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Agentic workplace

Cowork, Amazon Quick and other productivity agents for business teams, on the same governed foundation as your developers.

The problem

Every business team now asks for an AI assistant, and the offer changes every month: Claude Cowork, Amazon Quick, Microsoft Copilot, ChatGPT Enterprise, Gemini. Most companies we talk to end up in one of these situations:

  • -Several tools were bought by different teams, with overlapping licences and no view on who uses them.
  • -The choice was made on a demo, without checking where the data goes or which systems the assistant can reach.
  • -Licences are paid for everyone, and a few months later most seats are barely used.
  • -Security blocks the rollout because nobody can say what the assistant can read or do.
How we see it
  • There is no best assistant, only a best fit per use. We compare the options on your own tasks, with your data, your identity provider and your security rules, and we write the decision down with the costs.
  • Several tools can coexist when each has a clear job: an agent for knowledge work on the desktop, a BI and research workspace on company data, the suite already bundled with your office tools.
  • Where the data is processed is part of the choice. Some of these assistants can run their inference on Amazon Bedrock, inside your AWS account and region, and that often decides it.
  • Adoption is measured, not assumed. Seats are reviewed against real usage, and the money follows the teams that use them.
  • We are independent from the vendors. We recommend what fits, including the tool you already pay for.
Our approach
  1. 01

    Use cases & shortlist

    With the business teams, we list what they want to do (research, writing, analysis of company data, automating recurring tasks) and the data each use needs. That gives the shortlist and the test tasks.

  2. 02

    Side-by-side evaluation

    The shortlisted tools run the same tasks with a pilot group, in your environment. We compare quality, the data and systems each one can reach, security and admin controls, and the total cost per user. It ends with a written recommendation.

  3. 03

    Governed deployment

    Single sign-on with your identity provider, connectors to the approved sources only, and the same gateway and tool policies as your other agents where the tool supports them. For Claude Cowork, inference can run on Amazon Bedrock in your account.

  4. 04

    Licences, handled

    We can handle the licences for you: procurement, seat allocation per team, renewals and the quarterly review that removes unused seats. You get one contact and one view of what you pay.

  5. 05

    Adoption

    Training on each team's real tasks, shared prompts and skills, and a usage dashboard per team, so the next renewal is decided on numbers.

Where to start
  • -A 2-hour discovery on the tools you already have and what your teams ask for.
  • -A 3 to 4-week side-by-side evaluation with a pilot group, ending with a written recommendation.
  • -The rollout, team by team, with licences and adoption followed over time.
Guide · PDF · coming soon

Choosing a workplace AI assistant

The grid we use to compare Claude Cowork, Amazon Quick, Copilot and the others: the criteria, the test tasks and the questions to ask each vendor.

Shared foundation

Productivity and knowledge-work assistants reuse the layers deployed for coding agents: governed model access, the gateway and its tool policies, cost tracking. If your developers already have them, your business teams start from there.

Developer Agentic Platform →
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