Project Case Study

Automating Risk & Regulatory Compliance

We built ComplyGuard AI, an intelligent agent that parses regulatory documents, checks operational workflows against ISO/GDPR standards, and prevents violations before they happen.

View Results Tech Stack

Live Scan: Policy_GDPR_v2.pdf ● Active

Lexical Analysis 100%

Rule Mapping (ISO 27001) 84%

Critical Risk Detected

Missing data retention clause in Section 4.2

The Regulatory Tsunami

Organizations must navigate an evolving landscape ranging from GDPR and HIPAA to SEBI and ISO standards. Our client, a multinational financial services firm, faced critical bottlenecks.

Volume & Velocity

50+ new regulations introduced annually. The legal team was physically unable to review 15,000+ active contracts manually.

Audit Failures

Human error in "Ctrl+F" keyword searches led to missed context-dependent risks, resulting in a 12% audit failure rate.

Siloed Operations

Policy updates didn't reach operational teams in time, creating a gap between "Rule" and "Reality."

The Agent Architecture

We moved beyond simple keyword matching to a Semantic Understanding Engine.

1. Ingestion

PDFs, SOPs, Emails, and API streams.

2. Logic Engine

NLP maps text to regulations (e.g., GDPR Art. 5).

3. Action

Risk Alerts, Dashboards, and Reports.

Under the Hood: Dynamic Rules

The core advantage is the Dynamic Rule Engine. Unlike static software, the agent receives regulatory updates (via RSS/API) and automatically re-scans existing documents for new compliance gaps.

It calculates a Confidence Score for every document. Low scores trigger human review loops.

Technologies Deployed:

Python LangChain Tesseract OCR Vector DB (Pinecone) FastAPI

class ComplianceAgent: def validate_document(self, doc_text): for rule in self.active_rules: match = self.nlp.check(doc_text, rule) if match.confidence < 0.8: self.alert_manager.send({ "risk_level": "HIGH", "gap": rule.description }) return generate_report()

The Shift: Reactive vs. Proactive

Process	Old Way (Manual)	New Way (AI Agent)
Document Review	Manual reading (3-4 hours per doc).	Instant scanning (3 seconds per doc).
Updates	Quarterly reviews of new laws.	Real-time ingestion of regulations.
Scalability	Linear (hire more lawyers).	Infinite (cloud-based scaling).
Accuracy	Inconsistent (Fatigue prone).	Standardized (Rule-based).

The Transformational Impact

Enhancing audit preparedness and ensuring continuous regulatory alignment.

0 % Documents Digitized

0 % Audit Cost Reduction

0 Audit Failures (Q4)