Make every AI agent work as part of your team.
AI pilots are running everywhere, but every agent works from different knowledge. Teklens gives every agent and team the same prepared, checked picture and the same playbooks, in the tools you already use.
Hosted CH/EU · European proxy · no training on your data · approval before every change
In one sentence.
Teklens is your company’s Company Brain: it connects Jira, Confluence and code into one prepared picture that people and AI agents use alike, and keeps it current after every decision.
One picture for every agent.
Claude, Codex, Cursor and other MCP clients pull the same checked context. No separate RAG per team.
The same playbooks.
Proven ways of working that people and agents follow. A person approves the result.
Governance built in.
Model choice per project, European proxy, anonymisation, roles and approvals. In Enterprise also your own model.
Two agents. One picture. One result.
The difference shows when two agents work on the same task.
The product team uses a copilot with its own prompt. Engineering runs its own RAG. Support tests a third agent.
Each knows a different version of the spec. Last week’s customer request is missing everywhere. Results contradict each other, and nobody knows which source they used.
Both agents pull the same prepared picture from Teklens and follow the same approved playbook.
When the requirement changes, the picture is updated for everyone after approval. Every answer names its source.
Where AI leaders start.
From the Teklens Playbook, chosen for building one AI system across teams.
Make an AI pilot measurable.
“We have lots of pilots, but no number that shows what works.”
Set a few indicators per pilot and review them regularly with evidence, instead of reporting success by feel.
The result: Pilots you decide on with evidence.
Related: Run an adoption experiment
Record agent decisions.
“Which model may see which data? It’s written down nowhere.”
Record decisions on model choice, data access and approvals once, with consequences and reasons, findable for everyone.
The result: Governance that holds at the next review.
Related: Define service level objectives
Check agent output against the decision.
“The agent delivers fast. Whether it matches the decision, nobody sees.”
Check what an agent built against the requirement and the decision, with its location. A person approves.
The result: Fast agents that build the right thing.
Related: Run a retrospective
What changes for you.
| Today | With Teklens |
|---|---|
| Every team builds its own context for its agents. | One prepared picture that every agent uses. |
| Results without a traceable source. | Every answer with a source, every change with approval. |
| Changed requirements never reach the agents. | Updated for everyone after approval. |
| Model choice and data access scattered per tool. | Model choice, roles and proxy in one place. |
We agree the criteria for your test together.
Let’s test Teklens on one AI workflow.
Pick a workflow where two agents or teams work from different knowledge today. We show the difference on the real case.
Hosted CH/EU · no training on your data · model choice per project