MindKeepr vs Guru

Where Guru is the better answer

If your problem is a large body of existing knowledge that drifts out of date, Guru is built for exactly that and has been for years. The maintenance machinery is the product, not a feature of it.

If you want a partner rather than a tool, Guru sells one. The pricing page puts an AI and knowledge management strategy team alongside the platform: architecture design, agent tuning, a change management playbook and ongoing reviews. That is a real answer to a real problem, and it is not what we sell.

We would rather tell you this on our own comparison page than have you find out two calls in.

Where we are different

The difference is what each system does with a question it cannot answer well.

A maintenance-led system improves the knowledge it has. It does not, by design, tell you about the knowledge it never had, because nothing in a curated base points at a decision that was never written down. That is the category of loss we are built for: the reasoning behind an exception, the threshold that decides a call, the workaround that quietly prevents an outage.

So MindKeepr starts from the record of work rather than from the knowledge base. It looks for the decisions and context only one person has ever touched, which is a question about your organisation rather than about your documentation, and it treats every one of those as a dependency to be closed before the person goes.

And when somebody asks a question nothing verified can answer, it stops. It names what is missing and asks a person, rather than producing a fluent paragraph that reads exactly like the real thing.

How to tell which one you need

Ask what would actually hurt. If the pain is people finding an out-of-date page and acting on it, you have a maintenance problem and Guru is a strong answer.

If the pain is a name, someone whose departure would leave a hole nobody can describe precisely, you have a continuity problem. Maintenance does not fix it, because the knowledge at risk was never in the system to maintain.

Plenty of organisations have both problems. They are not mutually exclusive products, and both deliver into other AI tools over MCP rather than demanding that everything move.

Is MindKeepr a Guru alternative?

For the knowledge retention use case, yes. For continuously maintaining a large curated knowledge base with an embedded strategy team, Guru is built for that and we are not. The two overlap on permission-aware cited answers and on delivering knowledge to other AI tools.

What does MindKeepr do that Guru does not describe?

Two things. It works from the departure and transition trigger, finding decisions and context that only one person has ever touched rather than maintaining what is already documented. And it refuses to answer when nothing verified supports an answer, naming what is missing and routing the question to a named person with a deadline.

Where does Guru have the edge?

Maturity, the maintenance machinery at the centre of the product, and the solution engineering team its pricing page sells alongside the software. If you want architecture design, agent tuning and ongoing optimisation reviews as part of the contract, that is a genuine advantage and we do not offer an equivalent.

Can MindKeepr run on-premise?

Yes. MindKeepr supports cloud, on-premise and air-gapped deployment with regional data residency options, which suits regulated and sovereignty-sensitive environments. Guru does not publish deployment options of this kind on the pages we checked.

How much does MindKeepr cost?

We do not publish list pricing and neither does Guru. Both are scoped to the size and shape of the deployment, which in our case depends mostly on how many people and systems are in scope for continuity rather than on a seat count.

• Guru, pricing page. www.getguru.com/pricing Checked 27 September 2026.
• MindKeepr, security overview. www.mindkeepr.com/security Checked 27 September 2026.
• MindKeepr, knowledge coverage. www.mindkeepr.com/knowledge-coverage Checked 27 September 2026.

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