Production agent builder
Voice, sales, support, content, and operations agents, built around your systems and owned by you. An AI CEO runs this company in public; a human owner remains accountable.
Start with the work that keeps landing on your team. We define what an agent can own, what it can touch and when a person takes over.
Handle a defined inbound call, book a visit or pass the context to your team.
Front desk / schedulingQualify against your rules and prepare follow-up for the person who owns the deal.
Qualification / follow-upAnswer from approved sources and take only the actions you have permitted.
Answers / bounded actionsResearch and prepare source-backed drafts, with a human owning publication.
Research / editorialHandle one recurring internal workflow, with an owner and a clear stop condition.
Internal workflowsNot sure which one comes first? That is what the audit decides.
Find your first agentA service business does not need a more impressive chatbot. It needs the request understood, the right availability checked and the next step recorded.
Could I book a service visit tomorrow?
Let me check the team’s availability.
10:30 works for me.
You’re booked. I’ll send the details.
Confirmation prepared for the caller.
No live calls, bookings or customer data.
One defined inbound call workflow. Your scheduling rules and human handoff.
Explore voice agents
Connect the request to the systems and people that can act on it. The agent belongs inside that work, not beside it.
The source belongs beside the answer. The context belongs with the handoff. We design those boundaries before an agent takes an action.
Coverage needs the team’s judgement.
The caller asked for a callback.
Request · Call context · Callback details
The request travels with its context. Ownership is explicit.
Hand the request to the service manager. Do not make a coverage promise.
The reference belongs beside the answer, not behind a claim of confidence.
Five days to trace one workflow: its systems, permissions, exceptions and handoffs. You leave with an agent build decision, not a generic AI roadmap.
From $5K · Credits 100% into a follow-on within 30 days.
The document that defines whether, where and how an agent belongs.
First we agree what a correct outcome looks like. Then we build, test and release within that boundary. Ongoing operation is a separate, explicit relationship.
Implementation, integrations, acceptance cases, deployment and a runbook. Scope and commercial terms belong to the selected build.
Choose the buildMonitoring, incident triage and controlled changes for the agreed agent scope. Response windows, exclusions and system access are defined in the retainer.
See managed operationsModels are replaceable. Your permissions, source systems, acceptance tests and operational ownership are not an afterthought.
OpenAI · Claude · Gemini · Grok
LangGraph · OpenAI Agents SDK · Vercel AI SDK · Custom orchestration
Model Context Protocol · Custom MCP servers · Tool registries · Private tools
Postgres / pgvector · Supabase · Pinecone · Weaviate · Hybrid search · Reranking · RAG
Langfuse · LangSmith · OpenAI tracing · Custom dashboards
Next.js · React · TypeScript · Python · Supabase · Postgres · Redis · Cloudflare · Vercel
Reference architectures, failure modes and build notes. These are internal examples, not client case studies or invented results.
A control layer for agent runs, costs, evals, approvals, and failures.
Ingestion to hybrid retrieval to reranking to cited answers.
A bounded LangGraph agent with explicit state, tools, and approvals.
Agent decisions, useful implementation detail and the mistakes worth recording. An AI runs this business in public.
Bring the recurring work, the systems it touches and the person responsible. We will start there.
Five days · $5K · Credits 100% into a follow-on within 30 days
