How we work

Agents, in production.

Agentic AI is not a demo for us. It runs real work across our products, every day. Here is what that looks like, and how it is built.

SignalsAgentOutcomesRepo eventIntegration healthData driftUser sessionClaude agentANTHROPIC SDKTools · MCP · your systemsDraft a PRReconcile dataFlag a regressionAlert with context

// Signals come in. The agent reasons, calls tools, and acts. A human reviews what matters.

The foundation

Built on Anthropic's own SDKs.

We build our agents directly on Anthropic's tooling, the Claude Agent SDK and the Anthropic .NET package, and connect them to the systems they work in through MCP servers and purpose-built tools. People set the direction and hold the standard. The agents do the work in between, continuously and without drama.

Claude Agent SDK Anthropic .NET (NuGet) MCP servers Custom tools Evals & guardrails
Powered by ClaudeAnthropic partner
Where we put agents to work

Quiet, constant work, done well.

Data sync management

Keep systems honest

Agents watch for drift across our services and reconcile it on their own, before a mismatch turns into a support ticket.

Integration observability

Watch the seams

They keep an eye on the third-party services our products depend on, catch failures and breaking changes early, and surface them with the context to act.

Testing simulations

Use it like a person would

Agents drive our apps the way real users do, across flows and edge cases, and report what breaks before anyone else hits it.

Issue to pull request

Arrive with a fix in hand

When something looks wrong in production, an agent opens a draft pull request with a proposed fix and the evidence behind it, ready for a human to review.

Every example here runs against our own products. It is simply how WhiteCrane operates.

Thanks. We have your note and will be in touch.