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ChatterWise: Build AI Chatbots with Your Knowledge

ChatterWise is an AI-powered tool that empowers organisations to build, train, and deploy intelligent chatbots without writing a single line of code. By turning internal knowledge into smart, conversational agents, ChatterWise breaks down technical barriers and makes automation accessible to any team, in any industry.

Inspiration

The idea behind ChatterWise emerged from a previous project where we attempted to create a low/no-code chatbot builder using visual flows. Although the interface was robust and feature-rich, users were still required to manually maintain and update conversation trees. We quickly realised that simplicity was lacking—especially for under-resourced teams or those without the necessary technical expertise.

Why Generative AI

Following the evolution of Generative AI, several key benefits stood out to us:

Learns from the data it is exposed to
Adapts over time
Offers 24/7 availability
Delivers a consistent and uniform customer experience
Communicates in multiple languages
Cost-efficient
Offers well-documented paths for integration

These capabilities led us to a pivotal question:
Could a GenAI-powered chatbot solve the limitations we identified in our earlier solution?

Building During the Hackathon

The "World’s Largest Hackathon" provided the ideal opportunity to put our ideas to the test.

We began by defining core requirements based on insights from previous users. The knowledge we gathered around pain points, entry barriers, and value creation proved invaluable. With our baseline in place, we used Bolt.new to prompt and generate the initial data model—laying the foundation of what would become our fully-fledged product. We then iterated extensively, refining each component to meet our standards.

Technology Stack and Challenges

We utilised OpenAI's Retrieval Augmented Generation (RAG) and Semantic Search to train our base models with test knowledge bases. This yielded responses that broadly aligned with contextual expectations—but the journey was far from smooth.

Initial trials exposed issues such as:

Hallucinations
Redundancy or vagueness
Occasional misinformation

These challenges pushed us to deepen our understanding of prompt engineering and model fine-tuning. We also had to address data variability, designing solutions to extract value from unstructured or inconsistent sources while still generating reliable outputs.

Late nights, bug fixes, and tough deployment moments tested our resolve—but ultimately, they strengthened our product.

What’s Next

We are confident that ChatterWise can transform the way organisations—especially those who previously ruled out chatbots or automated agents—approach technology-driven initiatives.

Our next steps include:

Building a business model around the solution
Structuring an ambitious, fast-paced go-to-market strategy
Testing with real organisations and refining our value proposition with early adopters
Adding multilingual support to promote inclusivity and accessibility across diverse customer bases
Enhancing our data gathering and analytics capabilities

Final Thoughts

ChatterWise is a reflection of our belief that powerful technology should be accessible, adaptable, and human-centred. As founders, we deeply believe in the potential of this product—not just as a tool, but as a catalyst for real, sustainable change. We're excited for what lies ahead and are fully committed to turning our vision into a lasting, impactful solution.