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Archaeology & Heritage Technology

ArchNova: Rediscovering the Field of Archaeology with AI-Powered Artifact Discovery

See how Rev9 Solutions built ArchNova, an offline-first mobile app for digitization of archaeologists in the field.

2026

OVERVIEW

ArchNova

ArchNova is a pioneering project built to modernize archaeological fieldwork, turning manual, paper-based site work into a smart, portable, AI-powered mobile solution. Archaeologists often work at sites with limited or no electricity and internet access. Rev9 built a mobile application that brings AI, 3D modeling, OCR digitization, and offline-first architecture together in one tool, so fieldwork keeps moving with or without a signal.

CHALLENGE

AI accuracy challenges: Object detection needed a very high bar of accuracy, reached through extensive model training and modern techniques like Gaussian Splitting. 3D model perfection: Building a smooth, lightweight, accurate 3D model efficient enough for professional use, yet optimized to run on a mobile phone. Offline complexities: Remote sites meant scanning and storing data with no connectivity, complex caching, background sync, and unstructured data handling in MongoDB. Tech stack issues: Multiple stacks and AI models, Flutter, Laravel, YOLO, Qwen 2.5, and PyTorch, all had to work together under one umbrella without breaking performance.

SOLUTION

Rev9 built ArchNova across six phases, each solving a real problem archaeologists face in the field. Flutter powered the frontend while YOLO-based models brought real-time artifact detection to a mobile camera, with heavy AI processing split across multiple threads to keep the app fast and stable. Gaussian Splitting, TensorFlow, and PyTorch reconstruct full 3D artifact models from a simple 70 to 80 photo series, with segmentation and a TF Lite conversion keeping the models sharp and light enough to run on a phone. Molmo and Qwen VL 2.5 generate editable historical context and classification for every discovered artifact, while AWS OCR digitizes handwritten field forms with automatic duplicate-entry prevention. A site mapping feature tags artifacts by exact excavation location, offline support covers nearly every feature, and Laravel job queues sync data to the cloud once a device reconnects, with export to PDF, CSV, and OBJ for easy sharing.

OUTCOMES

A pioneering, all-in-one archaeology tool, now expanding to iOS and web, with AI capability continuously refined. Key business outcomes include: Real-time AI artifact detection via mobile camera, working fully online or offline 3D artifact models generated from a simple photo series, running directly on mobile hardware AI-generated historical context and classification for every discovered artifact Handwritten field forms digitized via OCR, with automatic duplicate-entry prevention

STACK & SERVICES

FigmaFlutterFlutter WebLaravelMongoDBMySQLAWS OCRGoogle OAuthStripeAWS S3YOLOTensorFlowPyTorchGaussian SplittingQwen VL 2.5
AI-driven object scanning3D model generationOCR integrationOffline functionalityCross-platform availabilityAdvanced backend managementAI-based form extractionSecure user authenticationData sharing & synchronizationSubscription options
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WHAT'S INSIDE
  • Project context and business challenge
  • Approach, product decisions, and implementation direction
  • Key outcomes and operational impact

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