Custom reviewer tuned to your specific regs — SOC 2, HIPAA, FINRA, GDPR, EU AI Act. Every flag includes the exact section and the verbatim rule. Slack or Asana, results in minutes.
- Analyze
- Automate
- Monitor
monthly retainer
Who this is for
Compliance, legal, or risk lead at a regulated mid-market company where marketing, product, and customer communications need review against multiple regulation sets on a fast cadence. Your team is the bottleneck — manual review takes hours, audit documentation lives in email threads, and new laws keep adding to the checklist.
The pain today
- Compliance review holding up 2–5 product or marketing releases every week
- Manual cross-reference of marketing copy against regulations taking 3–5 hours per review cycle
- EU AI Act, state privacy laws, and amended guidance not yet in anyone's checklist
- Late-cycle reviewer fatigue causing misses that surface in audits, not reviews
- Audit evidence assembled by hand from email and Slack threads the night before
The outcome you get
- AI pre-review flags potential issues before the compliance officer even opens the doc
- Every flag cites the specific regulation section and verbatim rule — human verifies, not decodes
- Slack or Asana workflow: submit content, get AI analysis in minutes, not days
- Structured audit trail: content, AI analysis with citations, human decisions, final version — queryable on demand
- Regulation corpus updated on a defined schedule so new laws actually land in the review
Regulation corpus: what the AI actually knows
An AI compliance review assistant is only as reliable as the regulations it was trained on. Generic models have no idea what your current SOC 2 controls say, which FINRA rules apply to your product category, or that the EU AI Act's Article 50 transparency obligations took full effect in August 2026 with fines up to €15 million.
I build a custom regulation corpus for your specific situation. That means ingesting your active regulation set — SOC 2 controls, HIPAA Privacy and Security Rules, FINRA rules, GDPR articles, CCPA, state privacy laws, FDA guidance, FTC rules, EU AI Act provisions — tagged by section, jurisdiction, and effective date. If your industry has its own guidance (PCI-DSS, FCA, APAC local regulators), that gets added too.
When content comes in for review, the relevant sections are retrieved based on content category: marketing claim, data handling disclosure, customer communication, AI-generated content disclosure. The AI generates analysis citing specific sections. It does not work from vague pattern memory — it pulls the actual text.
The corpus is yours to own and update. I wire scheduled re-ingestion pipelines from official sources and build tooling so your compliance team can add amendments without touching code.
AI pre-review flags potential issues before the compliance officer even opens the doc
Citations, not verdicts
Compliance decisions require explanation. A flag that says "potential violation" without a source is not useful — it just adds noise to an already-pressured review cycle.
Every AI flag in this system includes: the specific regulation section cited, the verbatim text of the rule, the exact language in the submitted content that triggered the flag, a severity rating (high, medium, or low), and suggested remediation language. The human reviewer reads the citation, applies judgment, and either accepts or overrides with a written rationale.
Overrides matter. When a reviewer overrides an AI flag — with justification — that decision feeds back into prompt refinement. The system gets more calibrated over time, not just more flagged.
For auditors, the record shows both what the AI found and what a human decided. That distinction holds up in a SOC 2 audit or HIPAA review far better than a black-box approval stamp.
40+: Payment providers integrated.
Workflow: where content lives, that is where the review happens
Nobody sends content to a separate compliance portal. That is why these systems get abandoned. I integrate the review into the tools the team already uses.
Slack: a compliance channel with a slash command. Marketing submits content, gets AI analysis threaded in the same channel within 5–10 minutes for standard copy, 30–60 minutes for complex disclosures.
Asana or Jira: a ticket tagged for compliance review triggers the AI analysis as a task comment. The compliance officer reviews, decides, and closes the task. The audit trail lives in the project management tool your team already audits.
For marketing automation (Marketo, HubSpot): an API endpoint that requests review before campaigns launch. Content that has not cleared compliance cannot be scheduled. The gate is automatic, not a courtesy reminder.
Turnaround targets are set at build time based on your content volume and review SLAs — I do not wire a system that creates a new bottleneck.
At bolttech, compliance was not optional
At bolttech — a $1B+ unicorn operating across 15+ international markets with 40+ payment providers integrated — every customer-facing communication touched multiple regulatory environments simultaneously: EU PSD2, UK FCA, APAC local regulators. There was no margin for a compliance miss.
Working at that scale taught me what compliance infrastructure actually needs to do: produce consistent, documentable decisions at volume without degrading quality when the pace of releases accelerates. That discipline — corpus grounding, citation discipline, audit-trail-first design — is exactly what I bring to a custom AI compliance review assistant.
The patterns transfer directly to any regulated mid-market environment. You do not need unicorn infrastructure. You need the same thinking, right-sized.
What AI handles and what it does not
I build this with explicit limits because the limits are what make it trustworthy.
AI handles: identifying patterns associated with regulatory violations, retrieving the relevant regulation sections for a content category, flagging specific language that appears to make regulated claims, and suggesting remediation based on what has passed review before.
AI does not: provide legal advice, certify content as compliant, replace compliance officer judgment, or make final decisions on anything. Every AI output is analysis for a human reviewer. For high-stakes content — clinical claims, investment return language in FINRA contexts, AI-generated content subject to EU AI Act Article 50 — the AI adds efficiency to the human review process. It does not replace it.
I write these limits into the interface itself. Every output carries a visible disclaimer so no one uses the tool beyond its intended scope.
Pricing and timeline
AI compliance review fits the AI Automation retainer at $3,999/mo. The first-version timeline is 6–8 weeks: regulation corpus ingested and indexed, analysis prompts tuned to your content types, workflow integrated into Slack or your project management tool of choice.
The retainer continues through regulation updates (new laws, amendments, changing enforcement guidance), prompt refinement as overrides accumulate, and scope expansion as new content types or regulations are added.
14-day money-back guarantee, cancel anytime, Work Made for Hire — the code and corpus are yours on day one. LLM API costs typically run $500–3,000/mo depending on review volume, billed separately at cost.
Recent proof
A comparable engagement, delivered and documented.
Unified payment orchestration across Asia and Europe
Delivered the payment orchestration platform at bolttech, a $1B+ unicorn, with 40+ integrations across multiple regions.
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Frequently asked questions
The questions prospects ask before they book.
No — it makes them faster. AI handles the initial retrieval and pattern analysis; the compliance officer reads the citations, applies judgment, and decides. Time savings on routine marketing copy reviews typically run 50–70%. The officer's role shifts from manually cross-referencing regulations to verifying AI analysis. Complex or novel content still requires the same depth of review — just with better supporting material.
The regulation corpus is refreshed on a defined schedule: quarterly for stable regulations, monthly for actively evolving ones, and immediately for major changes like new laws or significant amendments. Before any update affects live reviews, your compliance team reviews the corpus change. I wire the update pipelines; your team gates what goes live. The goal is that a regulation change is reflected in the review tool within days, not quarters.
Anything with a documented rule set. Common examples: SOC 2, HIPAA, GDPR, CCPA, FINRA, PCI-DSS, FDA guidance, FTC rules, EU AI Act, state privacy laws. Industry-specific regulations in insurance, pharma, and fintech are scoped per your active compliance obligations. Well-documented regulations with clearly structured provisions work best. Vague or frequently-amended guidance is harder — I will be direct about that in scoping.
EU AI Act Article 50 transparency obligations took full effect in August 2026, covering disclosure and watermarking of AI-generated content. The compliance corpus includes the relevant Act provisions, the GPAI Code of Practice, and content-category rules so your marketing team's AI-generated copy gets flagged for disclosure requirements before it publishes. Fines reach €15 million or 3% of global turnover — this is not a regulation to catch up on after the fact.
The human reviewer overrides with a written justification. That override is logged — content, AI flag, regulation cited, reviewer's rationale, final decision. Over time, override patterns feed back into prompt refinement to reduce false positives in that content category. The system is designed to get better from the compliance team's expertise, not just from my tuning. A wrong flag caught and documented is far less risky than a miss that surfaces in an audit.
Marketing teams can run pre-checks before sending to compliance — a first-pass scan to catch obvious issues before the formal review cycle. This reduces back-and-forth between marketing and compliance and shortens release cycles. The compliance officer still makes the final call; the pre-check reduces the volume of low-quality submissions that reach their queue.
Every review preserves: the content submitted, the AI analysis with regulation citations, any overrides with reviewer rationale, and the final approved version. The trail is queryable by date, content type, reviewer, and regulation. Audit reports generate on demand for a SOC 2 review period or HIPAA compliance assessment. Auditors see both AI and human work, which holds up far better than a single approval timestamp with no supporting documentation.