Computer Vision
Development
We design, train, and deploy vision systems for real-world operations, detection, OCR, visual search, quality inspection, and video analytics, built for accuracy, latency, and cost.
- / Trust By
Model-agnostic (SAM, CLIP , YOLOv8/11, Detectron2). Built with PyTorch, OpenCV, TorchVision, ONNX/TensorRT. We engineer pipelines, evals, and serving from day one.
KPI-driven
Reliable
Deployable
- / Techstack
Our toolkit
What we build
From dataset to dashboard: collection → labels → models → evals → serving → monitoring.
Object Detection & Tracking
YOLO/Detectron2 pipelines with multi-object tracking (DeepSORT/ByteTrack).
Semantic & Instance Segmentation
Segment Anything (SAM), Mask R-CNN, and U-Net for pixel-level tasks.
OCR & Document AI
Invoices, IDs, forms. Layout parsing, key-value extraction, and validation.
Visual Search & Similarity
CLIP/ViT embeddings for find-similar, deduping, and content moderation.
Quality Inspection
Defect detection, counting, alignment checks, and tolerance measurements.
Video Analytics
Realtime edge inference, activity recognition, heatmaps, and alerts.
Outcomes you can expect
Accuracy
Task metrics (mAP, F1, IoU) tied to business KPIs
Latency & Cost
Edge/Cloud tuning, quantization, batching, and caching
Reliability
Canaries, regression tests, and drift monitors
Adoption
APIs, dashboards, and operator UX for teams
Our delivery process
- / Process
1/6
Goals, constraints, camera/data mapping, and success metrics.
Discover
2/6
Model choices, labeling plan, evals, serving strategy, and SLAs.
Design
3/6
Training, augmentation, ablations, and automated tests.
Develop
4/6
Profiling, optimization, safety, canary, and monitoring hooks.
Harden
5/6
Edge devices (TensorRT/ONNX) or cloud serving with CI/CD.
Deploy
6/6
Human feedback, drift handling, and next-win roadmap.
Improve
Who we build for
From visual search in ecommerce to defect detection in factories tailored to your domain.
Ecommerce (PDP, search)
Manufacturing (QA)
Logistics (counting)
Retail (footfall)
Healthcare (docs)
Operations
Engagement models
Pilot (4-6 weeks)
Focused use-case with labeled set, KPIs, and demo dashboard.
Production rollout
Edge/cloud deployment, monitoring, and operator tooling.
Co-build & Enablement
We build while upskilling your team with playbooks and templates.
- / FAQs
Frequently Asked Questions
- Do you support on-prem or edge?
Yes – Jetson/TensorRT for edge; VPC for cloud with private networking.
- How do you label data?
We define a labeling plan, tools, QC steps, and inter-annotator agreement.
- How do you ensure quality?
Eval sets, mAP/F1/IoU, regression suites, canaries, and drift monitors.
- How fast can we launch?
A focused pilot can ship in 4-6 weeks depending on data and integrations.
Ready to build with vision?
We will define KPIs, engineer the pipeline, and deploy models your teams can trust and extend.