AI and platform delivery — for consultancies, integrators and agencies

You sold the project. We build it and put it into production.

Closing an agent or automation project is one thing. Making it reliable against the client's data, permissions, security review and deadline is another. We build the agent and its Azure platform inside your delivery, under your brand if needed, without touching your commercial relationship.

When people usually call us

01

The PoC landed and now there is a deadline

The demo convinced the client and the deal closed. Open it up to real data and real users and you get hallucinations, permissions that were never properly modelled, latency, and a cost per task nobody measured.

02

You have the prompt, not the system

The prompt and the flow already work. What is missing is a system that remains reliable against your client's data and permissions, plus reproducible deployment, observability, rollback and the evaluations that client will ask for in the security review. That is what we build.

03

Your capacity is already committed

Your best team is on another account and this one cannot wait for next quarter. You need a pod that owns a specific piece, not individual profiles by the hour.

04

The project needs skills you do not have in-house

Agents, LLMOps, Azure, Kubernetes and CI/CD in the same project. Hiring for one delivery does not add up, and subcontracting two separate vendors means someone has to coordinate them.

Ways we work with you

White-label

We appear under your brand in meetings, documentation and deliverables. The end client deals with you. We sign an NDA and non-circumvention before we start, and we give up using the project as a public reference.

Named specialists

We come in under our own name as specialists within your project, with a bounded scope. Useful when the end client wants to see who is executing the technical part and you would rather not carry that risk alone.

A second opinion before you sign

If you are still closing the proposal, we look at scope, architecture and risks so you know what you are signing. It is the one case where we come in before there is a commitment, and we do it because that is when fixing things is cheap.

The rules, in writing and before we start

  • Your client stays yours

    Signed non-circumvention: we sell them nothing on our own account, during the project or after. We do not talk to them without you unless you ask us to.

  • Who decides and who speaks

    A split of responsibilities agreed before kick-off: who decides, who executes, who communicates with the end client and how an incident gets escalated.

  • Milestones with acceptance criteria

    Every milestone closes against criteria written before we start, with a demo. If the first one is not met, you have an exit option without dragging the rest of the commitment along.

  • Minimum access, bounded data

    We work with the permissions we actually need and agreed environments. Where AI tools are involved, we put in writing which data is used, where and within what limits, in a form you can show your client's security team.

  • A clean exit

    The code lives in whichever repositories you name from day one, with runbooks, an evaluation report and handover sessions. You do not depend on us to run what we delivered.

Trust and security

What your client will ask before letting us in.

When the project belongs to an end client, someone on their security team is going to review this. We have it in writing before we start, so you can show it instead of improvising it.

  • Minimum access and agreed environments

    We work with exactly the permissions our piece needs, in the environments we agree on. No shared credentials and no open access "to move faster".

  • The client's permissions are enforced at retrieval

    Two different users see different things, and the filtering happens when data is retrieved, not by trusting the prompt. This is where most projects stall in the security review.

  • Every answer can be reconstructed

    What was retrieved, under which permissions, what prompt was sent and which model version answered. Without that trace there is no audit and no way to fix the cause.

  • Which data AI tools touch, in writing

    If third-party models are involved, we define up front which data can be used, where and within what limits, in a format you can hand to your client’s security team.

  • Guardrails and human control where it costs money

    Cost and latency limits with alerts, and an explicit boundary: where the agent decides alone and where a person approves. That boundary is a business decision and it is made before the system opens.

  • Confidentiality and non-circumvention, signed

    An NDA before you tell us the detail if you need one, and non-circumvention in writing: we sell nothing to your client on our own account, during the project or after it.

  • The code is yours from day one

    It lives in the repositories you choose, not ours. At the end there are runbooks, the evaluation report and handover sessions: you do not depend on us to operate what we delivered.

If your client requires a specific approval or a particular official partner, tell us on the first call: better to know then than halfway through the project.

When we are not the right call

If you need dozens of people in parallel, an approved vendor with specific certifications, or continuous 24x7 cover, that is not us, and we will say so on the first call rather than let you find out halfway through. What we have is a senior pod that owns a piece and leaves it running.

Three deliveries, and what reached production
Next step

Shall we talk about your project?

In 30 minutes we review what you want to build or what you already have running, the data, the integrations and what it still needs to remain reliable once users arrive. Whether the project is yours or a client’s, the call is the same.

Free 30-minute review, no commitment. We sign an NDA beforehand if you need it. We reply the next business day.