Your company should never have to remember twice.
MindKeepr turns scattered facts, decisions, procedures and outcomes into governed organizational memory, then applies that memory to live work, safely.
AI can read your files. It still doesn’t know how your company works.
The fact lives in the CRM. The decision lives in a thread. The reason lives in someone’s head. The knowledge your company runs on is the relationship between them, and no single system holds it.
Memory remembers. Workflows execute. Insights proves it.
Your CRM, Jira, GitHub and ERP stay the systems of record. MindKeepr stores and governs the reasoning, procedures, decisions and outcomes around them.
Remembers how your organization works.
Capture what your organization knows, why it decided, how it operates and what happened next. Every memory object is permission-aware, source-traceable, versioned and time-aware, available through API and MCP.
Served today through Digital Twins, Enterprise Search, Knowledge Builder and Trained Experts.
Explore Memory →Applies that memory to live work.
One gateway for business requests. Work moves through states with risk classification, authority checks and human approvals, and nothing is complete until the outcome is verified.
An execution product built on Memory. Humans and governed AI agents, dispatched with least privilege.
Explore Workflows →“ACME needs automated reporting before its renewal.”
A request arrives at the gateway.
MindKeepr retrieves the account context, the active procedure and the closest precedent.
The request is classified. Risk is set. Missing information is flagged.
A governed agent prepares the assessment with least-privilege context.
The right approver signs off. Authority is checked, not assumed.
Work is completed in Jira, GitHub and the CRM, where it belongs.
The done-gate verifies the outcome against the original request.
The decision and the result become organizational memory.
Prove the work is getting better.
Measure workflow velocity, waiting time, quality, verified outcomes and AI cost, from the original request to the final business result. Tokens are a cost input. The unit that matters is cost per verified outcome.
Explore InsightsStart from a proven playbook.
Capture a leaver's knowledge before the last day.
From ticket to verified release, approvals intact.
Assess, price and approve changes with precedent.
Respond with the runbook, the authority and the evidence trail.
What was promised becomes what gets built.
A repeatable first 90 days, verified at each gate.
Prove the work happened before the invoice leaves.
Every pack ships with its intake, roles, state machine, risk rules, approvals, verification criteria, escalations and a learning loop.
See all packs →Someone critical is leaving. Start there.
Offboarding, role transitions, project handovers, restructuring. Capture the knowledge once, deprovision the idle seats, and the memory compounds from there.
↓
Role and department memory
↓
Decision and workflow memory
↓
Context for every employee and AI agent
↓
Governed workflow execution
Ask a departed expert anything.
Each digital twin is trained on a person or role. Chat with it for instant, sourced answers, scoped to exactly what you are allowed to see. This is Memory, working today.
Most vendors answer sovereignty with a region dropdown. We answer it with architecture.
Deploy on-prem or air-gapped. A self-hosted model is included, so nothing has to leave the building.
Permissions come from your systems. Retrieval is topic-first, with no scoring of individuals. Ready for works-council review.
The knowledge layer is. Swap in commercial cloud, enterprise-hosted, regional, open-weight or on-premise models, and keep everything you have built.
Why not just build on a model API?
A model API gives you intelligence. The memory layer is still your problem: where the knowledge lives, who is allowed to see it, and what an agent is allowed to do with it. MindKeepr is that layer, and it runs where you decide.
| Capability | Model APIs | MindKeepr |
|---|---|---|
| Built from your live tools | No | Yes |
| Permissions inherited | No | Yes |
| Runs in your environment | Limited | Yes |
| Model included on-prem | No | Yes |
| Governed agent execution | No | Yes |
| Preserves departing experts | No | Yes |
Your knowledge stays yours. Your policies stay in control.
Privacy is the first question enterprise teams ask. Here is the honest answer, by design, not by policy.
Answers respect your existing access controls. MindKeepr never surfaces anything a person could not already open.
Each response links back to its source. Auditable by design, never a black box.
Knowledge is processed securely and stays yours. No retraining on your content.
Commercial cloud, enterprise-hosted, regional, open-weight or on-premise. Different models for different risk levels.
Risk policies route sensitive steps to the right approver. An agent cannot approve its own work.
A done-gate checks the result against the original request before anything is marked complete.
No agent can edit organizational policy. Changes go through people with the authority to make them.
“Summarise the Q3 board deck.”
Questions, answered.
What is MindKeepr?+
MindKeepr is the memory and workflow layer for governed AI. It captures your organization's facts, decisions, procedures and outcomes as permission-aware memory, applies that memory to live work through governed workflows, and proves the results with outcome-level measurement.
What is MindKeepr Memory?+
MindKeepr Memory remembers how your organization works. It captures facts, decisions and reasoning, procedures, roles, approved exceptions, previous cases and outcomes. Every memory object is permission-aware, source-traceable, versioned and time-aware, available to employees and approved AI systems through chat, search, API and MCP.
What is MindKeepr Workflows?+
MindKeepr Workflows applies organizational memory to live work. It is one gateway for business requests, with state machines, risk classification, authority checks, human approval checkpoints, governed AI task dispatch and outcome verification before anything is marked complete.
What is a governed AI agent?+
A governed AI agent uses an organization-approved model and operates only with permitted data, tools, identities and approval policies. High-risk steps still require human approval, and no agent can change organizational policy.
Does MindKeepr replace Jira, our CRM or SharePoint?+
No. Your existing tools remain the systems of record: the CRM for customer state, Jira for delivery, GitHub for code, ERP for finance. MindKeepr stores and governs the reasoning, procedures, decisions and outcomes around those records.
Which AI models does MindKeepr work with?+
MindKeepr is model-neutral. Use commercial cloud models, enterprise-hosted models, regional models, open-weight models or on-premise models, and different models for different risk levels. MindKeepr supplies the context and governance regardless of the model you select.
Is our data secure and private?+
Yes. Answers are permission-scoped, so people only see what they could already access. Your data is never used to train external models, and you can deploy in the cloud, on-premise, or air-gapped, with EU and GCC data residency.
How quickly do we see value?+
MindKeepr starts answering as soon as your sources are connected, and the strongest first project is a departure that is already on the calendar: capture the expert's knowledge before the last day.
Give every person and AI agent the context to act correctly.
Start with one critical role, knowledge domain or governed workflow.