deYour AI only knows what is written down.We give it experience.
AI assistants search documents. How decisions are really made lives in your experts’ heads. Omnora captures that knowledge in AI interviews, validates it and makes it usable for people and AI.
- Hosted in Germany
- MCP, RAG and REST
- No training on your data
650+ companies trust Omnora
In short
- 1AI assistants and agents answer from documents. The rules and exceptions that matter are usually not in them.
- 2Omnora draws this experience out of your experts’ heads in AI interviews of about 30 minutes each.
- 3Every knowledge object is checked for contradictions and gets an owner, a validity date and a source.
- 4Your AI accesses it via MCP server, RAG or REST API, your teams via AI chat with sources.
“Copilot finds the policy, but not how we actually do it.”
AI does not fail on the model. It fails on the knowledge.
The rules, exceptions and experience that matter most are written down nowhere. That is exactly what your AI needs to answer reliably.
No AI knows what is written nowhere
Criteria, thresholds and special cases live in experienced people’s heads. No crawler will find them.
A file share is not a knowledge base
If your AI’s context is a drive full of old documents, its answers are old documents, just more fluently worded.
Plausible is not reliable
Without a source and an owner, your people double-check every answer. Or go back to asking their colleague.
- 60%
- of AI projects without AI-ready data will be abandoned through 2026
- Gartner, 2025
- 42%
- of job-related knowledge is not documented anywhere
- Panopto/McKinsey
- 30 min
- per AI interview, alongside daily work
- Omnora
Experience becomes context for your AI.
Without Omnora
AI without experience.
- Assistants answer from outdated, contradictory or incomplete documents
- Exceptions and decision logic are missing from the context
- Answers without a source, so without trust
With Omnora
Tacit knowledge as a data source.
- AI interviews capture decision logic and exceptions
- Omnora checks for contradictions, owners approve
- Every answer with a source, for people and agents
From people’s heads into your AI.
Area by area, expert by expert. Your existing assistants stay; they simply get better context.
- 1
Capture what is written nowhere
AI interviews draw out decision logic, exceptions and warning signs. SOPs and project documents feed in as context.
- 2
Validate and approve
Every knowledge object gets an owner, a validity date and a source. Contradictions between teams surface and get resolved.
- 3
Connect: MCP, RAG, REST
Copilots, agents and business applications draw on validated knowledge. Your teams ask in the AI chat.
- 4
Keep it current
Validation questions go to the owners regularly. Outdated content gets flagged instead of served.
The knowledge nobody writes down.
A corporate brain is not another document store. It holds what standard AI fails on: how decisions are made, what the process does not say and who stands behind it.
- Decision logic: criteria, thresholds and trade-offs
- Exceptions: special cases, workarounds and customer specifics
- Governance: contradiction checks, approvals and a source in every answer
One body of knowledge, two audiences.
The same validated knowledge reaches your teams and your AI systems.
Human to human
- AI chat with sourcesQuestions in plain words, answers backed by an interview or document.
- Knowledge documentsStructured playbooks per topic, to read, share and export.
Human to machine
- MCP serverAI assistants and agents query Omnora directly, with source and owner in the answer.
- RAG and REST APIFor your own RAG pipeline and business applications. Omnora provides the validated layer underneath.
Connects toMicrosoft CopilotMCP-capable agentsYour own RAG pipelinesBusiness apps via REST
Context you can trust.
- 3
- interfaces
- MCP server, RAG API and REST API
- 0
- training on your data
- Your knowledge never trains AI models
- DE
- hosted in Germany
- Processing in the EU, no data transfer to the US, TISAX certified
Billed per initiative, not per head.
Start free with one area. The MCP server comes with the Business plan, and extra accounts cost nothing.
See pricingHosted in Germany, GDPR compliant
What pilot customers say
“Beginners use the video, experienced users the chatbot. The same knowledge in several formats.”
“What I loved was that the bot picks up new insights immediately. I described a fault that actually occurred at the start of yesterday’s shift and then added how the electrician fixed it. The bot then took on the solution.”
Frequently asked questions
What is a corporate brain?
A validated body of company knowledge that also holds your experts’ experience: decision logic, exceptions and warning signs. Every knowledge object has an owner, a validity date and a source. People query it via AI chat, AI systems via MCP server or API.
Does Omnora replace our RAG pipeline or our assistant?
No. Omnora provides the validated knowledge layer underneath, connected to your existing systems via MCP server, RAG API or REST API, Microsoft Copilot included.
How much time does this take our experts?
An AI interview takes about 30 minutes and fits around daily work. Nobody has to write anything: Omnora structures what was said and puts it forward for approval.
How does the context stay current?
Validation questions regularly check content with its owners. Outdated content gets flagged, and contradictions are resolved rather than indexed.
Where is the data stored?
In ISO 27001-certified data centres in Germany. Processing in the EU, no data transfer to the US, GDPR-compliant and TISAX certified. Your data is never used to train AI models.
Make your experience AI-ready.
We show you on one area of your company how Omnora captures tacit knowledge and makes it available to your AI.
Further reading
- Agent enablement: the context AI agents needThe model is the first suspect. Usually it is the context.
- Microsoft Copilot vs. custom enterprise AINot Copilot or build your own, but: where does the context come from?
- RAG architecture in the enterpriseThe prototype runs in weeks; the roll-out fails on the state of the sources.