Knowledge and automation
Private knowledge and RAG systems
Retrieve and synthesize internal knowledge with citations, permissions, evaluation, and deployment in the right data boundary.
Primary buyer: Knowledge, legal, support, and enterprise teamsThe real constraint
Business knowledge is fragmented, permissions matter, and a fluent answer is not the same as a correct action.
How we approach it
We make sources, tools, approvals, audit trails, confidence, and exceptions explicit in the workflow.
How we prove it
Representative tasks are evaluated end to end against correctness, completion time, exceptions, and reviewer effort.
Production system
Knowledge and automation
Controlled systems that retrieve, reason, extract, route, and ask for human judgment when needed.
- 01Knowledge and permission model
- 02Retrieval and structured extraction
- 03Agent tools and workflow state
- 04Human review and exception routing
- 05Audit, monitoring, and retention
Typical fit
Faster trusted access to internal knowledge with visible source evidence
FAQ
Questions before a pilot
These answers describe how we normally work. Only a signed agreement creates commitments. Website enquiry terms
01Our documents are inconsistent and half of them are scans. Is that a problem?
It is normal, and it is the actual work. Clean, uniform documents would not need us. What matters is whether the variation is bounded, because twenty supplier formats is a project and an unbounded long tail is a different conversation. We establish which one you have during discovery, on your own documents.
02Will it act on its own, or does a person stay in the loop?
A person stays in the loop wherever an error is expensive to reverse. We agree the approval points and confidence thresholds with you, and anything below the threshold goes to a review queue with the supporting evidence attached rather than being silently guessed.
03How do you stop it inventing answers?
By grounding it in your own sources and showing them. Every answer carries the passage it came from, so a reader can check it in one click, and the system is built to say it does not know rather than to fill the gap. That reduces invention rather than eliminating it, which is why the review queue and the citations exist.
Service focus
Answers from your own documents, with the receipts
Your people already know the answer exists somewhere. The problem is finding it and trusting it. We build retrieval over your corpus that respects who is allowed to see what, cites the passage it used, and is evaluated against questions your team actually asks.
- Built for
- Knowledge, legal, support, and enterprise teams
- Designed to achieve
- Faster trusted access to internal knowledge with visible source evidence
What you get
- Retrieval architecture inside your data boundary
- Citations and provenance on every answer
- Access rules enforced at query time
- Evaluation set built from real internal questions
Need a different system?
Not quite your solution?
Explore nearby systems or bring the outcome, workflow, and constraints that do not fit a predefined category. Tandemora can scope a custom solution around the real operating problem.
Your version will have different constraints.
Bring the workflow, current system, available evidence, and the assumption you trust least. We will identify the smallest useful next step.
Discuss this system