Alternatives
Products that do what Origin Detector (OD) does
Community based consumer awareness platform
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2015 · openhunt.co
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Hey HN, I’m Henry, cofounder and CTO at Span (https://span.app/). Today we’re launching AI Code Detector, an AI code detection tool you can try in your browser. The explosion of AI generated code has created some weird problems for engineering orgs. Tools like Cursor and Copilot are used by virtually every org on the planet – but each codegen tool has its own idiosyncratic way of reporting usage. Some don’t report usage at all. Our view is that token spend will start competing with payroll spend as AI becomes more deeply ingrained in how we build software, so understanding how…
Sep 2025 · code-detector.ai
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Hey HN! My name is Christian, and I’m the co-founder of https://frigade.ai. We’ve built an AI agent that automatically learns how to use any web-based product, and in turn guides users directly in the UI, automatically generates documentation, and even takes actions on a user’s behalf. Think of it as Clippy from the old MS Office. But on steroids. And actually helpful. You can see the agent and tool-calling SDK in action here: https://www.youtube.com/watch?v=UPe0t3A1Vpg How is this different from other AI customer support products? Most AI "copilots" are really just…
2025 · frigade.ai
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Hey HN, We're building Invoice Detector (https://invoicedetector.com/), a tool that uses LLMs and computer vision to automate invoice collection for startups. Our AI agents automatically extract, process, and categorize invoices, helping startups stay on top of their expenses. In addition to extracting invoices, we send smart spend optimization notifications and generate easy-to-understand, accurate expense reports. Our pricing is transparent and available on our website. You can try our tool for free without a credit card. We're really interested in any feedback you have, as…
2024 · invoicedetector.com
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Hi HN, we're Kiran and Vijay! Over the past two years, we have built a columnar storage engine for observability: logs, metrics, and traces. Today, it's exciting for us to show what we've built on top of that foundation: LLM Agent Observability. Given how non-deterministic agents are, storing all traces without sampling was critical for us. But these traces tend to be in the MBs, sometimes GBs - we needed to store them inexpensively. We also needed the queries and analyses to be fast. To meet both these goals, we store them in S3 in our own parquet-like file format, and query them using AWS…
Jul 2026 · oodle.ai
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2025 · scamchecknow.com
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