Inspiration
Manual lead intake, API payload drift, and repetitive workflow routing create persistent operational bottlenecks that increase processing time and error rates. We wanted to build an autonomous, agentic pipeline that handles the process end-to-end.
What it does
The Unified Intelligence Pipeline ingests inbound requests, enforces strict schema validation, orchestrates multi-agent workflows, and generates dynamic dispatches and telemetry reports seamlessly.
How we built it
Built using a low-code architecture centered around Relevance AI for agent workflows, integrated with GitHub for version control, and deployed with frontend interfaces on Netlify.
Challenges we ran into
Ensuring low-latency asynchronous execution across multiple agent nodes while maintaining strict schema integrity and preventing payload drift.
Accomplishments that we're proud of
Successfully deploying a fully automated, end-to-end execution loop that eliminates manual data entry and speeds up request processing.
What we learned
Mastering low-code multi-agent orchestration patterns to build production-grade automated pipelines rapidly.
What's next
Expanding the integration layer to support additional real-time data sinks and multi-channel notification routing.
