Agentic apps and AI tools, built for production
We design and ship bounded agentic workflows, copilots, retrieval systems, internal AI tools, and eval harnesses that your engineers can operate after handover.
What we build
AI tools that do real work inside real systems.
We do not sell chat wrappers. We design the product surface, tools, permissions, evals, and operating model that let an agentic app survive production.
Agentic workflows with stop conditions
Agents that read context, call internal tools, take bounded steps, and hand off to a human when the risk requires it.
Copilots and internal AI tools
Interfaces for support, sales, operations, legal, product, or engineering where AI drafts, classifies, summarizes, or recommends without owning judgment.
Evaluable RAG and search
Retrieval systems with answerability tests, source grounding, explicit refusals, and latency/cost measurement.
Tool and MCP integrations
Connectors into internal APIs, CRMs, warehouses, repos, tickets, and documents, with permissions, audit trails, and action limits.
Evals, verifiers, and release gates
Versioned datasets, rubrics, verifier loops, adversarial cases, and thresholds that block bad changes before production.
Operations and handover
Observability, model routing, cost budgets, runbooks, feature flags, rollback paths, and on-call playbooks.
Our standard
State of the art does not mean more autonomy. It means better boundaries.
- Bounded autonomy: every agent has permissions, limits, and an escalation path.
- Typed tools: external actions run through clear contracts, not free text glued to an API.
- Humans at risk points: approval, editing, or escalation where the domain requires it.
- Measured model routing: frontier when needed, smaller models when they pass the eval.
- Security and auditability by design: identity, permissions, traces, logs, and data under your control.
Engagement shapes
Three ways to work with us
Agentic application builds
Agentic system review
AI tools for existing products
Bring a workflow that currently consumes human judgment.
In 30 minutes we will review the user, the tools the system would need to call, the success criteria, the budget, and whether a defensible eval can be written.