We build the Model Context Protocol server layer that makes your existing systems readable and actionable by AI agents.No migration. No rip-and-replace. Governed from day one.
The systems running your business already hold the context an AI agent needs. The problem was never the data. It was that nothing could reach it safely.
Model Context Protocol (MCP) is the emerging open standard for connecting AI agents to real enterprise systems. We engineer that layer for you, so the platforms you have already invested in become the foundation for what comes next.
Critical context sits locked inside systems that were never designed to be queried by anything other than a human with the right login and a report request.
We build a governed MCP server layer that exposes exactly the operations you approve, in a form any MCP-capable agent can understand.
Your teams ask questions in plain language and get answers from live systems. Routine operational work moves from manual retrieval to governed automation.
Modernisation without migration. We connect what you have instead of asking you to rebuild it.
Not a dashboard. Not another platform to adopt. An engineered integration layer that sits between the systems you run and the agents you want to put to work.
We build the server layer against your existing ERP, CRM, core banking, databases and internal APIs. Nothing gets migrated, rewritten or moved.
Every tool is defined with explicit permissions, role boundaries and an audit trail, so you always know what an agent can reach and what it actually did.
We instrument around the current stack. Your production workflows keep running exactly as they do today while the layer is built and tested.
Agents retrieve live operational context and, where you allow it, write updates back through controlled actions with human checkpoints.
A business question becomes a governed system call. Your teams stop waiting on report queues and custom extracts to get an answer.
Once your systems speak a common protocol, every future automation builds on the same connected foundation instead of another point integration.
MCP is an open standard, and we build to the standard. That keeps the decision about which AI platform you use yours to make, and yours to change.
Platforms that speak MCP directly connect to the layer we build without a translation shim in between.
For platforms that expose tools through function-calling patterns, we adapt the same governed layer to fit.
If you are building agents in-house, our engineers work alongside your team to connect them to the layer and the systems behind it.
Each of these starts the same way: a system that holds the answer, and a team that currently has to go and fetch it manually.
Which customers are past due beyond 60 days? Which purchase orders are still open? Answered from live ERP data, not last night's export.
Query live stock positions, surface low-stock exceptions across locations and assemble movement summaries without anyone pulling the data by hand.
Track consignments in motion, flag delays as they emerge and keep records and stakeholders updated through a single governed channel.
Pull transaction sets across systems, surface discrepancies and assemble the supporting context your finance team needs to close faster.
Cross-reference deal stage with order and payment history to surface the accounts that genuinely need attention this week.
Spot the patterns that only appear when systems are read together, then route the full context to the person who can act on it.
A deliberate sequence. We understand the environment before we design, and design before we build.
We map the systems in scope, where the data actually lives, how it can be accessed and what your governance and compliance boundaries require.
We define the tool schema, read and write scopes, role-based permissions and the escalation points where a human stays in the loop.
The server layer is built and validated against your live systems, engineered so that day-to-day operations continue without disruption.
Your chosen agent platform is connected, workflows are configured, and the layer is handed over with documentation and operational support.
Opening production systems to an agent is a governance decision before it is an engineering one. We treat it that way.
Every boundary is designed with you, in writing, before the first tool is exposed.
Engineering Engagements Sized to Where You Are
A focused assessment of your stack, access paths and governance needs, ending with a scoped build plan.
One system, one well-defined set of tools, connected and running in production before you widen the scope.
Several systems connected under one governed layer, with orchestration across the workflows that span them.
Continued engineering as your systems, tools and agent workflows change over time.
What changes by market is not the engineering. It is the residency, the frameworks you have to satisfy and the people who have to sign it off.
Deployed in your VPC and documented to clear SOC 2, HIPAA and the state privacy patchwork before procurement asks.
EU-resident by construction, engineered around GDPR, the EU AI Act, NIS2 and — for financial entities — DORA.
On-premise or domestic-region delivery built to move agents past PoC, with documentation in Japanese.
Most conversations start with a system map. Share the platforms and databases you depend on and what you want an agent to be able to do. We will scope the build from there.
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