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AI Chatbot Development for Productivity Assistant

Domain: AI

Technologies we used: RASA, S-BERT, BLOOM, PEFT, Accelerate, Causal Language Modeling, Sanic and NGINX.

Engagement model: Project-based
Services provided: Custom software development

Project Overview

Empowering end-users to reach peak productivity, a growing ERP firm sought our expertise to develop a friendly AI chatbot assistant. This intuitive companion delivers instant help, optimizes workflows with data-driven tips and statistics, and unlocks untapped potential within the app, leading to a happier and more productive digital workforce.

Integrating a chatbot into our client's platform offers:

  • Quick app navigation for immediate query resolution, eliminating the need for extensive menu searching.
  • Time-saving quick actions like creating tasks and setting automation rules.
  • Data simplification into tailored one-page reports, enabling easy comprehension of essential insights without information overload.
  • Efficient issue resolution through feedback analysis and guided solutions, minimizing downtime and enhancing user experience.
  • Customized recommendations based on user behavior, preferences, and interactions within the app, boosting productivity and app utility.
  • Improved user engagement and retention, fostering an enjoyable and seamless app experience.


The Challenges We Met

Our journey commenced with a meticulous analysis of our client's requirements and the existing ERP system's architecture. This meant dissecting the business logic in their product, identifying user personas and scenarios, and preparing data specific to the platform. Without this nuanced understanding, the chatbot wouldn't grasp user needs and deliver relevant assistance.

Next, to bridge the gap between human language and business logic, our development team constructed two essential components that empower the Assistant to grasp and execute tasks: an entity extractor and a chat markup language translator.

  • Entity Extractor: Functioned like an attentive listener, adept at identifying and extracting key information such as names, dates, and specific actions from user interactions.
  • Chat Markup Language Translator: Acting as the chatbot's interpreter, skillfully translated intricate business processes into a language comprehensible to the Assistant.

This powerful tandem equips the Assistant to not only grasp user intent but also follow through and execute tasks flawlessly, ensuring a smooth and efficient journey for every user.

We harnessed the capabilities of RASA, Duckling, and state-of-the-art Large Language Models (LLMs) to progressively enhance the chatbot's functionalities. Our commitment to Agile methodologies facilitated continuous refinement through regular feedback loops. This approach ensured the development of a chatbot that not only resonates with our client’s needs but also stays attuned to evolving market trends.


Delivery Approach

  1. Understand the scope of work and discuss upcoming features via calls and emails.
  2. Define system architecture and implement the first demo to get approval from the client.
  3. Define project phases and release roadmap.
  4. Delivery features by features in an interaction manner that includes development, testing, deployment, and feedback.


The Results

This project was completed on schedule and within the allocated budget. The chatbot was integrated into the ERP system with a focus on user-friendliness and maintaining system integrity. Post-implementation data showed a significant increase in operational efficiency and user satisfaction. The AI-powered chatbot continues to evolve, learning from each interaction to enhance its performance over time.

Let’s take a look at some screenshots of the chatbot assistant!

Custom AI chatbot for Customer support services


AI chatbot development for Productivity Assistant

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