Multi-Agent Compliance Operations
A planner-executor mesh of policy, evidence, and exception agents replaced a fragile stack of single-purpose RPA bots — and nearly doubled compliance workflow coverage in a single quarter.
The challenge
The firm's compliance operations covered 210 distinct workflows across onboarding, transaction monitoring, and reporting, automated where possible with single-purpose RPA bots. That approach had plateaued:
- Each bot broke whenever an underlying system's UI changed, requiring constant maintenance
- A new regulatory workflow meant building a new bot from scratch, with no shared logic between them
- Only 86 of 210 workflows (41%) were automatable under the existing bot architecture
- Exceptions were routed to analysts with no structured evidence, so triage started from zero every time
- Bots had no shared context — a decision made in one workflow wasn't available to the next
- Analyst review time per escalated case averaged 22 minutes, most of it spent gathering supporting documents
How it works
Agents that plan, gather evidence, and escalate only what genuinely needs a human
The redesign replaced fixed automation scripts with a coordinating mesh of purpose-built agents:
- 01
Mapped all 210 workflows into a planner-executor structure with distinct policy, evidence, and exception agent roles
- 02
Built a planner agent that decomposes each incoming compliance case into an ordered set of sub-tasks
- 03
Gave the policy agent retrieval access to current regulatory requirements and internal control policies
- 04
Built an evidence agent that gathers supporting documents and system records for each sub-task automatically
- 05
Configured the exception agent to escalate only cases it cannot resolve, packaged with a structured evidence bundle
- 06
Replaced brittle UI-based bot handoffs with a defined agent-to-agent protocol between systems
- 07
Rolled out in three phased waves, retiring legacy RPA bots as each workflow class moved to the agent mesh
What we built
Key capabilities
Adaptive workflow coverage
New workflows are configured through the planner-executor structure rather than requiring a new bot built from scratch.
Structured escalation
Analysts receive a packaged evidence bundle with every escalation instead of starting triage from zero.
Reduced automation maintenance
Agent-to-agent protocols replaced UI-dependent bots that broke on every system update.
Auditable agent decisions
Every agent action is logged against the policy it applied, giving compliance leadership a clear decision trail.
Before vs after
What changed in compliance operations
- Workflow coverage
- 41% (86/210) → 78% (164/210)
- Escalation quality
- Raw case → structured evidence bundle
- Analyst review time
- 22 min → 9 min per case
- New workflow onboarding
- New bot, weeks → agent config, days
Business impact
What it changed
Coverage nearly doubled in one quarter
Automated workflow coverage rose from 86 to 164 of 210 workflows (41% to 78%), without a corresponding increase in engineering headcount.
59% faster case review
Average analyst review time per escalated case fell from 22 to 9 minutes once evidence arrived pre-assembled.
Maintenance burden shifted off UI automation
Retiring UI-dependent bots removed the recurring break-fix cycle that had consumed a meaningful share of the automation team's time.
Technology stack
“The ceiling wasn't the regulation or the headcount — it was an automation architecture that couldn't share context between workflows. Agents that can removed the ceiling.”
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