Capabilities.

We design and build production software with AI models embedded in the core workflow, not added as a chat widget: document understanding with page level citations, computer vision pipelines that compare jobsite photos to a plan, and voice guided task assistants. Every system we ship, we operate ourselves in production, so we carry direct knowledge of the operational cost and failure modes of the AI we build.

Our production systems run on a mix of AWS, including EC2, Lambda, DynamoDB, API Gateway, Cognito, and S3, and Cloudflare, including Pages, Workers, and D1, chosen per workload rather than defaulting to one vendor. We build for cost visibility and contained blast radius from the start: per pool spend caps, signed origin authentication between edge and origin, and infrastructure a small team can operate without a dedicated operations function.

We move from a stated problem to a working, testable prototype quickly because every person on the team can design, build, and deploy independently, without waiting on a separate design or infrastructure group. The AI guided staff training platform on this site is one example: a working prototype built as internal research and development to validate an interaction pattern before proposing it to a customer.

Every production system we operate has been through internal adversarial security review covering authentication, per user and per IP rate limiting, resistance to prompt injection in AI facing inputs, and data isolation between accounts, with findings fixed before the next release rather than tracked and deferred. We treat all inputs, including inputs passed to AI models, as untrusted until verified.

As a small team that has personally written, deployed, and debugged the systems described on this site, we advise on architecture choices, AI model and vendor selection, and build versus buy tradeoffs from direct operating experience rather than from a slide deck. That includes plain assessment of what an AI system can and cannot reliably do in production.