Assess & Define
Pick the target workflow, set success metrics, and map data, access and compliance needs.
We connect Claude and Claude Code to your applications, data, codebases and workflows. Every deployment ships with the architecture, security and governance needed for production. Your pilots become secure, measurable enterprise workflows, not one more demo.

We help you go from people simply having Claude access to Claude doing governed work inside your systems. It reads only what each user is allowed to see, uses approved tools, and asks for approval before sensitive actions.

We connect Claude to approved documents, databases, CRMs, ticketing systems, internal APIs and legacy applications. We do it through MCP servers and well-defined tools, so answers come from your real context and respect existing permissions.

We build workflows where Claude gathers context, reasons, calls tools and prepares outputs. It pauses for human approval before sensitive steps. You decide what it can read, what it can do, and what is off-limits.

We configure Claude Code around your repositories, coding standards, IDEs and CI/CD pipelines. That includes shared settings, hooks, skills, approved plugins and team policies. Developers get consistent, secure help that follows how your team already ships software.

We set up SSO, SCIM, role-based access, sandboxing, connector and action policies, data protection, audit logging and monitoring. Users never gain access to information just because they can ask an AI for it.

We recommend a deployment based on your requirements: Anthropic-managed Claude Enterprise, Amazon Bedrock, Google Cloud Vertex AI, Microsoft Foundry, or a governed API gateway. The choice depends on your cloud commitments, data residency, retention and compliance needs.

We expose your validated pipelines, notebooks, Python, R and command-line tools to Claude as controlled tools and reusable skills. Researchers get a conversational, agentic layer on top. Your pipeline stays the source of computational truth, and your data stays in your environment.
A successful POC is not production. We build the technical, security and operating foundation first, prove value on one measurable workflow, then scale.
Pick the target workflow, set success metrics, and map data, access and compliance needs.
Choose the deployment model. Set up identity, network, policies, sandboxing and audit.
Connect systems through MCP and APIs. Configure skills, hooks and Claude Code standards.
Enable a pilot group, capture baseline metrics, and confirm value, cost and reliability.
Roll out what worked, and manage seats, spend, adoption and policy as usage grows.
We plan architecture, testing, monitoring, failure handling and maintainability from day one, not after the demo.
We focus on the last mile between AI and the apps, APIs, data and codebases where your work already happens.
Identity, permissions, data boundaries, action controls and human approval are architecture requirements from the start.
We measure success by cycle time, effort, quality, cost and developer productivity, not by how many seats are deployed.
We work with your existing investments in Anthropic, AWS, Google Cloud, Microsoft or a direct API.
After go-live, we provide hands-on training, admin handover, and ongoing tuning as Claude and your needs evolve.