# Enki – memory for AI agents that keeps ~half as much and answers as well > Source: > Published: 2026-06-27 23:35:47+00:00 Enki is a memory engine for LLM agents. **This repository publishes evaluation results only** — the engine is closed-source. No configuration, internals, or methodology beyond what is described below is included here. Both systems ingest **identical** conversation histories from LongMemEval-S. Each system's retrieved memories are answered by the **same** model (Claude Haiku) and graded by the **same** LLM-as-judge, at equal retrieval depth (K=10). The only variable is the memory layer. **Validated slice: 25 instances** (full-benchmark run in progress). | Question type | Enki | mem0 | |---|---|---| | Multi-session reasoning | 4 / 5 | 2 / 5 | | Knowledge update | 3 / 5 | 3 / 5 | | Single-session (user) | 3 / 5 | 3 / 5 | | Single-session (assistant) | 2 / 5 | 2 / 5 | | Single-session (preference) | 2 / 5 | 2 / 5 | Total | 14 / 25 | 12 / 25 | **Storage:** Enki answers from**0.49× the stored facts** mem0 keeps on the same conversations (mean 138 vs 283).**Standout:** multi-session reasoning (4/5 vs 2/5). Honest framing.This is a small, hand-validated slice; the overall margin (14 vs 12) is modest and within what a 25-item sample can show. The robust, repeatable result iscomparable answer accuracy at roughly half the memory footprint, with a clear multi-session advantage. Further evaluation is ongoing. Measured on a ~139-fact store, CPU-only (no GPU), 240 samples: | Percentile | Latency (ms) | |---|---| | mean | 7.6 | | p50 | 6.1 | | p95 | 11.9 | | p99 | 13.0 | Full methodology and per-question results are available on request. *Enki Labs (UK) · 2026*