A structured way to get an expert's knowledge out of their head and into documentation a colleague or successor can actually use. Tailored to your organisation and tech stack.
Knowledge that keeps companies running lives in people's heads, not in documents. Nobody has time to write it down. There's always something more urgent. When key employees leave, their knowledge leaves with them. When a teammate needs to cover a vacation or sickness absence, they lose time trying to figure things out.
But "document everything you know" is a paralysing brief. You don't know where to start. You can't tell how much detail is enough. What's obvious to you won't be obvious to someone else. The standard handover is a couple of calls and a half-finished document.
A chat with an AI agent generates a table of contents, identifying the chapters that cover your role.
The agent then interviews you, one chapter at a time, question by follow-up question. Your answers, however rough, transform into a well-structured document.
You review and approve each draft as it's written. If you like, the agent can scan your files and attach related links.
It never invents. When something is missing, it flags the gap rather than filling it with a plausible guess.
The handover agent works inside whatever AI and IT tools your business runs on. Your data stays in the systems you already use. Nothing new to install, no separate tool to buy. The four examples below show the agent in action in different systems. If your stack is different, the same method can be built for it.
The original agent came out of a long Claude thread. It tracks detail across every chapter and creates the files itself, as Markdown or Google Docs, without extra plumbing.
Under the hood: cross-chapter memory and native file creation. Connect to Google Drive, Calendar and Mail to surface relevant files and details.
Built as a Gemini Gem or Gemini-powered web app, working directly with Google Docs. If your company runs on Google Workspace, the handover lives where your team already works.
Under the hood: upload files directly from Drive, writes straight to Docs.
Built with Copilot Studio and Power Automate, running on either Anthropic Sonnet 4.6 or OpenAI GPT-5.5. It searches the user's own SharePoint and OneDrive to find related files and attach them to the right chapter. The whole handover stays inside your Microsoft tenant.
Under the hood: flexible model choice, file search, resumable state across sessions, Microsoft-native connectors only. No third-party services and no extra licences like AI Builder. Data never leaves your tenant.
Built on Mistral, for companies that need their data on a European LLM. Just as capable as the other implementations. Connects with a wide range of services, from Google Mail and Outlook to Atlassian and Slack. It presents each approved chapter in-window for you to edit directly.
Under the hood: runs on an EU-sovereign model. Wide range of connectors. Canvas editing.
Videos only go so far. Run a short handover yourself in the live demo. Want it fitted to your own company and stack? Get in touch.
Opens in Claude. You'll need a Claude account.
Written from scratch, that's 40 to 60 hours of work. More likely, it wouldn't have happened at all.
“The best and most detailed handover they'd ever received from a client.”
— HR agency that took over the function
Beyond securing knowledge when someone leaves, the handover documents unlock a bunch of other use cases.
Structured data about how this role or department actually works builds a knowledge operating layer. A reliable foundation for building automation, improving processes, onboarding talent, and much more.
If someone who holds a lot in their head is leaving and you want to see whether this fits your company, let's talk.