Oppora AI
Find Leads, Run Outreach, and Book Meetings on Autopilot
What it does
Oppora is an AI sales system that turns your ICP into a self-running outbound workflow. Find and enrich decision-makers, score leads, personalize email and LinkedIn outreach, protect deliverability, handle replies, book meetings, and sync qualified opportunities to your CRM. Instead of stitching together databases, enrichment, sending, warm-up, inbox, and CRM tools, build one workflow once and let Oppora keep it running.
Automate outreach with Oppora's Outbound AI sales agent. Build end-to-end workflows like n8n to find leads, send emails, auto-reply, and book meetings hands free.
Oppora's Claude MCP is Live. Connect our Email Database & Outreach features with any tool to build smart automations inside Claude. Start for Free Just tell what you sell and who you want to reach and our AI Sales Agent will find leads, send emails, reply from your inbox and sync meetings to your CRM automatically. Tell us what you sell and our AI will find leads, send emails, and book meetings for you. From cold company to closed deal. Oppora is built to run your outreach hands-free or hands-on. Apollo for leads. Instantly for sending. Smartlead for warmup. ZoomInfo for data. Four logins, broken syncs, four bills. Or — one Oppora. Most tools give you "AI," but you still have to prompt it…from oppora.ai
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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
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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…
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Launched alongside, August 2026
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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