Engineers who stay until the work is running.

What it is

A senior engineer, or a small team, deployed forward into your organization for the length of an engagement. Forward deployed describes where the work happens rather than a job title: instead of writing a recommendation and leaving, the engineer learns your environment, agrees each decision with you, builds inside your tenant under your change control, and hands over something your team can run. Accountability for the outcome stays with us until that handover is finished and accepted.

What this is not

Who it is for

• Organizations whose AI pilots have not reached production
• Teams with a Microsoft 365 or Azure estate and no in-house AI engineering capacity
• Leaders who need an accountable owner rather than another set of recommendations
• Partners who need delivery capacity under their own brand

What we do

• Discovery against your real environment, not a questionnaire
• A prioritized plan with the decisions, dependencies, and risks written down
• Implementation inside your tenant, under your change control
• Identity, permission, and data boundary work before anything is switched on
• Governance and monitoring designed with the build rather than added afterwards
• Adoption work with the people who have to use it
• Handover to your team, or continued operation by ours

What you get

• Environment assessment and prioritized findings
• Implementation plan with validation criteria and rollback requirements
• Working implementation in your tenant
• Governance model, ownership map, and operating documentation
• Adoption material written for your users
• Measured result against the baseline agreed at the start

How an engagement runs

1. Discovery and architecture

   We start in your tenant, with read access, rather than in a questionnaire. What comes out is the current state as it actually is, the decisions that have to be made, the dependencies between them, and an architecture written down in enough detail that your own team can argue with it. If the honest finding is that nothing needs buying yet, that is the finding you get.

2. Governed implementation

   Building happens inside your tenant, under your change control, against a plan you approved. Identity, permission and data boundary work is done before a capability is switched on rather than after. Every change carries its validation criteria and its rollback path into the change record, so how to undo it is answered before it is made rather than during an incident.

3. Integration and validation

   The work is connected to the systems it has to live with, then tested against the criteria agreed at the start rather than against a demonstration script. Validation includes the failure paths: what the workflow does when a source system is unavailable, when a permission is missing, and when a person needs to reject an output. Results are recorded against the baseline taken during discovery.

4. Handover and operation

   Documentation, a named owner on your side, and working sessions with the people who will run it. From that point your team can operate the result without us. If you would rather we kept running it, that is a separate managed operations agreement with its own scope, available after launch rather than bundled into the build.

Human approval points

• The architecture and the implementation plan, before any building starts
• Each production change, with its validation criteria and its rollback path stated
• Any new access to data, before the access is granted rather than after
• Any workflow step where an automated output affects a customer, a payment, an employment matter or a regulated record
• The point at which the work is accepted as finished and ownership transfers to your team

What we need from you

• A named business owner who can make decisions, and a named technical owner who knows the environment
• Access provisioned through your normal process, at the level the current phase needs and no higher
• Time with the people who do the work today, because the process as documented and the process as performed are rarely the same
• Timely decisions at the approval points above, which is usually what sets the pace of an engagement
• Your own security, change and data policies, given to us at the start rather than discovered at review

Data, access, and ownership boundaries

• Everything is built in your tenant, on your subscriptions, under your licensing. You own it while it is being built, not only once it is finished.
• Access is scoped to the current phase and is time bound. Standing administrative access is not the default and is not requested as a convenience.
• Your data stays in your tenant and inside your Microsoft data boundary. We do not copy production data into our own systems in order to work on it.
• Your data is not used to train models, ours or anyone else's.
• Our access is logged in your environment, so what we did is auditable by you, from your own records, without asking us for them.
• When the engagement ends our access ends with it, and you can verify that from your own identity logs.

Handover, ownership, and what happens after

The engagement is finished when your team can run the result without us, and the handover is the part that decides whether that sentence is true.

• Written operating documentation: what was built, why each decision was made, and what to do when it misbehaves
• An ownership map naming who owns each part on your side, because a system owned by everybody is owned by nobody
• Working sessions with the people who will operate it, rather than a document sent to a distribution list
• The governance model and the monitoring, handed over as configured rather than as described
• Full ownership of what was built, in your tenant, with no dependency on us to keep it running
• Managed operations if you want them, as a separate agreement, available after launch

Microsoft technologies this work touches

• Microsoft Entra ID, including Conditional Access and identity governance
• Microsoft 365 and SharePoint, including permission and sharing remediation
• Microsoft Purview, for classification, labeling, retention and audit
• Microsoft Defender, across endpoint, identity and cloud applications
• Microsoft 365 Copilot, where the capability is already licensed and unused
• Microsoft Copilot Studio and Power Platform, where a workflow is better served low-code
• Microsoft Foundry and Azure OpenAI in Foundry Models, where a workload needs a custom model
• Azure infrastructure, networking and platform services
• Azure Monitor and Log Analytics, for the telemetry an operating model depends on