This case study describes a generic mid-size fiduciary firm in an English-speaking offshore jurisdiction. Specific firm, jurisdiction, and individuals have been anonymised per AgentsBooks's privacy policy. Numbers are aggregated from the firm's pre- and post-deployment audit records.
The starting state
The firm operates as a regulated fiduciary practice with a few-dozen-person team across compliance, accounting, and client-services functions. Pre-deployment, customer onboarding ran on a manual checklist process: a junior analyst reviewed the inbound document set, populated a regulator-mandated questionnaire, escalated risk-flag items to a senior reviewer, and routed the case to a designated approver.
Median time-to-onboarding-completion: 18 business days. P90: 36 business days. The bottleneck was the senior-review queue.
The firm's regulator-mandated cycle time was 30 business days for standard-risk customers and 45 for high-risk. The firm was meeting it but not comfortably, and growth in inbound case volume was eating senior-reviewer capacity at a rate that would have required net-new senior hiring within two quarters.
The 8-primitive shape of the deployment
The firm deployed an agent fleet that mirrored the existing process — not a rip-and-replace, but a parallel agent layer the human team could oversee:
- Intake agent (Identity:
intake-tier1). Parses inbound documents (PDFs, scanned IDs, business registration documents) and populates the regulator's questionnaire schema. Heart:eventtriggered on inbound email. - Risk-screening agent (Identity:
risk-screener). Runs WorldCheck + sanctions list lookups via MCP servers; scores the case; flags items that warrant senior attention. Heart:A2Atriggered on intake-agent completion. - Senior-review agent (Identity:
senior-reviewer). For flagged items only — composes a structured review memo (Decision + Evidence + Confidence per the audit-trail spoke) that goes to the human partner for sign-off. Heart:A2Afrom risk-screener. - Operator dashboard. Human approvers see the full audit trail per case + the four-tuple decision; sign-off is a single click.
The substrate emits the Memory + Knowledge primitives that make the audit trail queryable; the substrate handles the Heart cadence; the Friends graph routes agent-to-agent.
What changed
After 90 days of shadow-mode followed by 90 days of human-in-the-loop:
| Metric | Pre | Post | Δ |
|---|---|---|---|
| Median time-to-onboarding | 18 BD | 6 BD | -65% |
| P90 time-to-onboarding | 36 BD | 12 BD | -67% |
| Senior-reviewer time per case | ~90 min | ~15 min | -83% |
| Escalation rate (to partner) | unchanged | unchanged | 0% |
| Audit findings on closed cases | baseline | baseline | unchanged |
The firm's regulator audit cycle came back with no new findings — the audit trail per case was stronger, not weaker, after deployment, because the four-tuple structure (Intent + Evidence + Decision + Confidence) replaced the prior free-text-memo trail.
What didn't work the first time
Two things the firm got wrong initially, then corrected:
- Routed agent decisions straight to partner sign-off. The partner queue overflowed in week 1. Inserting the senior-review agent as the intermediate layer (Pattern 2 in the HITL spoke) brought the partner queue back to pre-deployment volume while still processing 4× the inbound.
- Initial eval set was too small. 80 historical cases didn't cover the long tail of customer types. Expanding to 450 cases (drawn from the firm's two-year case history) caught three risk-classification regressions in the first model swap. They re-shipped without those regressions.
The economics
- Token cost across the fleet: roughly $1,200/month at steady-state volume.
- Senior-reviewer time saved: ~80 hours/month at the firm's loaded cost.
- Partner time saved: ~30 hours/month.
Payback period on the deployment effort: ~3 months. The firm reinvested the senior-reviewer capacity into higher-margin advisory work rather than reducing headcount.
What this case is not
It's not a fully-autonomous firm. The partner still signs every onboarding decision; the agent fleet is amplifying the team, not replacing it. The firm's regulator wouldn't currently accept agent-only sign-off, and the firm isn't pushing on that boundary.
It's not a one-size-fits-all template. The firm's specific case mix + regulator regime shape what agents you build. Other AgentsBooks customers in the same regulator regime have shipped meaningfully different fleets.
FAQ
Q: How long did the deployment take?
A: Initial agent fleet (3 agents) was running in shadow mode within 6 weeks. Cutover to HITL was another 12 weeks. Total: ~18 weeks from kickoff to "this is our production process".
Q: What was the hardest part?
A: Eval set construction. Getting from 80 cases to 450 cases of high-quality labels took the senior team about 4 weeks of part-time work. That work pays back across every future model swap.
Q: Can a similar firm replicate this?
A: Yes — the firm-starter for fiduciary-onboarding on AgentsBooks is a one-click clone of the agent fleet described above. You'd customise the regulator-mandated questionnaire schema for your jurisdiction.
Q: How does this map to the 8 primitives?
A: Identity per agent, Heart per task, Friends edges between agents, Memory + Knowledge for the audit trail, Control via Slack notifications to the partner queue, Shares not used (the firm doesn't expose public-facing agents).
Want to see the firm-starter? Start free →
