Tell us what needs to ship.

We design and build AI agents and copilots, enterprise workflow automation, RAG and knowledge systems, AI products, SaaS platforms, integrations, and internal software. Strategy, reliability, governance, security, deployment, and operating handoff are included where the workflow requires them.

Start with a workflow that has a clear owner, measurable handling cost or delay, accessible data, and a bounded decision or action. We map the current process, exceptions, systems, permissions, and success measures before recommending a pilot or platform.

Yes, when the systems provide suitable APIs, databases, exports, webhooks, or controlled integration boundaries. We work with the existing permission model, data quality, rate limits, and ownership constraints rather than giving an agent unrestricted access.

Each agent receives the minimum context and tools required for the workflow. Important actions use validation, permissions, approval gates, audit events, evaluation cases, monitoring, and human escalation. Autonomy is increased only when the evidence and risk allow it.

Both. Existing products can be audited, hardened, extended with AI or automation, or reviewed before an architecture decision. New builds begin with a written core workflow, constraints, exclusions, and acceptance criteria.

Yes. The client owns the product code, repository, and agreed infrastructure. Production services are placed in client-controlled accounts where practical, with deployment and operating context documented for handoff.

A bounded pilot can move quickly when the workflow, data, integrations, and decision boundaries are clear. Multi-team automation, legacy integration, regulated data, migration, or a complete software product needs a phased plan. The schedule follows evidence from discovery rather than a standard promise.

The written quote depends on the workflow, integrations, permissions, data readiness, evaluation coverage, migration risk, deployment, and operating requirements. Implementation and recurring model, hosting, monitoring, and support costs are separated.

Yes. The scope can include tool calling, permission boundaries, human approval, retrieval, structured outputs, evaluations, monitoring, and product integration. The design is based on the actual workflow rather than a generic agent template.

Yes. We can review product architecture, AI behavior, data access, secrets, dependencies, integrations, tests, performance, deployment, and operating visibility. The resulting finding register can become a separate remediation or modernization scope.

Yes. Architecture, delivery decisions, and production risks are explained in plain language. Decisions and trade-offs are documented for the founder and any future internal engineering team.

NDA and confidentiality requirements can be reviewed before repository access. Access level, retention, communication channels, and handling expectations are recorded as part of the engagement setup.