What compliance automation consulting actually means
The phrase gets used loosely. Some vendors sell it as a SaaS subscription. Some firms sell it as a strategy deck. What actually moves the needle is someone who can map your specific compliance workflow (a KYC review queue, a trade reconciliation cycle, a monthly attestation process) and replace the manual bottleneck with a working automated system.
That means understanding the regulatory requirement well enough to know which parts require genuine human judgment and which parts are just pattern-matching: tasks a well-designed AI agent can handle faster, more consistently, and with a full audit trail.
Where I help
I am an AI automation specialist based in Miami with hands-on experience across compliance-adjacent workflows in financial services. Specific areas include:
- Regulatory reconciliation Automating the match-and-exception workflow between source data and regulatory reports, so analysts spend time on real breaks, not cleaning spreadsheets.
- Document review and extraction Building pipelines that read regulatory filings, policy documents, and onboarding packets, extract the relevant fields, and flag items that need a human decision.
- AML and fraud alert triage Designing multi-step review queues where AI handles first-pass triage on alerts, assembles a structured case summary, and routes to the appropriate analyst with context already prepared.
- Compliance reporting and attestation Replacing manual data collection with automated pulls from source systems, reducing the time from data freeze to final report submission.
The common thread: I build with Claude-based AI agents and connect them to your actual data. Not a demo environment. Not a proof of concept that lives in a sandbox. A workflow your team can run on Monday morning.
How an engagement works
Most engagements start with a scoped discovery call. I want to understand the specific process: what triggers it, what data it touches, where the human time goes today, and what "done correctly" looks like from a regulatory standpoint.
From there, I scope an initial proof of concept, typically deliverable in four to six weeks, targeted at the highest-friction step in the workflow. If it works (and it typically does), we extend. If it surfaces a constraint we did not anticipate, you have spent a small engagement finding that out, not a six-month implementation.
I work on a project basis with Miami-based clients and remotely. No retainer lock-in to start.
Why this approach is different
Most compliance technology projects fail not because the tool is wrong but because the implementation is wrong. The system does not know your naming conventions, your exception logic, or the regulatory carve-outs your legal team negotiated two years ago.
I sit between the AI capability and the compliance requirement, making sure the automation reflects how your process actually works, not how a vendor demo assumes it works. That translation layer is where most of the value lives, and it is almost never included in a platform subscription.