ConceptNet
Voice intent classifier for enterprise AI agents
What it does
ConceptNet classifies enterprise voice commands into 4 intent layers — Basic, Context-Aware, Predictive, and Autonomous — producing structured JSON for agent execution. Token-free · 98.6% accuracy · 9 languages · No API cost · Open source Built for sales, legal, ops, and CS teams who want to automate repetitive workflows without paying $125K/year for GPT-4o. Try the live sandbox in 30 seconds — no login, no setup.
Low-cost SaaS is the stepping stone. Proprietary voice IP is the moat. Enterprises collect voice data, build IP across 4 intent layers, own it, and license it to others. We charge 10%. Features get copied in months. Proprietary IP lasts a decade. GPT-4o charges $0.08 per query. At 5,000 queries/day across an enterprise team, that's $146,000/year — just for classification. ConceptNet: $0.015 per query, token-free. Voice UI, integrations, workflow automation — competitors ship these in 3–6 months. Product features are not a moat. Proprietary voice data and IP stacking is. GPT-4o supports ~50 languages. Claude ~30. ConceptNet supports 200 via SONAR multilingual embeddings — the only enterprise…from conceptnet.co.uk
Does the same job
all alternatives →
More ai this month
the category →
I trained a 125M-parameter transformer to autocomplete piano performances in real time (~108 notes/sec on an iPhone 15). The idea is basically GitHub Copilot or Tabnine, except instead of prompting it with code, you prompt it by playing a few notes on a MIDI piano. The model then continues what you played, entirely on-device. The app is free if anyone wants to try it. Happy to answer questions about the model, training, Core ML, or the many things that didn't work.
AI · 16d ago · simedw.com
Astute▲585Automate your B2B brand going viral, with new media creators
AI · 18d ago · company-app.joinastute.com
Hey HN, Henry from Cactus here! We previously released Cactus Needle, a 14MB agentic LLM for tool call, device use, and structured extraction for phones, wearables, smart homes, small robots and microcontrollers. We got really great feedback here, and have now incorporated the suggestions to release Needle 2. The whole model is a single 14MB binary that runs a full session in 28MB of RAM; 45m parameters at 2bit compression. Needle hits 500 tokens/sec decode speed on a Raspberry Pi 5, sits between 400-1,500 tokens/sec on VR devices like Meta Quest 3S and Apple Vision Pro, and ranges…
AI · 26d ago · cactuscompute.com
Launched alongside, August 2026
the whole month →- TL
Life & fun · 10d ago · louisabraham.github.io
- SA
Hello HN! I found that picking out plausible but diverse skin tones for my digital art and game development projects was kind of difficult, and I got curious about if there was a way to define a color space that made it easy. I've built a color picker and procedural generation algorithm based on the space as well as a bunch of other fun js features and demos throughout the page that use the equations. If you find it interesting, I have lots of explanations of how I built it and what properties the space has. The methodology might be a bit shaky, but hopefully the result is as helpful for…
Life & fun · Aug 2026 · toneyalexander.github.io
I trained a 125M-parameter transformer to autocomplete piano performances in real time (~108 notes/sec on an iPhone 15). The idea is basically GitHub Copilot or Tabnine, except instead of prompting it with code, you prompt it by playing a few notes on a MIDI piano. The model then continues what you played, entirely on-device. The app is free if anyone wants to try it. Happy to answer questions about the model, training, Core ML, or the many things that didn't work.
AI · 16d ago · simedw.com