Building a Clay Compliance Engine to Reduce Friction in Enterprise Teams
Building a Clay Compliance Engine to Reduce Friction in Enterprise Teams
When personalizing messages at scale, ensuring compliance with brand and legal guidelines can be tricky. This is how I built a simple compliance engine that plugs right into Clay!
At an early-stage startup, sending a personalized message based on pain points or triggers is pretty straightforward. Worst case, you annoy someone for a day.
At the enterprise level, that’s a different story. Every outbound message needs to pass through layers of brand and legal checks before it reaches anyone. The bigger the company, the tighter the tolerances.
Having worked at the largest creative agency in the world, I saw this problem up close. Marketing and brand teams would spend weeks going back and forth with legal, rewriting the same lines over and over. It slows GTM teams down and kills creativity.
My hunch is that this is exactly the friction enterprise Clay users deal with every day
The Idea
I love Clay. It makes it easy to personalize at scale and plug in whatever tools I want. I also heavily rely on Octave’s Clay integration for context-aware personalization.
So one weekend, I decided to build something fun: a compliance engine that fits into the Clay ecosystem.
In my head, it looked like this:
A simple interface to input your brand and legal guidelines
An API route that Clay can call automatically
Optional built-in regulatory settings (like HIPAA) for industries that need it
That was the plan. Nothing fancy. Just something that helps GTM teams move faster without stepping on legal landmines.
How It Works
Input your brand guidelines using the interface.
Create your personalized messages on Clay.
Call the application using the HTTP API on Clay.
Requests hit an evaluation endpoint with a message and context. The system normalizes inputs, retrieves relevant policies, and merges them into a unified rule set.
The application then checks for issues like forbidden terms, sensitive data, or prohibited claims using patterns and AI inference. Decisions are binary, with detailed reasoning.
For violations, the system attempts AI rewrites, validating them iteratively. All evaluations are logged for auditing and insights.
Clay marks the final output as “approved,” replacing non-compliant text with a compliant version if needed.
Tech Stack
Core Framework: A React-based full-stack platform for both frontend interfaces and backend APIs, emphasizing speed and scalability with built-in type safety.
Styling and UI: Utility-first CSS for rapid, responsive designs, paired with accessible component libraries for polished interfaces without custom code.
Database and Data Handling: A relational database with an ORM for easy modeling of workspaces, policies, and audit logs, supporting quick setup and queries.
AI Integration: OpenAI API for parsing guidelines and generating rewrites, chosen for its reliability and structured outputs.
Other Essentials: Authentication for user management, validation libraries for inputs, and icons for visual appeal. The stack prioritized simplicity, allowing focus on logic over boilerplate.
Key Features
Policy Parsing: Users input plain-text guidelines; AI converts them into enforceable rules, making setup accessible.
Interactive Testing: A dashboard lets users simulate evaluations, viewing decisions, issues, and suggested fixes in real-time.
Smart Rewrites: When problems are detected, AI generates compliant versions, refining them until they pass checks.
Regulatory Support: Built-in templates for common laws (e.g., privacy, health, finance), auto-selected by industry.
Audit Tracking: Every check is recorded, enabling teams to review patterns and improve over time.
Clay Integration
The entinre application was designed to plug into no-code sales platforms like Clay, acting as an automated gatekeeper during outreach campaigns. Simply generate a secure key per workspace, then configure an API call in the platform to send messages for review.
Takeaways
Being able to build something that plugs right into a GTM tool I rely on everyday is what I would call an awesome weekend! I’m not entirely sure if what I solved is a real problem, or whether my solution is what will work, but I typically build these to see what is possible and to get even more ideas out of them.
If you think this might be useful to you, or have any ideas for me, feel free to reach out!
Imagine you could just upload the job description of the position you’re applying for, and your resume; then an AI avatar interviews you live. I was able to vibecode this with minimal coding knowledge!
Vibecoding an authorized RAG chatbot with minimal coding experience, facing a critical security incident, and learning how to debug something I don’t quite understand.