Show HN: AceIQ360 – First AI memory system to achieve 100% on LongMemEval

[maheshvaikri99]

I built AceIQ360, a deterministic agentic memory system.

Results: - LongMemEval: 100% (500/500) - first ever - LoCoMo: 75.32% J-Score (vs Mem0 68.44%) - 80x cheaper per turn - 13x faster

Built on RudraDB, my relationship-aware vector database with automatic relationship detection.

No LLM extraction calls. Pure embedding-based.

Solo developer. Looking for feedback.

[maheshvaikri99]

Full raw benchmark logs published: https://github.com/AceIQ360/AceIQ360-Benchmark

Unlike others who only share top-line numbers, I published every question, answer, and judgment. You can verify the 100% claim yourself.

[bucket31]

Great claims. Where is the code to check them at?

[maheshvaikri99]

Hi Thanks

Benchmark results and methodology here: https://github.com/AceIQ360/AceIQ360-Benchmark

The full system isn't open source yet - still deciding on licensing. But the benchmark repo has: - Complete results (500/500 on LongMemEval) - Raw logs showing each question/answer - Comparison with baselines

Happy to answer questions about the approach. The core insight: intelligent context organization beats raw context volume. No LLM calls for memory extraction - pure embedding-based retrieval using RudraDB (https://rudradb.com).

If you want to verify independently, I can provide API access.