CREUX AI
[Solutions / 01]

Products where agents do useful work

Creux designs and builds software where agents, data, systems, and people work together around a specific operating problem.

Where this fits

Start with the product, not the model

An agent is only useful when it has a job, the right context, and a reliable path through the surrounding product. We work from the workflow backward to define the system that should exist.

System of record
Product
Agent input
Context
Control point
Human
Build scope

From operating problem to working product

  • [01]

    Define the job

    Clarify what the system needs to accomplish, who uses it, and where judgment still belongs with a person.
  • [02]

    Shape the system

    Map the data, tools, permissions, interfaces, and handoffs that give the agent a useful operating context.
  • [03]

    Build the product

    Turn the system shape into a product with explicit states, usable interfaces, and dependable paths through the work.
  • [04]

    Evaluate in context

    Test the product against representative work, edge cases, and the decisions users need to make with it.
  • [05]

    Deploy deliberately

    Connect the product to the environment where the work happens and make the transition visible to the people using it.
  • [06]

    Keep compounding

    Use real usage, feedback, and failure modes to improve the system after the first release.
Focus

Build surfaces

  • [01]Agentic product strategy.
  • [02]Workflow and interaction design.
  • [03]Data and knowledge systems.
  • [04]Integrations and orchestration.
  • [05]Evaluation and observability.
Expected outcomes

The product should earn its place in the workflow

  • [01]Clear responsibilities between agents, software, and people.
  • [02]Interfaces that make system state and next actions understandable.
  • [03]Evaluation that reflects the work instead of a demo environment.
  • [04]A product foundation that can grow with the operating problem.
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