For the CEO, the CFO and IT
AI agents for business: from the first agent to governed agents in production.
We pick a process, build the agent on your data and put it into production with an owner, permissions and audit. Everything runs in your own Microsoft 365 and Azure.
- AI agent programmefor a utility company, won through a utilities-sector tender
- Two-day hackathona fixed price, an agent that runs on your data
- SharePoint governance since 2010permissions, metadata and retention: the data agents read
What we do with AI agents
Each service has its own page, listed below.
One agent for the whole company
A central agent connected to CRM, operations, HR, documents and integration. The agent proposes each operation, and the user approves it before anything is written.
Hackathon on your data
In two days we build an agent on a process you choose, running on your own data.
Copilot Studio agents
Agents published in Teams that fill in forms and prepare requests. The user confirms before anything is written.
Copilot, configured
Tenant configuration for Copilot: data sources, permissions and enabled features.
AI agent governance
Inventory, owners, environments, connector policies and audit.
The right model
Copilot Studio or models from Microsoft Foundry, depending on the data and on compliance.
The stages of an AI agent, from hackathon to production
The same five stages for every agent, in the same order.
- 01
The hackathon
An agent built in two days, on a process you choose.
Teams
Copilot Studio
- 02
The data
The right structure and access, before scaling out.
SharePoint
Dataverse
- 03
The pilot
With the people who will use it every day.
- Teams
- 04
Governance
An owner, an environment, connector policies.
Entra ID
Purview
- 05
Production
With audit and support, then the next process.
Azure DevOps
Common situations
- The same people answer the same questions about procedures and policies every day.
- Data from incoming documents is typed into systems by hand.
- A purchase request or a ticket means filling in a long form.
- You have Copilot licences, but no agent used every day in a process.
- An AI pilot stopped at the demo stage, with no owner and no agreed permissions.
- You have no list of the agents employees have created and the data they read.
If at least three of these sound familiar, the first agent can be built on one of your processes, with an owner, permissions and an audit trail.
Pick a processQuestions about AI agents
AI makes things up. How can we rely on it?
The agent works only with data from the catalogue, from your systems or entered by the user. The agent writes to a system only after the user confirms a card, which the user can also cancel. Where the same decision repeats at volume, the model calculates the proposal, and a person decides on the cases below the confidence threshold.
We rolled out Copilot and hardly anyone uses it.
Copilot answers from the documents, metadata and permissions already in the tenant. When documents are stored in unstructured folders, the answers are poor. We put the documents and access in order first, then build the agent on a specific process that people use every day.
Our data is not in order. Can we still start?
Yes. We start from a single process and put in order only the data its agent needs: the data model, the documents, the connection to the ERP. The two-day hackathon starts from there, on your own data.
Where is our data processed, and is it GDPR-compliant?
The agent runs in your own tenant, with the permissions of the signed-in user. With environments created in Europe, requests to the model are processed within the EU Data Boundary. Microsoft does not use your data to train its models.
Who is accountable when the agent gets it wrong?
Every agent has a named owner in your company, and without an owner the agent is not deployed to production. The agent does not write to any system without the user's confirmation.
Do all our users need a Microsoft 365 Copilot licence?
No. Agents built in Copilot Studio and published in Teams can also be used by people without a Microsoft 365 Copilot licence. Their usage is billed at tenant level, in Copilot Credits.
Related solutions
Copilot on your data (hackathon)
Copilot answers from the documents, permissions and systems it has access to.
Copilot Studio agents
The agent takes the request in Teams, searches your systems and makes a proposal.
Copilot configuration
You bought the licences and switched them on, and the results are modest.
AI agent governance
People in the company are already building agents in Copilot Studio.
Microsoft Foundry: AI on documents
When a Copilot Studio agent is no longer enough, for high document volumes, model choice or formal quality evaluation, we build on Microsoft Foundry, formerly Azure AI Foundry.
Apollo 365 AI Central
One central agent works across every module: CRM, operations, HR, assets, tickets, documents, integration and payments.
How we work
No hidden risk: what you know from the start.
The estimating risk is ours. Your data and your plan stay yours.
Your data stays in your tenant
The solution runs in your own Microsoft 365 and Azure. There is no separate platform to license or maintain.
Fixed price, fixed scope
We price the work before we start. The scope is written down before the first line of code, and any change is priced and agreed in the open.
The written plan is yours to keep
Our proposal comes in writing, with the scope and the steps. Keep it and use it, whether you work with us or not.
Pick the process your first agent starts from.
In 30 minutes we go through the process and agree what to prepare before the project.
Thank you.
We will reply within one business day.