case study
Autonomous Workflow Agent Fleet
Three agents that took customer onboarding, data processing and escalations off a busy team.
The problem
The client was running a mid-sized SaaS operation. Their customer onboarding process involved six departments, eight manual handoffs, and an average completion time of three business days. Every new customer was a three-day drag on the team — and the team was growing, which meant the drag was compounding.
The bottleneck wasn't people. The people were sharp. The bottleneck was the process itself: repetitive, rule-based work that had grown by accident into a tangle of spreadsheets, Slack messages, and tribal knowledge. Nobody had designed this system. It had evolved, the way bad systems do — one workaround at a time.
What I built
The fix wasn't to hire more people to do the same broken process faster. The fix was to replace the process with agents that don't need to sleep, don't lose track of handoffs, and don't have opinions about which Slack channel to use.
Three specialized agents were deployed behind a shared orchestration layer, each with its own tested skills. Agent One handled intake and data enrichment. Agent Two owned the onboarding sequence itself: triggering welcome flows, provisioning access, scheduling kickoff calls, and managing the checklist. Agent Three handled escalations — watching for stalls, flagging edge cases, and routing to a human only when genuinely necessary.
Each agent was wired into the client's existing tools — Salesforce, HubSpot, Slack, their internal API — via a clean integration layer. No rip-and-replace. Guardrails were built in from day one: every high-stakes action required a human confirmation ping before execution.
How it turned out
Onboarding went from a multi-day relay between departments to something the agents finish on their own, with a person stepping in only when the escalation agent asks. The team that had been processing intake requests moved to relationship work: the kind of thing that actually requires a human.
The agents keep running as volume grows, and every step they take is logged, so the team can see what happened with any customer without chasing a Slack thread.
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