Introducing TraceLogicAI: Compare AI Architectures with Evidence

Hello, Product Hunt community! 👋

I’m Malik Dixon, a U.S. Army veteran and technology professional with more than 25 years of experience across full-stack development, AWS, DevOps, DevSecOps, UX, and AI systems.

I’m excited to introduce TraceLogicAI, a platform I built to answer a practical question:

Which AI architecture is actually right for the job?

TraceLogicAI runs the same task through five different pipelines—Plain, RAG, MCP, Agent, and Security-aware—and lets you compare their citations, retrievals, tool calls, latency, cost, groundedness, and safety signals.

The goal isn’t to prove that one architecture is always superior. It’s to help developers and teams avoid unnecessary complexity and make better decisions using measurable evidence rather than trends or assumptions.

TraceLogicAI is currently bootstrapped, live, and free to explore while I validate the product and learn from early users.

I’d appreciate your feedback:

• Which architecture comparisons would be most useful to you?

• What additional evaluation metrics should I include?

• Where could you see TraceLogicAI fitting into your workflow?

Try it here: tracelogicai.com

I look forward to learning from the Product Hunt community and sharing the journey as TraceLogicAI evolves.