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One controlled access point to AI models.

Managed AI Model Access

Give product and engineering access to approved models through Teklens instead of distributing individual provider accounts and API keys.

What ships today

Approved models and CH/EU hosting per project are live. The central admin console with per-role and per-team rules, routing and fallback is in beta.

Today

Teams use Claude, GPT, Gemini, coding agents and meeting agents side by side. Access, credentials and approved models fragment – and nobody can say who reaches which data through which model.

With Teklens

  1. Provider
  2. Approval
  3. Role & team
  4. Workflow
  • Admins configure approved providers, models and credentials
  • Models are released per role, team and project
  • Routing and fallback rules run centrally
  • Data and location policies apply per workflow – CH/EU hosting where supported
  • People simply pick “best model” – or let Teklens choose

Result

One approved model set for product and engineering, with access rules and an audit trail instead of shadow AI.

Why Teklens?

Because the same control layer governs the models already powering your product and engineering workflows.

Roles

CPO / CTOEngineerIT Ops

Teklens apps & integrations

Teklens.aiCoding agentsMeeting botAI providers

Example prompts & actions

Copy one of the following prompts and paste it into the Teklens chat. Adapt the details to your use case.

Enable Claude for engineering and Gemini for product.

Route privacy-sensitive workflows only to providers with EU hosting.

Disable model [X] organisation-wide.

Which models are currently approved for project [P]?

Related use cases

Three use cases closely connected to this one.

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