Automating SEC Filings with AI: A Compliance Engine

Overview
Compliance Requirements
Task & Workflow - Gap Analysis
Task & Workflow - Key Findings
Task & Workflow - Regulatory Requirements
Task & Workflow - Task Management
Report and Audit

Inspiration

Filing with the SEC is not fun. The Securities Exchange Act of 1934 and forms like the 10-K are massive, repetitive, and full of legal jargon. Companies spend weeks pulling data from different departments, lawyers spend hours making sure every line is correct, and still, small errors can slip through.

We thought: what if AI could handle the heavy lifting? What if legal text could be turned into something structured and actionable, like a to-do list, that compliance staff and auditors could trust? That’s what sparked this project.

What We Learned

How to use LegalBERT to break down dense legal documents into structured data
That clustering and harmonization can make messy, repetitive requirements easier to understand
Generative AI can make legal obligations sound clearer and less intimidating
Human oversight is critical, because automation without humans isn’t trusted in compliance
Building for on-prem deployment adds extra constraints but makes the tool more realistic for real companies

How We Built It

Parsing Legal Text – Used LegalBERT to turn filings into machine-readable JSON
Clustering – Grouped similar filing requirements so they’re not scattered across the document
Harmonization – Removed repetitive items while keeping the meaning intact
NLP Enrichment – Applied GenAI to give clusters clear titles and short descriptions
Synthetic Data – Created a dummy company with realistic data to simulate how it would work in practice
FastAPI Backend – Built a dashboard that shows compliance status, a score, and a to-do list of requirements
Human-in-the-Loop – Enabled compliance staff to step in and adjust anything the AI gets wrong
Auditor Review – Ensured outputs are cross-checked by auditors before they reach executives, making it more reliable

Challenges We Faced

Scope creep: We wanted to cover the whole Act of 1934, but had to narrow it to SEC filings for this version
Redundancy in law: Legal text repeats itself in different ways, and cleaning it up without losing meaning was tough
Performance: Running LegalBERT and clustering on big filings required significant processing power
Balance: Too much automation makes people nervous, too little automation defeats the purpose — we had to get the mix right
Trust: Adding human oversight and auditor review wasn’t just a nice to have, it was necessary for this to feel real and reliable

Conclusion

We built a compliance engine that turns long, complicated SEC filings into a clear, actionable to-do list. It’s powered by AI for speed and clarity, but grounded with human oversight and auditor checks for trust.

This version works as a demo on filings like the 10-K, but the architecture is scalable to the entire Act of 1934 and beyond. In the future, we see it growing into a full compliance platform with role-based access control (RBAC), enterprise integrations, and real-time monitoring.

Challenges we ran into

Accomplishments that we're proud of

We successfully turned dense legal filings into structured, machine-readable data using AI
Built a working compliance engine that outputs a dynamic to-do list instead of a static checklist
Balanced automation with human-in-the-loop oversight and auditor validation to make the system trustworthy
Simulated a real company’s filing process using synthetic data, showing how this could work in practice
Designed the solution for on-prem deployment, addressing real-world concerns about sensitive company data
Scoped down from the entire Act of 1934 to SEC filings, and still delivered a meaningful proof of concept under time and resource limits

What we learned

Legal text is far more repetitive and redundant than we realized, and clustering/harmonization is critical
Generative AI can simplify complex legal requirements and make them understandable to non-lawyers
Human oversight is not optional in compliance — people need to trust the output, not just see it
Deploying on-premises introduces unique challenges, but it makes the solution more realistic for adoption
Sometimes the hardest part is not the tech, but deciding what scope is achievable in the time we had
Collaboration between legal, technical, and compliance thinking was key to building something usable

What's next for Automating SEC Filings with AI: A Compliance Engine

This project started with SEC filings as a proof of concept, but the vision is much bigger. In the future, we see this evolving into a full-scale compliance platform with features such as:

Full Act Coverage: Expanding from specific filings to the entire Securities Exchange Act of 1934 and related amendments
Multiple Frameworks: Adding support for other regulatory frameworks and jurisdictions beyond the SEC
Enterprise Integrations: Connecting directly with company systems so data flows automatically from finance, HR, and operations
Role-Based Access Control (RBAC): Ensuring executives, auditors, and staff have role-specific access and permissions
Real-Time Monitoring: Continuously tracking changes in laws and filings so compliance status updates instantly
Insurability Scoring: Using compliance data to help organizations evaluate and improve their cyber and financial risk posture

Our long-term goal is to create not just a filing assistant, but a live compliance engine that companies can trust for accuracy, oversight, and accountability.