What is the best way to create a chatbot: Platform vs. Custom

Chatbot integration with a website or mobile app is a win-win strategy for both your business and your clients. Why? Firstly, thanks to various use cases, chatbots can increase revenue by up to 25%, lead generation to 9.5%, and improve engagement with clients by 35%. Secondly, your customers receive a better UX experience of finding and ordering goods or services, paying for them seamlessly, and more. Are you ready to integrate a Chabot into your business strategy? Great! But the question is, “Whether to build a custom-made Chabot or use a Chabot building platform”?

Let’s find out. 

Below, we have gathered the main chatbot types, their usages, and a comparison of custom vs. platform-build chatbots. After reading this article, you will know exactly what kind of chatbot you need. Depending on its type, you will know whether you need a custom chatbot or platform-build solution. 

Main types of chatbots

A chatbot is a computer app that mimics human behavior during a conversation with a real person. But, the degree of chatbot’s humanity depends on the complexity of the technologies behind the app. Now, let’s look at the Chabot types in more detail:

Type 1: Scripted/Quick Reply Bots

Scripted is the simplest type of chatbot. Such chatbots are powered with decision three hierarchy and communicate with people using predefined scripts via a set of questions or buttons. Such scripted chatbots are the slowest medium of getting the user to their desired value. 

Burberry scripted bot

[Burberry scripted chatbot] 

Type 2: AI Chatbots

AI chatbots are more complex than scripted chatbots and include two subdivisions: 

  • Chatbots with Natural Language Processing 
  • Content Enable Chatbots with Machine Learning 

Now, we will take a closer look at these types:

Natural Language Processing (NLP) chatbots can understand, analyze, and prioritize questions according to their complexity. NLP chatbots are programmed to recognize particular keywords. Then, such chatbots respond appropriately with a non-pre-scripted response. More advanced NLP can even understand your message intensity, i.e., whether you are asking a question or make a statement.

Booking chatbot

[Booking.com NLP chatbot]

Content Enable Chatbots. Powered by Machine Learning (ML) and Artificial Intelligence, Content Enable chatbots are the more advanced type. ML chatbots learn from conversations that happened in the past with a specific user and grow over time. Examples of such chatbots are Siri, Alexa, and AI versus, created and taught by our team, ISD GmbH, and Hoskhod agency. To learn more about this project, read the full case study.  

Now, let’s look at how you can use a chatbot for your business. 

Chatbot use cases

You can use live chats and chatbots for multiple business areas, including customer support, streamlined payment, shopping assistants, and even healthcare assistants. Many marketers agree that such chat options are here to stay as automation continues to make advances. Now, chatbots can cover the following usages: 

FAQ assistants

Chatbots, in most cases scripted, can perform as live FAQ and process over 80% of support queries. It means that the customer can ask them questions and receive an answer. But, to create such a chatbot, you need something more than integrating FAQ section materials into a chat interface. FAQ chatbots should also be able to ask follow-up questions and connect the user with a real person if needed. 

Such chatbots are used for both websites and mobile applications, and one example is the “Kate” chatbot, a mobile app digital assistant, developed by Geico insurance company. App users can ask Kate questions, via both voice and text, and receive answers about billing and basic policy.

Navigational botsshopping assistants

Navigations bots help website or mobile app users search for specific information such as blog articles, a particular website page or product, via a conversational interface. You can use the navigation chatbot to direct customers to the most relevant product. Firstly, the user tells a chatbot what product one is searching for. Next, the navigation bot shows the user all the products that match the user’s request and sends links to those items. To achieve this, the chatbot back-end is integrated with catalog and service-side API. Still, such chatbots are something more than navigation menus. Shopping assistants can even adopt changing messages and themes, send holiday greetings or information about an actual sale. 

Shopping assistants are widely used in the clothes and fashion industry. An example is the H&M bot on the KiK platform, which understands user style preferences, gives personalized style recommendations, and even builds an outfit. 

Healthcare assistants

Chatbots help clinics and hospitals save a considerable amount of money. In the healthcare industry, chatbots can perform as online receptionists, nurses, interns, or even assist with a patient progress report, assess drug interactions, and check post-op recovery. 

Besides, chatbots can make medical diagnoses faster, as MedWhat chatbot does. Thanks to the ML algorithm, MedWhat chatbot provides users with increasingly accurate answers on questions concerning medical diagnoses. Besides this, thanks to machine learning, the bot learns from each interaction with a patient. MedWhat bot expands existing medical data using a vast volume of medical research and peer-reviewed scientific papers. 

Recommendations and Booking agents

In industries like hospitality and traveling, chatbots can be used as personal traveler assistants or virtual concierges. In this way, customers receive 24/7 online support, which impacts customer loyalty and satisfaction. You can integrate such chatbots into a website, and even a Facebook Business page, like the SnapTravel agency has.

Using the SnapTravel Messenger bot, travelers can find the best accommodation that meets their preferences and budget. This bot is powered by Artificial Intelligence and works as an aggregator. You need to enter the dates and city you want to go to. Then, Snap bot analyzes offer from Expedia, Priceline, and other travel websites, to come up with the best deals. After selecting the best option, the user can book accommodation right through Messenger. 

Lead generation and retention bots

Chatbots might also be a part of a content marketing strategy and generate more leads from social media or websites. Besides this, a retention chatbot could activate your old leads by sending them sales alerts or relevant updates as TechCrunch Messenger chatbot does. It informs subscribers about stories on relevant topics. To achieve this, users need to subscribe to sections, authors, and topics on the TechCrunch website, and then the bot sends news articles, and other updates, right to the user via Messenger. 

Transactional bots

This type of chatbot is much different from other use cases on this list. The main goal of transactional chatbots is to simplify user experience and provide a convenient and quick channel for completing a particular action. Transactional chatbots allow users to place new orders and repeat purchases and even conduct an online payment. 

An example is Pizza Hut’s bot that helps users place orders for pizza and other meals via Twitter or Facebook. The bot also informs customers about recent promotions and answers FAQ questions.

Have you selected a perfect type and usage case for your chatbot? Great!

Now, let’s find out whether to build a bot with a builder or make a custom bot from scratch. 

READ ALSO: NLP Business Applications

Platform-based chatbots

Chatbot platforms allow you to make your own chatbot by yourself. While some chatbot-building platforms have a simple drag-and-drop menu, others require a degree of technical knowledge. Now, we’ll take a look at the most popular platforms for building chatbots, their capabilities, and price policies. 

Flow XO


Azure Bot Service





Where to use

·       Facebook Messenger

·       Slack

·       Twilio SMS

·       Telegram

·       Website

·       Facebook Messenger

·       WordPress

·       Shopify websites

·       Website

·       Mobile app

·       Cortana

·       Skype

·       Slack

·       Facebook Messenger


Main features

·       Simple questions answering

·       User answers validation

·       Switch between a chatbot and live chat

·       Accept payments

·       Build-in templates

·       Online chat

·       Payments

·       Call button

·       Switch between a chatbot and human agent

·       Support integrations via JSON API

·       Natural Language Understanding

·       Open-source SDK

·       Native integration of Azure Cognitive Services.

·       Any type of bots: from a Q&A bot to your own branded virtual assistant


·       Standard Plan – $19 per month


·       5 bots or active flows – $10 per month

·   25,000 interactions- $10 per month

·       Free – up to 1000 Subscribers

·       Pro – from $15 per month

·       Premium – from $199 per month

·       Free – 10,000 messages/month

·       Premium channels- $0.50 per 1,000 messages

So, what are the advantages of bot-building platforms?

  • Chatbot builders are handy for developing simple or even sophisticated chatbots for any business
  • You can integrate your chatbot to most popular messaging platforms, such as Messenger, Telegram, Skype
  • Some platforms allow integrating a chatbot right to your website or mobile app
  • You can connect your chatbot with third-party services such as payment gateway 
  • Chatbot-building platforms are cheap or even free 
  • By using a platform, you can set your business logic of chatbot behavior

At the same time, chatbot building platforms have some disadvantages:

  • You can only create a chatbot with simple logic. For more complex chatbots, you will need  help from developers 
  • Chatbot-builders’ tools may not always help you achieve your desired results.
  • If you are not a tech person, you will need more time and effort to make a chatbot. However, there is no guarantee that the chatbot will perform well.

Building a chatbot from scratch

If you want to create a sophisticated chatbot with your own API integrations, such as a shopping assistant, booking agent, or healthcare assistant, consider developing a chatbot from scratch. You can create a solution with custom logic and a set of features that ideally meet your business needs. Such chatbots work as a server-side application that implements chat features via its own API. To create your own custom chatbot, you need to hire a development team for chatbot development services. If your chatbot requires the integration of Natural Language Processing, the development team will use Opennlp or Nltk NLP tools. In this case, consider that NLP will perform as a separate service.  

Below, you can find our feature list of a custom chatbot MVP for a travel agency with estimation in hours. 


Functions required




Customization for agents

  • Logo
  • Agent Name


Connection to Data Server API


Switching between a chatbot and human agent

  • Switch between Human Agent and Chatbot
  • Return, Forward functions for user


Gathering of data from the user (Search for hotel, tour, full package flow)

  • Dates
  • Number of adults
  • Number of Infants
  • Meal
  • Hotel stars


Transferring Data to API and receiving results


Tour Proposals

  • Show search results


Show more variants


Admin Panel

Admin Login


Chatbot Management

  • Define questions and answers




From 240 hours

In our experience as a chatbot development company, developing a custom chatbot starts from $4000 and takes from 240 hours of coding

By developing a custom chatbot you will receive the following benefits: 

  • You can integrate complex and unique functionalities to your chatbot
  • Your development team will provide your bot with excellent user experience, as well as helping you to find the right technical solution for your business needs. 
  • The development team will conduct tests of your chatbot to ensure that it is bug-free.
  • After the bot release, the development team will provide you with technical maintenance and further bot improvement. 

However, there are also some drawbacks: 

  • Developing a custom chatbot takes more time and costs more than developing a bot via the building platform. 
  • To develop such a solution, developers will need to create service infrastructure and hosting, which also takes time. 

Now, let us compare developing a chatbot with a platform and a custom solution. 

Platform vs. Custom: Chatbot development comparison




Initial cost


While some bot development platforms are free of charge, others will charge a fee:

·   Monthly

·   Per user

·   Per transaction basis



The cost will depend on:

·   Experience of the developers

·   The number of developing hours

·   Bot usage case

·   The number of platforms required

·   The number of chatbot users

·   The number of third-party integration such as an online store or a CRM

·   API integration




You can simultaneously plan and build a chatbot using a flowchart-like or drag and drop interface

Here, you need to consider the integration of a chatbot with:  

·   NLP

·   Analytics

·   Payments

·   Subscriptions

·   Integrations

·   Platforms

All elements will work together, which increases both chatbot complexity.

Build Time


By using ready-made templates, you can integrate a simple chatbot in messenger in less than 30 seconds.

The chatbot building time depends on

·   Number of developers

·   Number and complexity of features

·   Number of integrations




You need to test the Chabot on your own. You can receive support on Chabot testing via a test/development chat within the platform.

The developing team will conduct the bench of the test to ensure that your bot operates correctly.




You can make changes and integrate new scenarios on your own without coding.

Only developers can make changes in the bot code.

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What to choose: platform-build or a custom chatbot?

There is no single answer since the solution will depend on the complexity of your chatbot, its’ usage case, number of integrations, and so on. 

Chatbot builders suite for developing:

  • FAQ bots
  • Transactional chatbots 
  • Navigation bots
  • Lead generation bots

Besides, you can use chatbot builders if you are in a hurry, have a tight budget, and need simple functionality. However, even platform build-solutions may be complex and apply MLP, AI, and machine learning. For such cases, you need to hire a development team to set up and teach the sophisticated chatbots for you. 

Custom chatbots are great in the following use cases:

  • Shopping assistants with AI and machine learning 
  • Healthcare assistants 
  • Medical diagnoses bot
  • Hospitality chatbots and personal concierge
  • A bot with catalog and service-side API integrations

In a nutshell

Chatbots vary in the level of their complexity, usage cases, and industries. Still, with such great diversity, you can find the option that will ideally meet your business needs. To achieve this, you need to answer the following questions: 

  • What is the purpose of the chatbot?
  • Where will you use it: in a messenger, website, or app?
  • How complex should it be?
  • How many features should it have?
  • Do you need to integrate it with third-party services, such as analytics or payment gateway?  

After answering these questions you will have a clear idea of whether to build your own custom chatbot or use a bot builder. 

Related articles:






Chatbot for travel industry: benefits, use cases, and a development guide

What does a perfect vacation overseas consist of? Before taking a sunbath on the beach, you need to spend time to find accommodation within your budget, book a flight, and spend at least two hours to check-in — that’s how this was before chatbots in the travel industry appeared. Now, using a chatbot and your smartphone, you can book and pay for hotels, flights, and even check-in online without a hassle. 

If you want to develop a chatbot for your travel agency, this article is right for you. Below, we share the most successful usage of travel chatbots and a step-by-step guide on how to develop one. 

But first, let’s find out what the advantages of using a chatbot for your travel business are. 

Why you need a travel chatbot for business: top 5 benefits

Online travel companies are simplifying the way we organize our vacation. When planning a trip, around 84% of travelers use online travel booking agencies, such as Kayak, Expedia, or TripAdvisor. Still, the market of travel booking is flooded with irrelevant options, and to find the best one, travelers visit 38 sites on average, and for 62% of travelers, it is hard to find the right deal. At the same time, Huxley’s survey said 87% of travelers want to interact with a travel chatbot to find the best accommodation while saving time for the indecisive search. Moreover, 79% of them expect a travel chatbot to perform as an online travel concierge

And now, let’s look at chatbots from a business perspective.

Consider integrating a chatbot to your travel business, since it will bring the following benefits: 

  • Increase engagement. As we have said, travelers are looking through various travel websites to find the best trip. At the same time, if your online travel chatbot can provide users with relevant offers, your agency will become more valuable for your clients and increase the engagement rate. 
  • Reduce workload and operation costs. When a traveler is interested in a particular tour or hotel, one is more likely to ask a question to receive more information. The bad news is that your customer support team spends at least two hours a day answering repetitive questions. FAQ chatbot can provide travelers with answers to basic questions, thus reducing both the workload on your employees and customer support costs up to 30%.
  • Increase sales. Travelers want to book a hotel, rent a car or pay for their ticket as quickly as possible and find long forms an unpleasant and irritating experience. Thanks to the integrated payment gateway, a Messenger travel chatbot could seamlessly get your customers through the sales funnel and close a deal with fewer interactions. To achieve this, travelers need to enter their credit card information into Facebook Messenger, and the platform will save it for next friction-free payments. 
  • Built community. Apart from business logic, like built-in payment and booking, a chatbot could be a handy tool for building a community around your travel agency by sharing their travel experience and inspiration. To achieve this, you can cooperate with influencers and travel bloggers, post their articles or videos in your blog, and suggest this content to travelers via a chatbot. 
  • Attract new customers. Customer acquisition cost is an essential metric, not only in travel but also in other industries. Proactive travel chatbots decrease CAC and attract new customers most effectively by starting a conversation. You can empower a bot to send a welcome message to anyone who makes a booking on your website or place a comment on your Facebook page. Besides, your chatbot can send relevant information based on keywords used by your customers. 

In a nutshell, chatbots can improve the booking experience of your customers by providing them with more relevant recommendations, while enhancing your business metrics and saving operation costs.  

The most successful use cases of travel agency chatbots

And now, let’s find out about famous travel chatbot use cases and what results they receive from such an integration. 

  • Reservation agent

By using this type of chatbot, travelers can book airline tickets, make hotel reservations, car rentals, cruises, and even vacation packages via their website or Facebook page. To get relevant offers, travelers need to provide the bot with their requirements such as destination, date, type of accommodation, price range, and so on. 

The chatbot by travel agency Expedia.com works on this scenario. After the user receives relevant hotel search results, one is redirected to Expedia’s website to make a direct booking. Then, the chatbot sends a user a link with itinerary in Messenger. Apart from Facebook Messenger, travelers can use this bot on Amazon Alexa virtual assistant and ask for booking updates via voice commands. 

  • Personalized digital travel assistant

With natural language processing (NLP), travel chatbots recognize particular user queries such as “exotic Japanese weekends” and provide one, not only with hotel recommendations and transportation but also with local places to visit. Travelers receive immediate and relevant recommendations without conducting long surveys. Moreover, such chatbots help travelers to find the nearest rental car service and give local weather forecasts while keeping in mind the traveler’s budget and even dietary requests. In this way, personalized travel assistants help travelers at each stage of their travel and keep all their documents and tickets in one place.  

One example is the Mezi AI chatbot, recently acquired by American Express. The company motto is “everyone traveling for work deserves a first-class experience.” This chatbot allows travelers to book hotels, flights, and even a table at restaurants.  

  • Customer care manager 

This use case of travel chatbot provides travelers with check-in notification, flight status updates, boarding pass, and even booking confirmation via the chosen channel, and simplifies the customer service. 

This exact type of chatbot is used by KLM Royal Dutch Airlines, built on the DigitalGenius platform. The company’s AI chatbot, trained with over 60,000 questions and answers, can provide travelers with non-pre scripted answers about information and updates on their flight via Facebook Messenger. After the bot launch, the KLM Facebook page received 40% more messages. Currently, KLM chatbot speaks 13 languages and responds to 15,000 queries in Messenger weekly. Since its release date, KLM chatbot answered 1.7 million messages sent by over 500,000 people.

Apart from social media networks, KLM also developed a chatbot for Google Assistant. The bot answers frequently asked questions, provides information about airline requirements via voice, and can even give tips on how to pack bags for a flight based on destination.

  • Two-sided chat agent 

If you own a two-sided travel marketplace, this bot travel use case will be useful for your business. This type of chatbot connects travelers and hotels to check hotel availability, look up necessary information such as check-in times, or parking reservations. The two-sided nature of this chatbot allows hotels to send notifications in response to user queries. 

This type of travel chat app was developed by Booking.com, a travel marketplace. Right now, the chatbot can respond to 30% of customers’ hotel-related questions in under 5 minutes, according to Booking.com.

  • Local insider

Many travelers are going to another country searching for an authentic experience. They want to eat, entertain, and live as the locals do. If you’re going to provide travelers with local recommendations on restaurants with local cuisine, festivals, and other activities, a local insider chatbot will be the best choice. In this way, your customers will receive relevant information without spending hours searching for the most recommended places on social networks. 

An excellent example of such a tourism chatbot is Bebot, launched on the threshold of the Tokyo 2020 Olympic Games. The main goal of this bot is to illuminate cultural and language barriers for an increasing number of foreign tourists. This bot help users to receive personalized recommendations on sights, local food and helps navigate around the country. 

Bebot travel recommendation chatbot

[Source: Medium]

How to develop a chatbot for a travel agency in 6 steps 

Below, we have gathered the main steps you need to complete to create the best chatbot for your travel agency. 

Step 1. Decide the chatbot’s functionality

At this step, you need to define the purpose of your chatbot, set up goals and objectives. To determine the proper chatbot objectives, you need to answer the following questions: 

  • What is your business size? 
  • Do you need a chatbot to handle customer queries or to entertain people? 
  • What business process you want to automate with your chatbot? 
  • How many people will use your chatbot? 
  • Do you need an integration of your chatbot with databases, CRM, or CMS? 

After answering these questions will help you have a clear idea about your chatbot project, and you can enter the next step. 

Step 2. Choose the chatbot type

Once you know the objectives of your project, it will be easier for you to choose the right chatbot type from  among the following: 

Rule-Based or Scripted Chatbots are the simplest type because they use a decision tree to communicate with users. When communicating with users, scripted bots recognize keywords and channel them down the correct path to achieve their goals, like information about current best deals, and so on. Such chatbots have a very limited skill set. Still, you can use them for simple tasks such as:  

  • Customer support agents that provide customers with automated responses 
  • Engagement bots that inform customers about special offers 

Rule-based chatbot

AI-Powered Chatbots are more complex chatbots, often empowered with Natural Language Processing (NLP) and Machine Learning (ML) algorithms. Unlike rule-based chatbots, AI-powered bots can answer a user with non-pre defined responses, and ML helps them to learn from each integration with the user and remember one’s preferences.

Choose this type of chatbot if you want to develop: 

  • Booking agents that help users to buy or book something 
  • Recommendation agents that gather requirements from the customer and then show relevant results 
  • Personal travel concierge that will help users find, not only hotels but also book flights and provide the user with local insights  
  • Comparison chatbot that will compare hotel rooms and flight ticket prices 
  • Automated check-in chatbot that allows the user to check-in to the flight or hotel 

AI powered chatbots

ML chatbot for travel agency

Step 3. Evaluate chatbot channels 

Now, you should consider where you can use your chatbot. The most popular channels for chatbots are: 

  • Embedded chat on your travel website, 
  • Your mobile travel application;
  • Mobile carrier channels (SMS, USSD)
  • Messaging app (Facebook Messenger, WeChat, Kik, Line, Viber)
  • If you want to use a chatbot in both your website, Facebook Messenger and Telegram, you can create an omnichannel chatbot, 

Then you need to make sure whether or not the chosen channels offer an open API, so your travel chatbot developers can integrate it easily. In this case, the most effective strategy is to select the most popular channel among your users and integrate a chatbot to other channels with time. 

Step 4. Choose the best platform 

Depending on your chatbot type and communication channel, you will select the platform to build your future chatbot. 

To build a scripted-based chatbot with if/then logic, you can use one of the following platforms: 

  • Hubspot conversations
  • Chatfuel
  • Facebook Messenger

Since these platforms have an intuitive drag-and-drop menu, you can create a chatbot without hiring chatbot developers. 

However, if you want to create a more sophisticated AI and ML bot that solves complex business tasks, consider that you’ll need to hire chatbot developers for initial bot settings and training. As for a technological solution, consider the following platforms for building AI chatbots: 

  • AWS
  • Wit.ai
  • IBM Watson Assistant
  • Microsoft Bot

If you need to create a custom chatbot, you will need to hire chatbot developers to work on the following custom chatbot components:

  • The script of the custom chatbot will include the whole dialogue from a greetings message, which gathers the user’s requirements, to the “goodbye” message. Also, consider those scenarios where the bot will not understand the user’s input and cases when the bot will need to switch the communication with the traveler to a human agent. 
  • NLP, also known as Natural Language Processing, helps a chatbot to extract the user intent, i.e., understand what your users want by defining particular entities in the message.
  • The backend of a custom chatbot should process messages with Natural Language Processing. The custom chatbot backend should also comprise business logic and include third-party integrations, like payment gateways. 

Step 5. Develop a chatbot MVP

Now you need to hire chatbot developers that will help you to prioritize the chatbot’s business tasks and implement the most important features in the travel chatbot MVP.

An MVP means a minimum viable product. This approach is used in software development when a client wants to test a hypothesis without spending a considerable amount. 

To give you an idea of the travel chatbot’s main features, as well as the project scope, we made a travel chatbot MVP estimated in hours. 


Functions required



12 hours

Customization for agents

  • Logo
  • Agent Name

60 hours

Connection to Data Server API

16 hours

Switching between a chatbot and human agent

  • Switch between Human Travel Agents and Chatbot
  • Return, Forward functions for user

32 hours

Gathering of data from a user (Search for hotel, tour, full package flow)

  • Dates
  • Number of adults
  • Number of Infants
  • Meal
  • Hotel stars

32 hours

Data transferring to API, receive results

16 hours

Tour Proposals (Search Results)

  • Show search results

8 hours

Show more variants

16 hours

Admin Login

8 hours

Chatbot Management

  • Define questions, and answers

40 hours


From 240 hours

Step 6. Enrich chatbots for the travel sector with additional features

At this step, your development team launches the chatbot MVP. But this is not the end of your chatbot development process. Why? Because at this step you need to thoroughly analyze how your chatbot interacts with your customers. To achieve this, ask your customers to test your chatbot and give feedback. You may also ask them what features you need to implement to your chatbot during the second development stage. Consider that chatbot creation is an iterative process that includes gathering the data, reviewing and applying changes to the chatbot. 

Now that you are aware of the main steps of chatbot development, it is time to find out about chatbot development costs. 

How much does it cost to develop a chatbot: rule-based vs ai vs custom 

As we have said, you can create a simple rule-based chatbot with DIY platforms, so you save money on chatbot developers. Most chatbot platforms are free to use, but also have paid premium plans: 


Pricing plans 

Hubspot conversations

Free of charge 


  • Basic plan- free, up to 1000 Subscribers
  • Pro plan – from $15 /month gives more advanced features 
  • Premium – from $199/month gives advanced tools and expert guidance.

Facebook chatbot

Free of charge 

To develop AI-based chatbots you will need to hire a chatbot development team for bot training, third-party integrations and other settings. Consider that the hourly rate of chatbot developers varies from country to country and level of experience.

Front end developer hourly rates across countries:  

  • The U.S. from $90/hour 
  • Western Europe from $60/ hour 
  • Eastern Europe from $40/hour 

Back-end developer hourly rates 

  • The U.S. from $120/hour 
  • Western Europe from $80/ hour 
  • Eastern Europe from $50/hour 

 In addition, take into account the following costs charged by  AI chatbot development platforms:  


Pricing policy 


Free plan – up to 10,000 text requests and 5,000 speech requests per month 

After a year’s trial period, you are charged based on the number of text or voice requests processed by your bot:

  • $0.004 per voice request, 
  • $0.00075 per text request


On request

IBM Watson Assistant

  • Free plan – 10,000 Messages/month
  • Standard – from $0.002675 USD/message
  • Plus – On request

Microsoft Azure Bot Service

On request

The cost to create AI chatbot starts from $6000, and the development stage takes 3 months. 

As for custom chatbot development, this is the most costly option. To create a custom chatbot you need to hire a development team, including front and back end developers, designers, QA engineers, and project managers, who will work on your project. That is why custom chatbots are so expensive – the price of custom chatbots starts from $40,000, and the development stage might take from six to eight months.  

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Wrapping up

If you want to stay ahead of competitors, provide customers with a high-quality customer experience, and keep them engaged, your travel business needs a travel chatbot. 

With many usage cases, you can develop a chatbot to meet the needs of a travel business of any size. 

Besides, with a wide range of DIY building platforms, you can even create a simple chatbot by yourself. 

But, if you want to automate business operations with an AI travel chatbot, you will need to hire a chatbot development team for initial bot settings. 

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How Mental Health Chatbots handle stress?

The rapid development of natural language processing and conversational interfaces has enabled a more progressive way of dealing with mental health problems, stress management, and psychological relief. 

It’s a big deal. According to the World Health Organization research, more than 300 million people are suffering from depression alone, not to mention other types of mental issues. Just a couple of months ago burnout was officially recognized as a medical condition. And this kind of thing is almost inevitable among professionals of any field. 

According to a Scientific American study, the economic cost of depression in the United States accounts for hundreds of billions of losses per year.

And while the need for mental health services is getting higher, its availability is unable to catch up. In this environment, the traditional means of psychological relief and stress management aren’t efficient enough. 

If you want to make Mental Health Chatbot, this article is right for you. In this article, we will look at: 

  • What mental health chatbots are?
  • How do mental health chatbots work?
  • Four major mental health chatbot applications and their business models;

What are mental health chatbots? 

A mental health chatbot is a type of a conversational interface application designed to: 

  • Have a conversation with the patient regarding his mental wellbeing; 
  • Provide instant 24/7 available chat;
  • Deliver detached statistics for the patient to self-regulate his mental state; 
  • Give users basic recommendations on how to improve a patient’s mental wellbeing; 

The primary goal of a mental health chatbot is: 

  • to help patients to manage and understand their mental states on their own as much as possible; 
  • connect with mental health professionals upon necessity. 

Mental health chatbots originate from the very beginnings of natural language processing conversational interfaces – ELIZA

Joseph Weizenbaum developed this chatbot in 1964-1966. Originally, ELIZA was proof of the concept “to demonstrate the superficiality of communication between humans and machines.” However, ELIZA quickly proved itself to be more than that. 

As it turned out, ELIZA was good at talking with people. At its core, ELIZA had mere pattern matching and substitution scripts that gave the illusion of machine understanding of the user’s input message. 

One of its scripts, titled DOCTOR, imitated a classic person-centered psychotherapy session blueprint. It wasn’t anything sophisticated – just a couple of template phrases, but it worked incredibly well. 

Despite its simplistic design, ELIZA was engaging enough to let people speak out about their problems (which is the simplest model of providing psychological relief). This laid the groundwork for future healthcare chatbots.

These days, mental health chatbots are not just a couple of template phrases that imitate language understanding. 

Modern mental health chatbots integrate into the healthcare system and involve certified medical professionals. These chatbots automate specific processes and also streamline the interaction between the patient/user and mental health professionals. 

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How do Mental Health Chatbots work?

Mental health chatbots are designed to maintain a conversation, not to lead it. In a way, using a mental health chatbot resembles practicing tennis against a wall. 

The general functional framework of mental health chatbots is based on Cognitive Behavioral Therapy methodology. CBT is a form of talking therapy designed to manage mental health states by rearranging the way the patient perceives it, i.e., making negative thoughts positive.

The list of chatbot features revolves around: 

  • Kickstarting a topic for conversation, 
  • asking directional questions, 
  • providing follow-ups to expand responses. 

The NLP algorithm, with Sentiment Analysis features, handles the flow of the conversation. It recognizes keywords and terms. Each trigger word has a decision tree. It is designed to gather as much information as possible and provide a viable resolution – either a simple conclusion, a piece of advice or contact professional help. 

The critical design component in mental health chatbots is the so-called empathetic engagement. 

In the context of a conversational interface, empathetic engagement means: 

  • making the impression of a credible and trustworthy conversation partner that can hear you out and offer a detached point of view on things.

Since the user is already aware of the artificial nature of the conversational interface, there is no need to bend over backward to imitate a full-blown human-human conversation. Instead, the chatbot needs to provide the necessary minimum credibility to enable the user’s suspension of disbelief. 

One of the biggest challenges of mental health chatbots is privacy and confidentiality. Since the entirety of user activity is related to personal matters and thus is sensitive information – it is necessary to address this issue.

The most effective solutions for this are:

  • End-to-end encryption of the user-bot interaction;
  • Making the user profile in the application database anonymous.  

Now let’s look at several major mental health chatbot applications and explain their inner workings.

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Major Mental Health Chatbot application overview

1 Moodkit & Moodnotes – paid app

Moodkit and Moodnotes are products of the company Thriveport. Both apps aim at managing the state of mental health. 

Both Moodkit and Moodnotes are traditional paid apps that charge $4.99 for an install, after which you get the full scope of features and customer support.

Moodkit was the first mental health app of the company. Launched in 2011, it is less of a chatbot and more of a mental health CRM. Moodkit was one of the trailblazers of mental health applications in the early 2010s. From a modern point of view, it is more of a proof of concept that was later perfected in Moodnotes.

Moodkit’s framework is specifically designed to engage users as much as possible to have control over their mental state and substantially improve it. In a way, Moodkit motivates the user to improve his mood and mental state with its handy tools.

The application itself consists of four tools:

  • Moodkit Activities – a tool that suggests what things to do to improve the user’s mood (for example, take a walk or talk to somebody);
  • Thought checker to manage negative feelings caused by a specific situation. It is used to identify and subsequently reiterate the thoughts into more positive ones;
  • Mood Tracker – designed to chart the permutations of the mood over the day, week, month, and so on;
  • Moodkit Journal – a kind of a notebook for a user to keep thoughts and comments on his mood and related events. 

Moodnotes is a kind of more sophisticated and elaborate version of Moodkit. The app was released in 2015, its framework is similar to Moodkit, but there is more thorough automation involved. Moodnotes applies Natural Language Processing and Sentiment Analysis to provide more profound and helpful insights into the user’s mental state. 

  • The user needs to describe his mood of the moment, rate it, and add some comments
  • Next, the app runs an NLP Sentiment Analysis algorithm that recognizes the polarity of the mood, and also its pattern, based on the available user activity.
  • After that, the application’s chatbot engages with the user in a conversation to determine the current thought pattern of the user
  • The questions are designed to reflect emotions and iterate them into more positive patterns

As a result, the bot provides some words of encouragement in a manner of “keep on keeping on.” It is very similar to how Grammarly engages with users to methodically fix texts.

2 Woebot – free app

At the time of writing this article, Woebot is one of the most prominent players in the field of mental health chatbots with over 100k downloads in GooglePlay alone. Founded back in 2017, it managed to take over the game by simply making the most efficient version of the product. In 2018, Woebot had managed to raise $8 million in series A funding. 

Woebot is a distillation of the best conversational interface solutions of the decade, streamlined and adapted for healthcare purposes. The other reason for its rising popularity is the fact that it is a free application. 

At its core, Woebot is a chatbot that keeps an eye on the mood of the user. It provides a platform for the user to speak out, contemplate, and reflect through meticulously designed conversation trees. 

Every once in a while the bot asks the user how he feels and how he’s doing. In response, the bot provides some handy advice or drops relevant contacts with mental health professionals if the situation is that dire. 

  • The NLP component provides a necessary level of personalization and spices up the conversation with a bit of humor
  • Sentiment Analysis is used to identify critical patterns in the user’s input and drive the conversation in a more positive direction

The continuous use of application accumulates its efficiency. There is daily check-in that provides the bot with the necessary information for analysis and, that in turn contributes to better healthcare advice in the future.

According to 2017 research by Stanford School of Medicine, throughout a two week test period, mental health chatbot users reported a decrease in anxiety and depression compared to a control group.

3 Wysa – free app with in-app purchases

Wysa is a kind of more ambitious spin on a mental health chatbot concept. Launched in 2015, Wysa is a result of a collaboration between Columbia and Cambridge universities (and also Touchkin, who did the development). 

Wysa markets itself as an “emotionally intelligent” chatbot to manage emotions and thoughts. The bot itself is built on a Facebook Messenger framework, compatible with IOs and Android so that it is available to as many people as possible.

One of Wysa’s key competitive advantages over other mental health chatbots is its scope. 

  • In addition to the standard Cognitive Behavioral Therapy method, which handles more casuals moods, Wysa applies Dialectical Behavior Therapy (something Woebot is currently working on)
  • It is a big deal because DBT aims at unhealthy, suicidal, and self-destructive behavior, and finds ways of getting out of such situations

The other Wysa innovation is the addition of meditation and yoga advice. While it is not everyone’s cup of tea, it might be a solution for some.

The rest of the framework is similar to Woebot. The user interacts with the bot, provides some information, and, based on that, the bot gives a custom response. There are daily check-ins and detailed stats. 

The other features that differentiate Wysa from the rest are in-app purchases. There is a subscription fee ($29.99 monthly) that enables a more personalized approach with a human operator.  

4 Sanvello – freemium app

Sanvello is a more glamorous variation of mental health chatbots. Developed by PacificaLabs in 2014, Sanvello (known initially as Pacifica) is more inclined to so-called “mindfulness” than straightforward “psychological relief” that is the core of CBT-based chatbots.

As such, Sanvellois a much broader tool that adds to mood tracking and management meditation and relaxation features.

Unlike the other bots on the list, Sanvello adds audio and video recognition tools to traditional text input. The use of image and voice machine learning algorithms helps to determine the state of the user and provide some relevant and helpful advice.  

The app’s features include: 

  • General mood tracking for everyday use
  • Human help feature for emergency cases
  • Coping tools to handle stressful situations
  • Progress assessment feature to see things from a long-term perspective

The other significant feature of Sanvello is the social element. Unlike other mental health apps, Sanvello connects users to share experiences and provide mutual support. While the quality of expertise of such help might be questionable, the concept itself is worth exploring. 

Sanvello’s business model is more in line with traditional mobile applications. There is a free version with a basic set of features, and a premium version with more tools and in-depth customization of service for a monthly ($8.99), yearly ($53.99), or lifetime ($199.99) fee.

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Mental Health Chatbot Development: Final Thoughts

Mental health is one of the healthcare fields that require cutting edge technologies to provide an effective and equally available service for anybody who needs it. 

The conversational interface seems to be a viable solution capable of handling basic needs for anxiety and depression management. Even if the ultimate benefit is encouraging people to speak out about their worries and relieve stress – that’s already a giant step forward.

In this article, we have looked at four different approaches to mental health chatbots.

Such chatbots can significantly contribute to the refinement of natural language processing and sentiment analysis algorithms. Interaction with humans and different case studies may drastically expand the scope of language models and their capabilities. 

What is even more important, in the long term perspective, this will help in further psychological research. 

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Personalized travel recommendation chatbot: the Case Study

 Our journey

Our client is a Polish traveling marketplace, where travelers can get in touch with different travel agents from partnering agencies to select the best trip. The primary sales channel of the client was their website. But, with the recent trend of communicating with businesses via social networks, the company decided to use Facebook Messenger chatbot as an additional sales channel. Apart from providing a more personalized booking experience for travelers, Facebook Messenger chatbot also become an additional channel for monetization since the company offers the chatbot integration to partners who want to stand out from others on the list. 

The client hired us since they were inspired by AI Versus, a chatbot project we participated in. 

Project key facts


Project goals 

Team composition

The project timeframe 



Develop a Facebook Messenger chatbot for personalized trip search. 

  • 2 back-end developers 
  • 1 front- end developer 
  • 1 designer
  • 2 QA
  • 2 dev ops 

2,5 month 

Strict control from Facebook developers who tested and reviewed the bot for 3 weeks.

Setting Goals

To achieve the client’ business goals, we outlined the main requirements for the chatbot MVP:

  • Integrate the chatbot with the client’s databases of partner agencies
  • Create a chatbot flow to help travelers to search for trips
  • Integrate search filters that will include the following parameters:

– Dates 

– Number of adults 

– Number of Infants

– Meal 

– Hotel stars

  • Allow the chatbot to switch to a human agent

How we did it 

Step 1. Development of an authorization page for agencies

  • We created the authorization page design and integrated the default Facebook authorization functionality for partnering agencies.
  • We built a chatbot admin panel using Sonata and a guide for the client on how to use the admin panel. 

Step 2. Development of chatbot flow

  • The main goal was to empower the chatbot with scripted answers for all possible questions since the MVP scope did not include open questions.
  • Each change in the chatbot was carefully reviewed and tested by the Facebook development team since the social network’s main concerns were user security and privacy. 

Step 3. Integration with Data Service

  • We integrated the chatbot with the client’s API Data Server to show relevant trip search results presented in the clients’ databases. 
  • The Facebook team requested the client company registration documents and a chatbot MVP demo. 
  • Then, the Facebook team gave us a list of changes to implement before the chatbot launch.  

Step 4.  Cloud server integration

  • Our DevOps specialist created scripts for the project structure deployment to the client’s servers. 
  • The clients could not estimate the workload to the server, which impacts the workload testing criteria and the client infrastructure for the project deployment, therefore, the server cost. Thus, we decided to use Amazon Web Service as a cloud hosting solution. 
  • Finally, our DevOps deployed the app to the AWS client’s account.

Technical details 

  • Facebook Messenger as a chatbot development platform 
  • Amazon Web Service as a cloud hosting solution 
  • MY SQL for chatbot localization  
  • Sonata for chatbot admin panel 
  • IBM Node-red powered by Node.JS as an orchestrator for microservices and bot flow logic 
  • Databases from the customer’s side

The future 

Currently, the travel chatbot MVP is in the final stage of testing and soon we will launch it on the client’s Facebook Page. With time, the client expects to integrate the following business logic:

  • More detailed search filters
  • In-chat payment
  • Scheduling the call with a travel agent.