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Built a production-ready AI voice and text agent using ElevenLabs Conversational AI to qualify website leads, answer FAQs with RAG, extract structured data, and automate CRM workflows.
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AI Assistant Using Your Business Knowledge Base — RAG on Your Documents
THE PROBLEM
Q&A bots break down when knowledge lives in documents: a 100-page manual has no "questions" to match, it can't fit into a prompt, and generic chatbots hallucinate instead of admitting what they don't know.
THE SOLUTION
A RAG (Retrieval-Augmented Generation) knowledge base: documents are split into meaningful chunks, embedded into a vector index, and the assistant answers from the right sections — by meaning, not keywords.
Any format as-is: PDF, DOCX, TXT, Markdown — 100+ pages is fine
Answers grounded in YOUR documents — it says "I don't have that information" rather than inventing
Source references — every answer shows which document and section it came from
Runs on your infrastructure — documents never leave your control
One command to re-index after updating documents — documented, no programmer needed
LIVE DEMO
Ask it about my products, pricing, deployment and support — it answers from 6 real documents with sources:
https://kb-assistant-demo.dvc-ai.workers.dev
The 'I don't have that information' line is the part most RAG builds skip, and it's the one that matters. How do you set the cutoff? On mine, a fixed similarity threshold broke once I filtered results by user role. Scores shifted and it refused questions it could answer.
A closer look inside my Clause Check template.
Clause Check is a SaaS AI concept I designed to make reviewing and understanding contracts a little easier.
Here’s a look at more of the landing page, from the UI components and interactions to the small details that bring the design together.
Designing a clear interface for complex voice AI infrastructure.
This project focused on turning a technically dense AI platform into a visual system that feels simple, confident, and approachable. I explored the relationship between editorial layouts and functional product UI, creating a consistent language across model discovery, AI conversations, pricing, security, and developer focused content.
The visual direction uses soft gradients, restrained color, generous whitespace, rounded containers, and strong typographic hierarchy to create depth without adding unnecessary complexity.
A key focus was information hierarchy: giving each technical capability enough visual space to communicate its value while keeping the overall experience cohesive and easy to navigate.
The final direction brings together brand, marketing website, and product interface design into one consistent SaaS experience.
The mix of soft visuals and functional UI works so well together.