VisionKIT
Computer vision, wired into your pipeline. OCR, detection, segmentation, and visual search — running on your images, video, and edge devices.
VisionKIT is a production computer-vision platform for teams turning cameras, documents, and media archives into structured data. It's aimed at operators — insurers processing claims, retailers auditing shelves, manufacturers catching defects, marketplaces moderating uploads — who need OCR, detection, segmentation, and visual search in one coherent pipeline instead of five vendor contracts.
Documents flow through PaddleOCR and TrOCR with layout-aware models (LayoutLMv3, Donut) for structured extraction of receipts, IDs, and forms. Real-time detection runs on YOLOv11 and RT-DETR, with Grounding DINO for open-vocabulary queries; segmentation uses SAM2 and Mask2Former. Fine-tuned ViT and SigLIP power classification and visual search, and everything serves through Triton with ONNX and TensorRT builds for GPU, plus CoreML and TFLite targets for edge devices like Jetson and mobile.
On day 1 you get OCR and detection running against your images, a labeling workflow wired up, and a search index over your existing media library.
By week 3 detectors are fine-tuned on your labeled data, OCR is tuned for your document classes, video streams run real-time via RTSP or WebRTC, and edge builds ship to your devices with drift monitoring in place.
Build it from scratch, or start a week ahead
- Six to nine months building the orchestration, memory and recovery before a first real result.
- An evaluation harness you write from scratch — then argue about.
- A team learning your edge cases live, in production.
- A black-box vendor you can't inspect, tune or move off.
- A working VisionKIT on your data in week one — the hard parts already solved.
- Evals seeded on day one and graded against your real workflows.
- Senior owners with full traces and dashboards from the first deploy.
- You own the prompts, the weights, the traces and the outcomes.
Ships with the hard parts solved
Document OCR & IDP
Receipts, IDs, forms, and tables extracted into typed JSON.
Detection & tracking
Real-time object detection and tracking on images and video.
Segmentation & search
Pixel-level masks and visual similarity search across your library.
Edge & streaming
ONNX, TensorRT, CoreML, and TFLite builds with RTSP/WebRTC ingest.
Where teams deploy it
Fine-tuned on your data and shaped to the workflow it lands in — these are the deployments we see most.
Kick-off to production in three weeks
A fixed scope and a visible finish line — you see it working before it's load-bearing.
Week 1 — Integration
Ingest cameras, archives, and documents; stand up the inference stack.
Week 2 — Fine-tune
Detectors, OCR, and classifiers trained on your labeled data.
Week 3 — Ship
Cloud and edge builds live with dashboards and drift monitoring.
Vision stitches together more moving parts than any other AI modality — labeling, training, serving, edge, monitoring — and every team underestimates at least three of them. VisionKIT ships the whole chain, so you start on pixels and business outcomes, not on infrastructure.
“They understand our needs quickly and are a delight to work with.”
VisionKIT, live on your stack in a week
One call to scope it, a senior team on it from day one — and a fixed scope agreed before we start.