An AI agent is only as useful as the systems it can reach. We connect agents into the tools your firm already runs, so they pick up work where it happens and write results back where people already look. Not another disconnected tool to log into.
This involves wiring an AI agent into the software your firm already runs, so it works as part of your setup rather than off to one side of it.
We build and run AI agents for governance-led businesses. An agent that isn't connected to anything is stuck: it can't pick up work as it arrives, and it has nowhere to put the results it produces.
If you're worried you'll just end up with another tool nobody logs into, don't. Integration is the part that brings an agent into the work, rather than leaving it parked beside it.
What an agent connects to depends on your setup. These are the parts a connection usually involves.
An agent works from a trigger, and the best triggers are things already happening in your systems: a new record in the CRM, or a document arriving in your management system. The agent picks up the work the moment it appears, without anyone passing it along.
Nobody hands the agent its work. It's already watching for it.
When the agent finishes, the result has to land somewhere useful. We write it back into the system the next person already opens, whether that's the case record, the CRM or the shared workbook. There's no separate report to chase and no export to download.
The work lands where the next person is already looking.
Most firms run a familiar mix: a CRM, an ERP, Microsoft 365 and a document management platform. We connect agents to those systems through their supported interfaces, so an agent reads from and writes to the tools you've already standardised on. If something in your setup is unusual, that's a good thing to raise in scoping.
Your stack stays your stack. The agent joins it.
An agent reaching into your systems has to do it safely. Each agent runs in an isolated Azure tenancy, with access scoped to only the systems and the data its process actually needs. Nothing wider, and nothing shared with another client.
Connected, and contained to exactly what the job needs.
Your systems don't stand still. They get upgraded, replaced and reconfigured. A connection that worked perfectly at launch can stop working when the software around it moves.
We run every agent we build, and that includes its connections. When a system you rely on changes, we adjust the integration so the agent keeps reading and writing where it should. A connection that's looked after is the difference between an agent that keeps working and one that slowly falls out of step. It's part of what makes this a managed AI agent service, not a one-off job.
Connecting an agent to your systems isn't a separate project with its own price tag. It's part of scoping, building and running the agent, and it's quoted as one thing.
You start with a refundable commitment per agent. It's a prepayment that goes towards the work, returned in full if we don't deliver the agent to the spec we agreed.
Once the agent is live, you're billed per output, the finished pieces of work it produces. And if an output doesn't meet the standard we agreed, you're not billed for it.
Here's an example. A team uses an AI tool to check incoming documents. The tool works. Getting documents to it, and results back, is the problem.
A document arrives. Someone downloads it, someone uploads it to the tool, and the tool runs the check. Then someone copies the result back before the case system is updated. Three manual hand-offs around one automated check.
A document arrives in the case system and the agent is triggered. It runs the check, writes the result back, and the case system is updated. No downloads, no uploads, no copying.
The checking was never the slow part. The moving between systems was, and a connected agent removes it.
This is an illustrative example. How an agent connects is shaped by your own systems, and is mapped during a Discovery session.
The common ones: CRMs, ERPs, Microsoft 365 and document management platforms. In general, most tools that offer a supported way in. We connect through those supported interfaces rather than anything fragile. If a system is unusual or older, it's worth raising early, in a Discovery session, so we can be straight with you about what's involved.
Some involvement, yes, mostly from whoever owns the systems: arranging access and credentials, and answering questions about how things are set up. The integration engineering itself is ours. Your team doesn't build anything.
Only what its process needs, and no more. Access is scoped to the specific systems and data the agent works with. An agent that checks documents doesn't get the keys to everything else.
Each agent runs in an isolated Azure tenancy, separate from other clients, with access limited to what its job requires. The connection is built to suit work that has to stand up to scrutiny.
We keep the connection working. Running the agent includes maintaining how it links to your systems, so when something changes on your side, the integration is adjusted to match. An agent whose connections aren't maintained slowly stops being useful.
It's part of the agents we design, build and run. We're not a general integration consultancy bolting AI onto anything that will hold still. Connecting the agent is one part of delivering a managed agent that does a real job for you.
We design it. We build it. We run it.
You only pay when it delivers.