We build with Claude where reliability and reasoning matter most: tool-using agents, long-context document work, and the evaluation discipline that keeps them fast, safe and affordable.
Azure
Reviewing a confidential information memorandum
Runs on
Claude is strongest when wired to real tools and data with discipline. We concentrate on the protocol, context and evaluation work that makes agents dependable.
Claude's tool use and reasoning are well suited to multi-step operational work. We design agents that complete real tasks, not chat demos.
We pair Claude's safety posture with our own guardrails, evals and human review, so autonomy is earned, never assumed.
Run Claude via the Anthropic API, Amazon Bedrock or Google Vertex AI, on the infrastructure and compliance posture you already approve.
We connect Claude to enterprise systems through the Model Context Protocol, the open standard for tools and context.
Put large document sets and deliberate reasoning to work on genuinely hard tasks.
Engineering that keeps agentic systems fast and affordable at production volume.
The measurement and safety layer that earns the right to run with less supervision. Every agent ships with golden-dataset tests, prompt-injection defenses, PII redaction and tracing, so reliability and cost are measurable before and after launch.
Yes. We build with Claude where reliability and reasoning matter most: tool-using agents over the Model Context Protocol, long-context document work, and the evaluation discipline that keeps them fast, safe and affordable. We design agents that complete real tasks, not chat demos.
The Model Context Protocol (MCP) is the open standard for tools and context. We connect Claude to enterprise systems through it: MCP servers for internal tools, the Claude Agent SDK, parallel and sequential tool calls, orchestrator and sub-agent patterns, and human-in-the-loop approval.
We pair Claude's safety posture with our own guardrails, evals and human review, so autonomy is earned, never assumed. Every agent ships with golden-dataset tests, prompt-injection defenses, PII redaction and tracing, so reliability and cost are measurable before and after launch.
Yes. Run Claude via the Anthropic API, Amazon Bedrock or Google Vertex AI, on the infrastructure and compliance posture you already approve. We deploy where you trust it.
With prompt caching, the Message Batches API, model tiering across Opus, Sonnet and Haiku, token and latency budgets, streaming responses, and retries and fallbacks. That is the engineering that keeps agentic systems fast and affordable at production volume, and cost is measured before and after launch.
Our published case studies do not name the model, so none is listed as a Claude build. The closest LLM work: Ford rewrites 13,000 engineering requirements to the INCOSE standard in 4 hours instead of 2,170, and Exactera cut client data mapping time 60% with a document agent. On Claude we build workflows such as writing a client proposal and onboarding a new client.