Employees widely use unapproved AI tools to boost efficiency, reflecting how fast-paced adoption exposes underlying workplace environments and device hygiene…
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I've been building a memory/context layer called BrainAPI for a while now, and we just landed on top of the two benchmarks we've run so far. I want to talk about it, but honestly the numbers are the least interesting thing here. The part I keep thinking about is how fast it happened , and what that says about where the actual bottleneck in this field is. First, the boring facts so nobody thinks I'm hiding the ball: LoCoMo : BrainAPI 95.39%, Mem0 92.5%, Zep 80.32%, Letta 74% BEAM1M : BrainAPI 78.97%, Mem0 64.1%. Zep and Letta haven't published here. That's it. Two benchmarks. I'm not going to pretend that's a complete picture. LoCoMo is fairly saturated at this point and it leans on an LLM judge, so a couple of points at the top is not the same as a couple of points in the middle. BEAM1M is
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