Eighty percent of what your organisation knows has never been in a system. We put it there.
Your experts' judgment, your institutional memory, the knowledge that actually drives decisions. None of it fits in a database. We capture it, structure it for AI, and build expert systems that get smarter every time they're used.
The knowledge that matters isn't in your systems
Your best people know things that aren't written down anywhere. The buyer who reads the market by instinct. The DBA who knows exactly which configuration fixes the problem. The engineer who remembers why that system was designed that way ten years ago. And the knowledge that is documented? It's buried in support tickets, spread across presentations, locked in forums and emails. Fragmented, unsearchable, disconnected.
AI can now change this, but only if you solve two problems that traditional approaches never have.
How do you capture the knowledge that's never been written down?
How do you stop a knowledge base from going stale the moment you finish building it?
Capture what's never been written down
Our agentic interview platform is an autonomous AI agent that interviews your experts through natural spoken conversation. It asks its questions aloud, listens, follows narrative threads, asks genuinely incisive follow-ups, and adapts in real time. Not just what your experts know, but how they think, what signals they watch for, and what experience has taught them.
Experts just talk, at their own pace, no typing and no forms. The output isn't a transcript. It's structured, contextualised knowledge, ready for AI ingestion.
We also ingest knowledge from across your entire organisation: support tickets, presentations, forums, documentation, internal communications. Everything your organisation knows, from every source, unified and retrievable.
Build a knowledge base that learns
Most RAG systems are static. Documents go in, get processed, and freeze. Nothing improves the knowledge base based on how it performs. Nothing flags when content goes stale. The knowledge starts degrading the moment you finish building it.
We build living knowledge bases. When an expert corrects an answer, the correction feeds back into the knowledge itself. When the system encounters a question it can't answer, it identifies the gap and reaches out to the right expert to fill it. Every interaction makes the system more accurate, more complete, and more valuable.
We wrote about why this mattersThat was cool as crap.
Almost scary how natural that was.
That was genuinely enjoyable.
This isn't a form to fill in. It's a conversation that people want to have. And that matters, because engaged experts share deeper, more valuable knowledge.
From knowledge to expert system
Capture expertise. Refine it for AI. Retrieve it intelligently. And keep improving it through use.
Capture
Expert interviews and org-wide ingestion
Refine
AI cleans, structures, and preserves traceability
Retrieve
Hybrid search finds the most relevant knowledge
Improve
Feedback loops make the knowledge base smarter
Interviews + ingestion
The interview platform draws out undocumented expertise through natural conversation. The ingestion pipeline pulls in everything else: documentation, support tickets, presentations, forums. All of it flows into the same knowledge base.
Cleaned, structured, traceable
All ingested knowledge goes through our AI pipeline. The content is cleaned, structured, and converted into semantically coherent chunks that preserve meaning, context, and traceability back to the original source. Nothing is embellished or invented. Every piece of knowledge traces to the expert or document it came from.
Hybrid retrieval + fusion
Our hybrid retrieval combines vector search for semantic understanding, lexical search for precise terminology, and structured queries for factual data. A fusion layer combines the results to find the most relevant knowledge for any question. Your expert system handles nuance, understands context, and reasons about what you're actually asking. We wrote about why this architecture matters more than prompt engineering.
A living knowledge base
This is what makes a living knowledge base different. Expert corrections feed back into the content itself. Performance monitoring identifies chunks that are frequently retrieved but rarely helpful. Gaps are detected and filled through targeted expert interviews. The knowledge base doesn't just serve answers. It learns from every interaction and gets better over time. We wrote about why the corpus, not the retriever, is what rots.
Combined with live operational data
Knowledge AI works alongside our data platform. Expert knowledge grounded in real-time data: knowing not just what the manuals say, but what your systems are doing right now.
A DBA expert system
that knows the manuals and can see your database performance.
A buying expert system
that knows the market and can see live futures prices.
Knowledge too valuable to leave in a few heads
Scaling specialist technical knowledge
DBA expertise, engineering know-how, compliance procedures. The knowledge that takes years to build and minutes to lose.
Augmenting complex decisions
Commodity trading, procurement, risk assessment. Combine expert judgment with live market data for better, faster decisions.
Preserving institutional knowledge
Succession planning, onboarding acceleration, cross-team knowledge sharing. Your experts' knowledge, available to everyone who needs it.
Enabling 24/7 expert access
Expert-level answers across time zones and shifts, without waiting for the one person who knows.
From expertise to AI-first knowledge
"How do we document what our experts know?"
"How do we make what our experts know available to AI, permanently, and in a form that gets better over time?"
That's the difference between managing knowledge and becoming AI-first. Your expertise stops being something that depends on who's in the room, and starts being infrastructure.
Let's talk about the expertise you need to scale
Every business has knowledge that's too valuable to leave locked in a few people's heads. Tell us about yours.