Fabrice Grinda has spent decades building, investing, and writing. Hundreds of blog posts, years of investment thinking, and a philosophy about markets and opportunity that very few people have had the chance to sit down and really absorb. The knowledge was all there, but it was scattered, and accessing it meant hours of reading with no guarantee you would find exactly what you were looking for.
That is where FabriceAI begins. We built a real-time conversational platform where anyone can have a natural voice or text conversation with an AI that thinks, responds, and reasons the way Fabrice does. Ask it about market sizing, a specific industry, or the reasoning behind a past investment, and you get an answer grounded in his actual words, his actual thinking, with the sources right there to follow if you want to go deeper.
The Challenge
Turning a body of work this personal and this vast into a reliable, intelligent AI required us to solve a few problems that do not have off-the-shelf answers.
Staying True to the Source
A general-purpose AI would hallucinate or generalise. Every answer needed to come from Fabrice’s actual writing, not a model’s best guess at what an investor might say. Accuracy was non-negotiable.
Feeling Like a Real Conversation
Nobody wants to interact with an AI that sounds like a search engine. The experience needed to feel warm, fluid, and low-latency, whether the user was typing or speaking.
Reasoning Over Documents
Users often arrive with pitch decks, PDFs, and research notes they want to discuss. The AI needed to actually read and reason over those documents in the conversation, not just acknowledge them.
Picking Up Where You Left Off
A knowledge tool that forgets everything the moment you close the tab is not really useful. Users needed their conversations to persist and continue naturally across sessions.
The Solution
Our development team designed and deployed FabriceAI, a robust AI-powered web application tailored to present Fabrice’s viewpoints through a seamless, engaging user interface.
Curated Vector Database
We started by building a curated vector database from Fabrice’s entire blog archive. This is the memory at the heart of FabriceAI.
Grounded Retrieval
Every time a user asks something, the system searches this database and grounds its response in real source material, surfacing the relevant blog posts alongside every answer so the user can always trace where an idea came from.
Voice and Document Intelligence
For voice, we integrated OpenAI’s Realtime API with semantic voice activity detection, which means the AI knows when you have finished speaking and responds naturally, without awkward pauses or interruptions.
For documents, we built an OCR and vision pipeline that lets the AI extract and reason over PDFs and pitch decks in real time, mid-conversation.
Conversation Memory
And because continuity matters, we store every conversation in MongoDB so users can return days later and continue exactly where they left off, in whichever language they prefer.
Impact
FabriceAI makes one of the most thoughtful investor minds in the world available to anyone, at any time, in any language. A founder preparing for a pitch, an investor doing research, or a curious reader exploring an idea can now have a genuine conversation with decades of thinking behind it. That is something no blog archive, however well-written, could ever offer on its own.
Key Features
Real-Time Voice and Text Chat
Natural, low-latency conversations powered by OpenAI’s Realtime API, with semantic voice activity detection that makes voice interactions feel genuinely human.
Retrieval-Augmented Generation
Every response is anchored in Fabrice’s actual blog archive through a curated vector database, so answers are accurate, traceable, and grounded in real thinking.
Source Citations
The relevant blog posts surface alongside every AI response, giving users the transparency to follow up, verify, and explore further whenever they want.
Document Intelligence
Users can upload PDFs, pitch decks, and research documents. The system uses OCR and vision models to read and reason over them during the conversation, in real time.
Persistent Session Memory
Conversation history lives in MongoDB across sessions, so every returning user picks up naturally from where they left off, with no need to repeat context.
Multilingual Support
The platform detects the user’s language automatically and responds in kind, making Fabrice’s thinking accessible to a global audience without any configuration.
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