfill back-office requests using FAQ knowledge bases, RPAs, or APIs

If done correctly, your users will see a quicker resolution of their incidents and you can significantly decrease your operational costs. So what are you waiting for! The time to create your AI Workforce has arrived. Talk to us to learn why Parlo is the preferred AI chatbot platform for our largest enterprise clients and technical service partners.

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If you found this article useful, please let us know your thoughts below. We regularly publish content like this on our blog in our mission to bring smarter AI to smarter enterprises.

Parlo builds smarter bots for smarter enterprises. We build AI chatbots that employ cutting-edge machine learning to seamlessly integrate with your business. They’ll support your human workforce, delight your customers, and save you time and money.

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What’s the big deal with AI chatbots and intelligent enterprise automation?

By Adi Subbarao on Oct 25, 2017 2:34:56 PM

As we enter the final quarter of 2017, the chatbot and AI landscape continues to grow and have a deep impact on the age-old practices of sales, marketing, and support in large enterprises. 

According to Suhas Uliyar, Oracle’s VP of Bots and AI, there is a rapid adoption of AI chatbot technology among enterprise customers for the following key factors:

  • Chatbots provide strong ROI by automating some of the repetitive end-user interactions, leaving the customer service agents to focus on high-value and high priority customers.
  • Chatbots are a great use case for adopting AI in the enterprise.
  • There is little to no additional cost to support multiple chat and voice channels, so businesses can reach more users without additional cost.
As Andrew Ng describes, AI will drive a new era of digital transformation and unprecedented productivity gains. In addition, according to a recent McKinsey Global Institute analysis, AI automation is projected to increase global productivity rates by 0.8-1.4% annually over the next 50 years!
As you can observe, the level of productivity growth driven by AI and intelligent enterprise automation has never been seen before. It is likely that the productivity growth will double that experienced during the IT revolution.


According to the AI Report from Woodside Capital Partners, “AI will enable companies to draw upon analytics across marketing, sales, and elsewhere to unify marketing automation, CRM, customer success analytics, content curation, etc.”

“By 2022, most sales and marketing communications, whether by professionals or customers, will be between humans and AI. Whether a personal assistant, a support bot, or a lead evaluation algorithm, AI will consume virtually all routine sales and marketing tasks...and be invaluable in increasing back-office productivity.”

For this reason, it is imperative for enterprises to embrace AI and develop a comprehensive strategy for automating customer and employee interactions.

Based on a 2016 KPMG study of 400+ U.S. CEOs, "a majority (85%) admit vulnerability about the amount of time they have to spend strategizing about the forces of disruption and innovation and an overwhelming majority are apprehensive about the integration of basic automated business processes with artificial intelligence and cognitive processes."

Therefore, in order to stay ahead of the competition, enterprise leaders must rely on technology service partners to stay focused on their digital transformation needs. In response, these technology service partners must seek out NLP and bot development platforms to expand their enterprise AI offerings. To further help these enterprise AI decision makers, we published an in-depth blog post highlighting the 5 Must-Haves for Selecting an Enterprise AI Chatbot Platform.

Estuate, a globally established IT services company, recently announced their AI Now solution empowering businesses to automate managed services using smart enterprise bots (eBots). AI Now is powered by Parlo’s enterprise AI bot platform, one of several ways in which Parlo brings smarter AI to smarter enterprises. If you would like to learn more about the Estuate and Parlo partnership, we are holding a joint-webinar next week entitled "AI Bots: The Digital Workforce for IT." 

In Conclusion

As AI chatbots and enterprise intelligent automation are on the rise, enterprises should be looking to leverage conversational technologies to drive increased cost savings, labor efficiencies, and enhanced customer experiences throughout their businesses.

In order to stay competitive, the smartest enterprises and technical service partners will embrace and develop an AI strategy which positions them for greater success. They will require smart chatbot solutions that can be rapidly built, deployed to their enterprise clients, and require minimal maintenance. These industry-leaders will be the ones who drive the greatest productivity gains over the next 50 years.

So, if anyone asks you about the future of AI chatbots and intelligent enterprise automation, you now know why it’s such a big deal.

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Want to discuss how Parlo is helping other enterprise customers and partners bring smarter AI to their enterprise? Request a call with us. We are currently offering a free proof-of-concept bot to enterprises looking to embrace AI in their core business.

Parlo builds smarter bots for smarter enterprises. We build AI chatbots that employ cutting-edge machine learning to seamlessly integrate with your business. They'll support your human workforce, delight your customers, and save you time and money.

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Parlo featured in VentureBeat's 2017 Intelligent Assistance & Bot Landscape

By Adi Subbarao on Oct 20, 2017 3:22:54 PM

VentureBeat recently published their 2017 Intelligent Assistance and Bot Landscape featuring Parlo alongside industry leading conversational NLP and bot development platforms.

Edited Landscape.png


This is very exciting news for us since it demonstrates Parlo's combined offering as an enterprise NLU service and an enteprise bot development platform:

  1. Broca - Parlo's Most Advanced NLU for Enterprise 
  2. The Parlo AI Bot Platform


Broca - Parlo's Most Advanced NLU for Enterprise

Broca is a one-of-a-kind NLU service — incorporating semantic parsing, grammar engineering, and machine learning capabilities. Put simply, Broca understands language and recognizes relevant tasks in a similar way to how the human brain operates.

Broca includes the following new features requested by customers:

  1. Complex intent and entity recognition for intelligent user interactions
  2. Vocabulary manager to easily tune models to your enterprise language
  3. Cloud and on-premise models for added privacy and security
  4. Integration with Parlo AI platform to make bot building easy and seamless

Parlo AI Bot Platform

The Parlo AI Bot Platform is a visual bot-builder that allows for rapid bot development and prototyping with minimal coding required. It is powered by our Broca NLU service to create AI bots that can call external web services and integrate with enterprise software systems using REST-based APIs.

If you would like to discuss how Broca or the Parlo AI Bot Platform can help your enterprise, please request a call with us. We are currently offering a free proof-of-concept bot to enterprises looking to embrace AI in their core business.

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Parlo builds smarter bots for smarter enterprises. We build AI chatbots that employ cutting-edge machine learning to seamlessly integrate with your business. They'll support your human workforce, delight your customers, and save you time and money.

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5 Must-Haves for Selecting an Enterprise AI Chatbot Platform

By Adi Subbarao on Oct 11, 2017 3:17:42 PM

So you’ve decided to invest in a smarter AI chatbot solution for your enterprise. Congrats!

You are now among the growing number enterprises looking to use AI-powered chatbots as a method of driving cost-savings, labor efficiencies, and enhanced customer experiences throughout your enterprise.

According to a recent Forrester survey of 7,000 consumers across 12 countries, 

  • 75 percent of service provider AI decision makers say that 85 percent of customer interactions will be with software robots in five years’ time. 
  • 65 percent of these decision makers fear they are lagging behind their competitors in the use of AI to improve the customer experience.
  • 49 percent plan to increase their AI budgets by at least six percent in the next 12 months and
  • 87 percent intend to expand their AI workforce.

As you can see, there is a growing need for enterprises to intelligently manage a dialogue between consumers, employees, and back-office business softwares. In order to do this successfully, choosing the proper chatbot platform for your enterprise is a critical step to ensuring intelligent, scalable, and cost-effective conversations in the future.

Selecting the Right Enterprise AI Chatbot Platform

There are currently hundreds of chatbot platforms to choose from who all claim to provide the “smartest” chatbot solution customized to your enterprise. However, only a handful may actually meet your specific chatbot requirements and deliver the cost-savings, labor efficiencies, and enhanced customer experiences you are looking to achieve for your enterprise.

At Parlo, we understand that choosing the right enterprise AI chatbot platform is a time-consuming, but crucial part of developing a successful AI strategy. In order to ease this decision-making process, we have laid out the following 5 most important criteria for AI decision makers to consider when selecting the right enterprise AI chatbot platform:

  1. Learning
  2. Understanding
  3. Deploying
  4. Training
  5. Pricing

1. Learning

An employee’s job effectiveness is dependent on his/her knowledge of the job. Similarly, the effectiveness of a chatbot solution is dependent on its knowledge base and ability to learn on the job.

When evaluating various AI chatbot platforms, it is important to ask:
“How will my chatbot learn on the job?”

Some platforms require you to manually teach your bot basic skills:
Customer asks question A…chatbot responds with answer A.

While this approach works in theory, it is a very time-consuming process. Unless you have a team of dedicated engineers who can monitor each input and output to become the chatbot’s “English teacher,” this method will lead to more frustration than success.


The better solution is to choose a chatbot platform that can ingest knowledge from your enterprise corpus in the form of chat logs, emails, knowledge bases, CRM data, and documents. 

This method allows the chatbot to learn very rapidly and dynamically based on historical conversations between your enterprise customers and employees.


Rather than being an “English teacher” you can simply guide the chatbot to the the right resources and let the chatbot learn independently on the job.

However, even if your chatbot is self-learning, you will still encounter complex business requests that a chatbot will not be adequately prepared handle. This leads us to our second criteria of evaluating a chatbot platform’s natural language understanding (NLU) abilities.

2. Understanding

According to Forrester, “The top need of enterprises using AI bots is the ability to deal with more complex requests.” And when it comes to consumers, they “love the speed and convenience of chatbot but don’t want forced interactions until these chatbots are more human and smarter”.

Chatbots are only as effective as their ability to break down complex language and execute complex tasks. For this reason, it is important to choose a chatbot platform that builds smarter bots using advanced AI and NLU capabilities.

Let’s take a look at an example:


In this sentence, most chatbots would understand that the user intends to make a purchase. However, a basic NLU service is likely to request more specific product information and completely disregard half of the user’s intent: “Please ship those shoes to my home.”

On the other hand, an advanced enterprise AI chatbot platform would break down complex language by detecting multiple user intents and entities.

The chatbot should recognize the word Minimus as the product type, black as the product color, and 10 as the product size. It should also be smart enough to set your home as your shipping location, leaving the next logical response to be “What is your home address?”

Here is another example involving complex entities:

“I would like to meet you by the Starbucks near the mall.”

A basic chatbot would detect either Starbucks or mall as the location and proceed to ask “Which Starbucks/mall?” as there are several dozen in the area.

A smart chatbot would find the differences between each location entities (Starbucks and mall) and preserve their relationship. It would understand that near the mall is describing a specific Starbucks location.

The ability to 
1) break down multiple complex intents and entities and 
2) understand unique enterprise terms and language (i.e. Minimus) 
is what sets a smart chatbot’s understanding ability apart from more basic chatbots.

3. Deploying

After building a smart chatbot for your enterprise, your next criteria should be how to deploy this chatbot in a quick, safe, secure, and scalable way.

Fully Integrated Solution

The most robust enterprise AI chatbot platforms provide a dialogue manager, NLU service, and behavior engine as an integrated offering in their platform tooling. If any of these pieces are missing from a chatbot platform vendor, then you risk stalling your chatbot project while building out custom integrations to your conversation channels and enterprise software systems.

Here is what a fully integrated chatbot platform should look like:


Time to Market

It is important to understand how long it will take to bring your chatbot solution to market. You should discuss ways to ensure a quick and reliable timeline when launching and refining a chatbot solution.


Most advanced enterprise chatbot platforms take between roughly 1–2 months to build and deploy a fully integrated AI-powered enterprise chabot solution. You must also budget another 1–2 months to refine each iteration of your chatbot solution to meet customer and employee expectations.

Be aware of how other chatbot platform vendors approach the deploying, testing, and refining phases of the chatbot development cycle. Ultimately, you must determine whether your chatbot solution can be deployed in accordance with the timeline and objectives set for your enterprise.



Data Security

The most robust enterprise chatbot platforms allow customers to build their chatbot on-premise. This allows the enterprise to have full control over the chatbot experience and securely manage all chatbot conversations within their enterprise environment. This is especially important if your enterprise deals with financial data, healthcare records, or other personal customer account information.

More basic platforms will only allow chatbots to be built on a cloud server, allowing minimal access and visibility into the chatbot data being collected. This could leave your enterprise vulnerable and exposed to critical security threats.

Deployment Channels

Finally, an important aspect of deployment is the various channels where a chatbot can live. Most basic chatbot platforms today allow for chatbots to live on Facebook Messenger. This channel works well if you are primarily interested in building simple marketing and support bots. However, if you are a large enterprise planning to drive conversations relevant to customer experience, IT service, finance, payroll, or other internal employee interactions, Facebook Messenger alone will not cut it.



Enterprise chatbots must be able to live on messaging applications, websites, mobile apps, and voice assistants in order to create an end-to-end conversational experience for your customers and employees.


4. Training (AKA continuous learning)

The fourth and arguably most important criteria for evaluating an enterprise chatbot platform, is the ability to train the chatbot for future conversations. Similar to the learning criteria, many chatbots require hand-holding in order to be consistently accurate when responding to customer and employee requests.

For example, let’s say your chatbot generates 10,000 messages per day. There may be up to 6 natural language understanding (NLU) predictions that appear for each response. This would mean that you would have to manually train up to 60,000 NLU inputs daily in order to adequately train your chatbot.

Ask yourself, “Is this really scalable?”


Enterprises need a chatbot solution that reduces its dependence on a human-in-the-loop to support a chatbot’s continuous learning. The best enterprise AI chatbots automatically become smarter with each conversation (using machine learning and semantic modeling) which lessens the burden of constantly having a human-in-the-loop for training purposes. The only instance where manual training would be required is to teach the chatbot unknown or new vocabulary.

It is the combination of learning, understanding, and training which indicates the intelligence of an enterprise chatbot. If you are searching for an enterprise chatbot platform that can create human-like chatbots, you will want to choose a platform that does all of these well.

5. Pricing

Finally, we must mention what is on every decision maker’s mind when evaluating a new enterprise AI chatbot platform: pricing.

Today’s enterprise AI chatbot platforms use a combination of the following three pricing models:

Monthly license fee:

-Build limited/unlimited bots for a fixed monthly cost

A platform license fee will provide you with regular chatbot support and server maintenance so you can build and manage chatbot conversations at scale.


-Cost is based on usage of the chatbot and number of software API calls

A pay-per call pricing will give you flexibility to pay-as-you-go when launching your chatbot.


-Cost is paid out of the savings generated by the chatbot

A pay-per-performance pricing monitors and optimizes your chatbot conversations to attain certain performance metrics (KPMs). You are guaranteed savings using this model, and will be charged accordingly to the goals you do or do not achieve.

As you look for an enterprise AI chatbot platform, you should find a model flexible to your needs.

Ultimately, while there are merits to each of these pricing models, we believe that an investment in any enterprise AI chatbot platform is also an investment in a strategic partnership. Regardless of the pricing model you agree upon, it is important to be working with an experienced team who understands your enterprise’s needs, priorities, budget, and strategic goals.

In Conclusion

Evaluating an enterprise AI chatbot platform is a challenging task for even the most knowledgeable AI experts. Therefore, we believe you should focus on the learning, understanding, training, deploying, and pricing value that each enterprise AI chatbot platform brings to your enterprise’s strategic AI needs.

There are many large enterprise AI chatbot platforms to choose from including Microsoft LUIS, IBM Watson, RASA, Amazon Lex, Google Dialogflow, and Facebook Wit.ai to name a few.

All of these platforms approach our 5 criteria with varied success. However, there is no one-size-fits-all platform to satisfy the AI needs of all enterprises.

The Parlo AI bot platform proudly differentiates itself by creating custom AI chatbot solutions for each enterprise we work with. Talk to us to learn why Parlo is the preferred AI chatbot platform for our largest enterprise clients and technical service partners.

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If you found this article useful, please let us know your thoughts below. We regularly publish content like this on our blog in our mission to bring smarter AI to smarter enterprises.

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