We uncover what you know, organize what matters,
and build practical ways to put it to work.
The answer exists somewhere. Finding it, trusting it, and using it are the hard parts.
A source-linked knowledge base can give you and your team a reliable place to begin.
Try a small example
Illustrative example.
Prepared content, not a live AI response.
“We usually start with a kickoff call. Except when the customer handles sensitive data. Then we check access first. I normally ask someone about that.”
“How should we onboard this customer?”
Add a source. See which part of the answer changes.
No sources selected
Context engineeringRelevant instructions and source material help an AI assistant respond to a specific task. More material is not always better: conflicting instructions need review.
About this demoThese answers are written in advance to show the effect of different sources. Nothing is sent to an AI service.
The method
We start with the work, then shape the system around it.
Understand
A conversation about what you do, where it gets difficult, and what would make a difference.
CaptureWith permission, recording and transcription tools create a record of the conversation.
Transcript preparationWe correct errors against the recording, mark uncertainty, and preserve the original. Your language and meaning stay intact.
Uncover
Explore real decisions, exceptions, workarounds, and the things experience has taught you.
Knowledge elicitationQuestions about real situations surface judgment that a process document may miss.
AI-assisted synthesisAI suggests patterns and follow-up questions from the sources. You confirm the meaning; additional research helps investigate gaps.
Organize
Connect what matters to its source, the task it supports, and the person who keeps it current.
Context engineeringSelect and structure the background, instructions, and examples AI needs for a particular task.
ProvenanceKeep sources, dates, and review status attached. Separate confirmed facts from interpretations and open questions.
Apply
Create the useful thing: a content series, a working reference, a second brain, or a connected workflow.
RetrievalBring relevant source material into the task when needed. This can use simple search or retrieval-augmented generation (RAG).
Tools and integrationsWhere useful, APIs or MCP connections let AI work with approved systems. Permissions and human review define what it can do.
Test
Try real tasks, correct the gaps, and leave a clear way to use and maintain the result.
EvaluationsUse real tasks, expected results, and difficult cases to check usefulness and source accuracy.
Durable contextKeep knowledge and decisions outside a single chat. Named owners and review points help prevent saved context from becoming stale.
One useful output.
Or a connected system.
We can focus on one part of the process or work through it together. The depth depends on what you already have and what you need next.
Tools are chosen around your work. A recording tool, an AI assistant, a shared workspace, or integrations only where they help.
The method in practice
Selected work · Research system
A scattered archive became a source-linked research system, with curated quotes, a claims register, and reusable outputs.
Useful interviews buried in folders. Difficult to retrieve, compare, and reuse.
Inventory the sources, structure the evidence, and distinguish claims from interpretation.
A reusable research foundation, with public briefs and guides people can explore.
What you keep
Questions
No. Scattered notes, recordings, and documents are the usual starting point. Sorting them is part of the work.
No. AI helps with some steps, such as transcripts and finding patterns. You decide where it is used, and people review what it produces.
Access to the material you want to use, and time to talk through the work. We ask the questions. You confirm what is right.
It depends on the scope. One useful output takes less time than a connected system. We agree on the scope after the first conversation.
Bring a process, a pile of notes, or something
you keep having to explain.
15 minutes. We’ll talk through the work, where it gets stuck,
and whether there’s a useful first step.