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Speechmatics - API for Voice AI Agents
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Enterprise-grade open-source AI inference at unlimited scale.Open
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Trust scores, cryptographic proof, and risk assessment for AI agents.Open
Alex Garden🛠️ 1 toolFeb 24, 2026@MnemomWe built Mnemom because we were shipping AI agents into production and couldn't answer a basic question: how do you prove this thing is doing what you told it to? Not monitor. Prove. So we built the proof layer. Cryptographic attestations, trust scores, risk assessment, containment — everything you need to deploy agents you can actually stand behind. It's free to start and open source. We'd love to hear what you think - new features shipping daily. -
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I have seen it on Reddit, surprisingly, it did help me to save 30% in input/output agent tokens, not 60% unfortunately, but for sure better than not using it. Saved way more than I spent on subscription, shame didnt know of 50% discount :)
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Brilliant system and feels fairly easy to use, one issue with sign in took me 5 mins, but i think its fixed now? Not perfect, but a step in the correct direction!
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- SponsorSpeechmatics - API for Voice AI Agents
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Similarity search works okay, but UX could be improved — it's hard to tell when a search was completed. Also there are some minor mistakes in BPM assignation. But overall works as expected and helps finding similar tracks.
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Extremely excited about this project and all the possibilities that follow!
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Claude — v5.0Claude Fable 5 State-of-the-art on Cognition's FrontierCode eval, scoring highest among frontier models even at medium effort. More token-efficient than prior Claude models. Stripe reported a codebase-wide migration on a 50M-line Ruby codebase done in a day, versus an estimated two-plus months by hand. Highest score of any model on Hebbia's Finance Benchmark (senior-level reasoning), with major gains in document reasoning, chart and table interpretation, and problem solving. IMC reported near-across-the-board top results on trading-analysis evals (factual lookup, conceptual reasoning, root-cause analysis, expected-value analysis). New state-of-the-art for vision tasks. Extracts precise numbers from scientific figures and can rebuild a web app's source code from screenshots alone. Needs less scaffolding: beat Pokémon FireRed with a minimal vision-only harness, where earlier models needed complex helper harnesses. Stays focused across millions of tokens on long-running tasks and improves its outputs using its own notes. With persistent file-based memory in Slay the Spire, performance improved 3x more than Opus 4.8, and it reached the final act 3x more often. Works autonomously for longer than any prior Claude model
