Detection, segmentation, tracking and re-identification — engineered into governed pipelines that run on your cloud, with confidence scores and audit trails on every decision. From pathology slides to factory floors to scanned documents, we ship vision you can trust.
A model that scores well offline stalls on real footage — lighting, occlusion, throughput and GPU cost break the pilot.
Inspection, grading and damage assessment vary by person and shift — disputes, rework and missed defects follow.
Black-box predictions with no confidence, no provenance and no review trail can't be trusted in regulated or high-stakes settings.
Modern architectures, engineered into resilient pipelines and wired into your systems.
Transformer and CNN detectors (RF-DETR, YOLO-class), semantic & instance segmentation, and fine-grained classification — with per-detection confidence and 360° visual reporting.
Multi-object tracking with body and face re-ID (FastReID, InsightFace) for presence, attendance and behavior analytics across cameras and full working days.
Foundation-model encoders (GigaPath ViT) for whole-slide histopathology — tissue segmentation, Gleason grading and recurrence prediction, delivered as prr.ai.
Defect, damage and condition detection from images and video for QC, vehicle inspection and field operations — fewer disputes, condition reports in real time.
Signature and stamp detection, layout analysis and visual validation on scanned pages — the vision layer behind regulated document review. Pairs with Document AI.
Gigapixel tiling, DZI pyramids, GPU inference services and viewers — the heavy-image plumbing that makes slide- and scene-level analysis usable at scale.
Deep learning on whole-slide images detects prostate cancer recurrence and predicts timeframes from a single modality.
Read the case study →A computer-vision platform grading embryo viability consistently — standardizing IVF decision-making across clinics.
Read the case study →Fast, consistent vehicle damage detection from images and video — fewer disputes, real-time condition reports.
Read the case study →Detects and categorizes damage in video and image content with per-detection confidence — QC and maintenance at scale.
Read the case study →Computer vision catches manufacturing defects early alongside GRI-standard ESG reporting — safer products, accurate reporting.
Read the case study →Fragmented highway data unified into a GIS monitoring platform with automated SLA compliance and decision intelligence.
Read the case study →Azure, AWS or open stacks — GPU inference where your data lives
Per-detection scores, thresholds and human-in-the-loop review
Provenance and traceability on every prediction
Built for regulated medical, pharma and enterprise settings
Detection, segmentation and classification; tracking and re-identification; pathology and medical imaging on whole-slide images; visual inspection and damage detection; and document and signature vision — all engineered into governed production pipelines.
Transformer and CNN detectors (RF-DETR, YOLO-class), FastReID and InsightFace for tracking and re-ID, and GigaPath ViT foundation encoders for pathology — selected per problem and deployed on your cloud.
Yes. We build with per-detection confidence scores, provenance and audit trails, and deliver regulated medical vision through prr.ai — HIPAA-aligned and designed for 21 CFR Part 11.
We engineer for real throughput, latency, GPU cost and edge cases, add human-in-the-loop review and monitoring, and ship on Azure, AWS or open stacks.
Tell us the outcome you need — we'll bring the engineers who've shipped vision in pathology, manufacturing, mobility and regulated document review.