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Product · Software · AI agents

Custom AI solutions and agent development

From prototype to useful software, each solution is built for a precise job and the people who will actually use it.

01

Who it is for

  • Organizations whose need does not fit a generic tool
  • Teams seeking a copilot connected to internal knowledge or systems
  • Product or operations leaders validating a solution before scaling it
02

Starting signals

This service becomes useful when…

  1. 01

    A user must search across several sources to complete a frequent task.

  2. 02

    Internal expertise could be made more accessible through a guided interface.

  3. 03

    A process combines research, reasoning, tool use and validation.

  4. 04

    You need a functional proof before choosing a long-term architecture.

03

Concrete engagement

What you receive

  • Definition of the need, users and system boundaries
  • A functional prototype or product within the selected scope
  • Agreed integrations, evaluations and oversight mechanisms
  • Technical documentation and an evolution plan
04

How we work

A three-part progression.

  1. 01

    Define expected behaviour

    We describe tasks, available tools, permissions and situations where the system must stop.

  2. 02

    Prototype with real scenarios

    We build a first version and evaluate it against representative examples, including difficult cases.

  3. 03

    Strengthen what should last

    We improve experience, reliability, observability and integration based on what the prototype teaches us.

05

A healthy boundary

What the approach does not claim to do.

An AI agent is not automatically the right architecture. Better search, a guided interface or a simpler automation can sometimes be more reliable and economical.

06

Before starting

Frequently asked questions

What is the difference between a copilot and an agent?

A copilot generally supports a person in a task. An agent can take a longer sequence of actions with bounded autonomy. The right choice depends on need and risk.

Can the solution use our internal documents?

Yes, when quality, access rights and confidentiality requirements allow it. The architecture must account for those constraints from the beginning.

Can a prototype become a production product?

Sometimes, but not automatically. The transition requires validation of security, performance, costs, operations and expected quality.

Other starting points

  1. 01

    AI advisory and strategy

    View the service
  2. 02

    AI readiness assessment

    View the service
  3. 03

    AI automation

    View the service

Exploratory conversation · 30 minutes

Bring the problem. We will clarify the next decision.

Bring a slow, costly or frustrating process. In 30 minutes, we will clarify what is worth improving and the most realistic next step.

Book a conversation