Skip to content

We take repeatable work off your desk and turn it into AI-native workflows with human control.

  1. Your rules You set the standard and approval points.
  2. The workflow It prepares, checks, and follows through.
  3. Less to carry Routine work keeps moving. You approve.
Speak with an AI Architect

We build and operate workflows across

  • Atelier
  • Amazon Web Services
  • OpenAI
  • Anthropic

Companies running AI-native workflows with us.

Why they choose us?

AI-assisted workflow

AI handles one task. You carry the rest.

You carry 5 of 6 steps.
  1. Give the task You
  2. Draft generated AI tool
  3. Review the output You
  4. Add missing context You
  5. Move to the next tool You
  6. Follow it through You
AI-native workflow

Runs end to end with an approval gate.

You approve 1 of 5 steps.
  1. Work arrives Workflow
  2. Gather context Workflow
  3. Execute the steps Workflow
  4. Approval gate You
  5. Complete and record Workflow

The result

Time back. Decisions stay yours. The workflow carries routine work forward. Your team steps in when judgment matters.
Where we take over

The AI-native workflow runs the day-to-day work across your tools.
Your team keeps control.

How it works

We identify the right workflow, define the proposal, select a provider, and keep the results visible.

  1. Speak with an AI Architect

    On the workflow call, we choose which workflow to implement first. We then document its steps, requirements, constraints, and success criteria in a workflow definition workshop.

    Speak with an AI Architect
    1. Workflow call
    2. Workflow selection
    3. Workflow definition workshop
    4. Ready for proposal

  2. Receive a proposal

    One proposal defines the work before you choose a provider.

    1. Selected workflow
    2. Scope
    3. Success criteria
    4. Implementation timeline and cost

  3. Select a provider

    Choose where the workflow runs. Implementation costs 1,000 EUR per day. You pay the provider directly for infrastructure and inference through a subscription, token usage, or both.

    1. Provider selection
    2. ApplauseLab implementation
    3. Provider running costs

  4. Results

    Read field notes on the products, workflows, and systems we have shipped.

    Inspect the work
    1. What shipped
    2. How it was built
    3. How it held up

Questions

Is this an agency, a consultancy, or software?

None of the usual shapes. You get an outcome like from an agency, it runs on software like a product, and someone stays responsible like a service. The industry has started calling this service-as-software. We just call it the work, done - with your name on the decisions.

Will it work with the tools we already use?

That is the point. We build across what you have. The workflow check identifies anything that cannot be connected before we start.

What if the AI gets something wrong?

Anything unclear or unusual stops and goes to a person. You can see what it based the work on, change it, reject it, or take over. And the harness never gives a step more trust than it has earned.

How do we know it is actually saving us anything?

We record how long the work takes today before we build. Then we measure the same thing in production and show you both numbers. If it is not paying for itself, you will hear it from us.

What if we want to stop?

The workflow check, build, and later changes use the published rate of 1,000 EUR per day. The proposal states the expected days before work starts. You can stop ongoing operation at the end of the agreed billing period, and the workflow definition, rules, and documentation remain yours.

Three notes from the systems we build.

All field notes

Which workflow is costing you time?

Show us one repetitive workflow. We will tell you if it is worth rebuilding.

Speak with an AI Architect