AI Agent Development — ship a production agent in 2-4 weeks.
A working AI agent in your stack — triaging inbound, enriching records, running outreach, drafting replies, or running the nighttime operator seat. Not a prototype, not a Zap that breaks when someone renames a column. A real agent, versioned, observable, yours.
The problem
Most "AI agent" projects at SMBs end up as one of three things: a glorified chatbot that can't actually write to your CRM; a Zap chain that falls apart the first time someone changes a field; or a six-figure "platform" demo that never ships to real users. Each of those spends the budget and solves nothing.
A real agent has a written job description, tool access to the systems it needs, a failure mode you can explain in one sentence, and a dashboard that tells you when it's running and when it's not. That's what we build.
What you get
- A written "agent job description" — scope, tools, failure modes, metrics.
- Production deploy on Vercel / your infra / your choice — not our portal.
- Observability dashboard: every tool call, every token, every failure, timestamped.
- Schema-validated tool interfaces so the agent can't write bad data.
- Handoff doc + a 30-day tuning retainer option.
- Repo access from day one. You own it when we stop invoicing.
Proof — what we've shipped
Agents research buyers, verify contacts, personalize outreach, and run DKIM-authenticated send. 21 opportunities surfaced.
Daily sales + inventory summary pushed to the owner's phone — without anyone opening a dashboard.
Selects questions per user, tracks mastery, adjusts difficulty. 10,993 questions live, bilingual.
Our stack
FAQ
n8n, LangGraph, or something custom — how do you decide?
If the agent is glue between SaaS tools and email, n8n wins on speed-to-production. If it's long-running, multi-step reasoning (research → synthesize → outreach), LangGraph or a native TypeScript agent is safer. We pick in the first week, in the open.
How do you handle failures and hallucinations?
Three layers. Schema-validated tool calls so wrong data types can't slip through. Human-in-the-loop on write actions above a fallback threshold. Observability dashboard with every tool call logged. You see it in production, not in the postmortem.
How long from kickoff to a working agent?
14 days for a scoped v1 in most cases. 2-4 weeks when the agent touches a legacy DB or a new third-party API. The scope doc is explicit — if the hard part turns out to be bigger than we priced, we tell you before you get a surprise invoice.
Can you integrate with our existing WhatsApp / Telegram / Slack stack?
Yes. We've shipped Telegram-native reporting for RetailOS (Mr. Donut), DKIM-authenticated email outreach for Bridge Sourcing, and Arabic WhatsApp workflows. If it has an API or an SMTP, we can drive it.
Ready to scope an agent?
20-min fit call — we'll tell you if it's a 2-week job or a 2-month one, before you spend.