For IT, security & data
Secure Construction Integrations and AI Agents for IT and Data Teams
Every new tool the business asks for is another set of credentials, another data copy and another thing you will be asked to explain. We build integrations and AI agent infrastructure the way IT would want them built: least privilege, read-only by default, logged, tested and kept in version control.
Sound familiar?
- Credentials get copied into every spreadsheet connector, script and AI client config.
- Agents connected to large APIs like Procore can see every write and delete operation.
- Nobody has one place to check what an agent actually did, with which inputs and results.
- Shadow reporting pipelines live on someone's laptop with no tests, no review and no owner.
- Vendor APIs change and fragile point-to-point integrations break silently.
- The business wants AI now, and you are expected to make it safe after the fact.
What changes
- Read-only source connections with secrets in Azure Key Vault.
- One MCP endpoint for every agent, with a scoped API key per agent that sets its tools, upstream auth and rate limits.
- Telemetry on every tool call: who made it, which key and server, the input, the output and per-tool success rates.
- Large API surfaces routed so agents see only the tools the current task needs.
- Pipelines, semantic models and reports kept in Git with automated tests and quality gates.
- Failures that stop publishing and keep the last good data, rather than serving wrong answers.
What we build for you
MCP gateway with telemetry
Tool Runtime pulls MCP servers into one endpoint, controls access by API key and logs every tool call with its input and output. Each key defines which tools, upstream auth and rate limits apply, so every agent gets its own scoped access.
Routing for large API surfaces
Our open-source Procore MCP server can expose 2,755 generated tools, or replace them with about 25 router meta-tools filtered by persona and policy. Every call passes through one dispatch path with schema validation, rate limiting, policy checks and idempotency.
Governed Primavera P6 access
Our P6 MCP server puts a gateway in front of Oracle's REST API with policy checks, approvals, response caching, audit logging and metrics. Agents get 24 tools instead of 585 raw operations, with mutation previews before any write.
Data platforms built as code
We build Fabric lakehouses with a bronze, silver and gold structure, versioned extractors and automated quality gates. The pipelines, semantic models and reports live in your repositories, so they can be reviewed and maintained like any other software.
See the proof
Frequently asked questions
Where do credentials live?
In Azure Key Vault for production builds. Source connections are read-only wherever the use case allows, and agents reach systems through a gateway key rather than holding upstream credentials themselves.
How do you stop an agent from writing to production systems?
By not giving it the tools. With MCP, the selected tool list is the agent's permission boundary. We start with list and read tools, keep writes behind previews and approvals where needed, and log every call.
Is the code open for review?
Yes. We build as code in repositories you control, and several of our reference builds, including the Procore MCP server, are public on GitHub so your team can inspect the patterns before engaging.
Does this run in our tenant?
Our data platforms run on Microsoft Fabric and Azure in your environment, and our MCP servers ship as containers. We work within your identity, logging and network requirements.
What happens when a vendor API changes?
Extractors read their endpoints from versioned configuration, and generated clients come from the vendor's OpenAPI spec, so changes are a reviewable update. Quality gates catch unexpected data before it reaches a report.
Next step
Let's talk about your team
Bring us your security requirements first, and we will show you how we would build to them.
Also for: CFOs & controllers · Schedulers & project controls · Owners, COOs & operations