What if 100 agents could optimize your code simultaneously in isolated production environments without copying data?

ParallelProof revolutionizes code optimization by deploying 100 AI agents simultaneously to test different strategies in isolated production environments, reducing optimization time from hours to just 3 minutes. Using Tiger Data's Agentic Postgres with zero-copy database forks, each agent tests a unique approach—from indexing to caching to algorithmic improvements—without duplicating storage or risking production data. The system achieves 100-200× faster testing with 90% storage reduction and 85% success rates compared to traditional sequential methods.