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Restore, colorize, scan and organize old family photos with privacy-first AI. Web, iOS and Android; free previews, multilingual guides and genealogy tools.
JavaScript is a lightweight, interpreted programming language.

Website, pricing, platforms and company facts side by side.
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JST
JavaScript Tutorial
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| Website | recolorthepast.com | appcreator24.com |
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| Company | Startup from Latvia · 1 - 9 employees · 2026 | — |
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In their own words, as submitted to SaaSHub.

Recolor the Past helps families digitise and revive old photographs without losing sight of the original. Scan printed photos with the mobile camera scanner or upload existing files, organise them into folders, and compare restoration previews before exporting. AI tools can colourise...
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As answered by people managing Recolor the Past and JavaScript Tutorial.
Recolor the Past's answer
Recolor the Past is an early-stage consumer product and does not publish or claim named major customers. It is designed primarily for individuals and families preserving their own photo archives rather than enterprise reference accounts.
Recolor the Past's answer
Recolor the Past combines photo capture, preservation and restoration in one privacy-focused workflow. Users can scan a printed photograph with the mobile app or upload an existing file, keep the untouched original separate, and compare it with every restored version. The service can colorize black-and-white images, revive faded colour, repair scratches, reduce blur and improve faces. A free watermarked preview lets people test the result before ordering a full-resolution export. Processing is hosted in the EU, photographs are never used for AI training, and temporary files are automatically deleted according to a defined retention policy. The web, iOS and Android apps are localized for 24 European languages.
Recolor the Past's answer
The web application is built with Next.js, React and TypeScript, with Tailwind CSS for the interface and next-intl for localization. The iOS and Android apps share a Flutter and Dart codebase with native camera and scanning integrations. Image-processing services are implemented in Go and use ONNX Runtime-based models and supporting image-processing tools. The service uses EU-hosted infrastructure, short-lived download links and automatic retention cleanup. Monitoring and error reporting are designed to avoid using customer photographs for model training.
Recolor the Past's answer
Choose Recolor the Past when you want more than a one-click filter. It provides a complete path from scanning or uploading a family photograph to comparing restoration previews and keeping results organized. The original is preserved separately, and users can test a free watermarked preview before paying for a full-resolution export. It is particularly suitable for people who value EU-hosted processing, clear deletion rules and a promise that their family photographs will not be used for AI training. It also works across the web, iOS and Android and supports 24 European languages.
Recolor the Past's answer
The primary audience is individuals and families preserving personal photo collections: family historians, genealogy enthusiasts, people digitizing inherited albums, and anyone preparing old photographs for relatives, memorials or family archives. The mobile scanning workflow also helps people who have printed photographs but no dedicated scanner. Recolor the Past is designed to be approachable for non-technical users while still giving careful users control over crop, perspective and restoration choices.
Recolor the Past's answer
Recolor the Past started from a simple observation: family photographs are irreplaceable records, yet preserving them often requires a scanner app, a separate restoration tool and another place to organise the results. Many AI image services also provide little clarity about storage, training use or deletion. The project was built to bring capture, preservation and restoration into one understandable workflow. The original stays separate, previews make experimentation low-risk, and privacy decisions are explained directly instead of hidden behind generic AI claims.
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