We design, build, and deploy production-grade AI systems for enterprises — autonomous agents, multi-agent orchestration (LangGraph), enterprise RAG, and Model Context Protocol (MCP) integrations. We handle strategy, architecture, engineering, and ongoing operations.

Most engagements begin with a free 30-minute strategy call to identify your highest-ROI AI opportunity, followed by a fixed-scope discovery. From there we run a focused pilot before moving to full production deployment.

Security is designed in from day one: least-privilege access, encryption in transit and at rest, private networking, and audit logging. We can deploy inside your cloud (AWS, Azure, GCP) so your data never leaves your environment, and we support SOC 2, HIPAA, and GDPR-aligned workflows.

We are model-agnostic. We build on a provider abstraction so you can use Anthropic Claude, Azure OpenAI, AWS Bedrock, Google Gemini, or open models — and switch without rewriting your application. We recommend the best model per task based on quality, latency, and cost.

A typical pilot ships in 4–8 weeks, giving you a working system on real data. Full production timelines depend on scope and integrations, but our phased approach means you see value early rather than waiting for a big-bang launch.

We offer fixed-scope project pricing for defined deliverables and retainer-based engagements for ongoing build-and-operate work. After the strategy call we provide a clear, itemized proposal — no open-ended billing.

Yes. We integrate with your existing data stores, ERPs, CRMs, ticketing, EHR/core-banking systems, and internal APIs. MCP and custom connectors let agents act safely within your existing stack.

Alongside consulting, we publish practical knowledge products — ebooks, prompt packs, and templates — so teams can learn and build faster. These are available directly through our store.