Pillar 01 · AI Agents
Not a chatbot. Not a Lindy template. Custom-trained agents we deploy on n8n + Groq + custom TypeScript, then operate continuously. Operators audit the edges where automation breaks.
Use cases that ship
Every workflow ships with observability, retries, rollback, and an operator on call. No "experimental" agents, no AI hype.
Every inbound lead enriched, scored, and routed to the right operator or sales rep in under 60 seconds. Tunable thresholds per channel. Average response time drops from hours to minutes, with operator override on high-value leads before they hit a rep.
Auto-fill missing fields, deduplicate records, normalize firmographics. Runs continuously, not as a one-time scrub. Operator audits the edge cases the agent flags as low-confidence before writing back.
First-pass classification, response drafting, escalation routing. Operator approves outbound when stakes are high. Typical mix is 60-70% auto-resolved, 20-30% operator-edited, the rest hand-routed.
Also ship · Sales follow-up cadences · document parsing and extraction · portfolio monitoring and weekly narrative reports.
The stack · self-hosted where it matters
Four primitives layered behind every agent we ship. Custom TypeScript services own the edges where vendor SDKs break.
n8n
Groq
Postgres
TypeScript
Let’s scope your first agent