How do you keep product knowledge when a long-serving expert leaves?

Capture what they know while they are still answering questions: on each feature, ask them what only they can answer, and keep each answer with where it applies and who confirmed it. Rivora Connect does this as part of designing every feature, so your product's memory grows long before anyone hands in their notice.

What actually leaves when an expert leaves?

What leaves is the part nobody wrote down:

• why the product works the way it does, and what was tried before;
• which rule applies to which client, and why that client is different;
• which code is still used, and which is only still there;
• the edge cases that only come up once a year.

Nobody had time to write these down, because the expert was always the quickest way to get the answer.

Why don't handover documents work?

A handover document is written once, in a hurry, by someone who is leaving. It covers what they remember to write, and it can't answer the question nobody has asked yet. Months later, the real questions turn up one at a time, and the person who could answer them has gone.

What works instead?

Capture knowledge at the moment it's used. When a feature needs an answer, ask the person who knows, and keep the answer where the next person will look for it.

Rivora does this as part of the work:

1. Rivora asks while the feature is designed. It reads what already exists, including your code and documents, and raises the questions it can't answer.
2. The expert answers once. The answer is kept as a decision, rule or clarification. Each decision records where it applies, where it came from and who confirmed it.
3. Every feature adds to it. The product's memory grows with every feature, and the next person, and the next AI tool, starts from what your team has confirmed.

The best time to start is the next feature that needs your most-asked expert.

What if they have already left?

Start from what is left behind. Rivora reads your code through a GitHub App with read-only access, and your documents through Confluence or upload. It drafts from those, and raises the questions they can't answer for the people who remain. What they confirm becomes memory; what nobody can confirm stays an open question, in plain sight.

Questions

Isn't this just better documentation?

Documents hold what someone wrote once. Rivora keeps what your team confirms, feature after feature, with the reasons and the scope attached.

Do experts have to spend hours writing things down?

Rivora lists the questions it can't answer on the feature, next to the sources it used, while a real feature needs the answer. It is designed to fit into work they are already doing.

Who can see what is kept?

Your team, in your workspace. We don't use your content to train general-purpose AI models, and we will not knowingly permit our AI providers to use it for that. What Rivora learns stays in your workspace, as your product's memory.