Bibrof AI – Bulk Image Background Remover Offline

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Bibrof AI – Bulk Image Background Remover Offline

Hi HN, I’d like to share BIBROF AI, an AI-powered background removal tool that runs entirely offline on your Windows PC. It removes backgrounds from images without any cloud servers - everything happens locally for privacy and speed. Use case: Ideal for developers, designers, or founders who need to batch-edit product photos, create marketing images, or just don’t want to send files to a third-party server. We built it after feeling uneasy uploading client images to random cloud services. Key features: Process up to 100 images at once, fairly accurate edge detection (does hair, fur, semi-transparent objects decently well), and it doesn’t require a GPU (runs fine on CPU). There’s no “credit” system or usage limit - one subscription and you can use it on unlimited images. Quality & speed: It always outputs the highest resolution results. In our tests it’s faster than waiting for many cloud API calls, since processing is local. Tech stack: Built on an MIT-licensed InSpyReNet model. We’re not open source (the UI code and packaging are proprietary), but we credit the open-source model. System requirements: Windows 10 or 11, at least 4GB RAM. Uses about ~1.5GB disk after install (includes the AI model). Pricing: Free 7-day trial (no credit card needed). After that, it’s paid: currently $23.88/year. No per-image fees. Try: https://bibrof.lislip.com/ Security note: The app is not code-signed yet. This means when you install, Windows SmartScreen might warn that the publisher is unknown. This is expected (EV certs are expensive for us right now). We plan to sign the binaries once we can afford it (targeting after first 100 sales). For now, users have to click “run anyway” on the SmartScreen dialog. We totally understand if that’s a dealbreaker for some - just want to be upfront about it. Why Show HN: We figured fellow developers might appreciate an alternative to cloud APIs for image processing. Also, dealing with an unsigned app and building an offline-first tool has been an adventure - I’m happy to answer questions about the tech or our journey. We launched very recently and are eager for feedback. Open to all questions. Happy to discuss trade-offs, accuracy, or why offline matters. Looking forward to your thoughts. Thanks HN!