xmemory

@xmemory_ai

The memory layer for AI workflows, built for precision, reliability, observability, and governance.

xmemory.ai

Joined March 2026

2 Following

20 Followers

Replies Reposts Media

xmemory
@xmemory_ai
Oct 22
Agents should get better with experience. We teamed up with @tolokaAI to measure that. Toloka evaluated xmemory on closed datasets. No peeking at the data. No tuning to the benchmark. Just learning from failures and measuring what improves. 📈 The results: 26% lower token costs
2
xmemory
@xmemory_ai
Sep 24
The right model for the right step. That’s how we build memory at xmemory – benchmarking for quality, cost, and latency. We tested @typesafeai's Jev as a judge of extracted data. It recovered 81% of the accuracy gap between a fast and a slow extractor while sending only 38% of
2
xmemory
@xmemory_ai
Sep 18
We’re excited to announce @xmemory_ai’s partnership with @temporalio! We have deep respect for Temporal’s leadership in reliable workflow execution, and we’re glad to work closely together as developers build the next generation of long-running agents and agentic teams. The
1
xmemory
@xmemory_ai
Jun 10
Agentic memory harness is more difficult than harness for coding agents. There is no quick self-correcting loop, and unlike with coding tasks mistakes accumulate and multiply. At #xmemory we are solving this once and for all.
Dima
@UniqueDima
Jun 10
SOTA model, 𝘦𝘹𝘱𝘦𝘤𝘵𝘢𝘵𝘪𝘰𝘯𝘴: too dangerous to release SOTA model, 𝘳𝘦𝘢𝘭𝘪𝘵𝘺: doesn't speak 𝚐𝚒𝚝 #Claude #Fable
xmemory
@xmemory_ai
May 7
66.88%. 80.1%. 85%. 90.79%. 93%. 100%. These are all SOTA scores on agentic memory benchmarks. None of them tell you whether the system will work in production. The deeper problem isn't the data — it's that we often misunderstand what these numbers actually measure. In our
1

xmemory

xmemory’s posts