Computer Vision

Real-time analysis of visual data for anomaly detection and automated monitoring.

From industrial scans to biometrics to medical imaging, we build vision systems that detect, classify, and monitor at a scale no inspection team can match, with the explainability to trust the result.

Business problem

Thousands of hours of manual inspection and review of visual data.

Tangible outcome

Time-to-insight measured in days instead of months.

Built on

Vertex AI, Gemini multimodal, and open vision models

What we build

Inspection and audit

Agents that reconcile physical reality (3D scans) with engineering intent (2D drawings) to catch discrepancies.

Biometric identification

Deep learning plus vector similarity search to match images against reference databases of millions.

Hybrid detection

Specialized detectors (YOLO) combined with multimodal LLMs to resolve hard cases like poor lighting.

Clinical imaging

Multidisciplinary automated analysis and remote monitoring for practitioners.

How it works with us

Speed is our differentiator. We move from discovery to production in weeks, not months.

1

Rapid Discovery

1 to 2 days to identify the highest-impact use cases in your data and processes.

2

Use Case Definition

Clear success metrics and an architectural blueprint for your solution.

3

Fast Build

Weeks, not months, using GCP-native tools, with real-time dashboards so you see what we see.

4

Production Deployment

Deployed for scalability, security, and immediate ROI.

Read more about how we work

Proof from production

Anonymized Computer Vision deployments from our case studies.

Global Environmental Engineering Firm

Agentic Line Walkout (Industrial Audit)

An Auto-Auditor that reconciles physical reality (3D scans) with engineering intent (2D P&IDs). Using Gemini-powered agents and SAM 3 (Segment Anything Model), the system performs virtual walkouts to detect discrepancies between "as-built" and "as-designed" infrastructure.

Outcome: Replaced thousands of manual inspection hours with a scalable, explainable AI process. Reduced time-to-insight from months to <2 days.
Read the case study
International Veterinary Certification

Equine Facial Recognition System

A production-ready biometric system for identifying horses leveraging Deep Learning (Vertex AI) and Vector Similarity Search to match new images against a reference database of 15 million.

Outcome: Drastically improved accuracy of animal identification and reduced fraud/errors in health certification. Self-improving over time.
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National Traffic Data Analytics

Traffic Data AI Enablement

A Hybrid AI Architecture (YOLO + Gemini Multimodal) for automated vehicle classification and velocity tracking, using LLMs to resolve situational difficulties like poor lighting.

Outcome: Targeted 95%+ detection accuracy for FHWA classes. MLOps pipeline captures human corrections to retrain models, lowering costs.
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Specialized Veterinary Diagnostic

Medical AI Vision for Practitioners

A computer vision platform for multidisciplinary automated analysis (Ophthalmology, Dermatology, Dentistry). Includes remote post-operative monitoring for AI-assisted healing assessment.

Outcome: Standardized patient care across the team. Significantly reduced revenue leakage by ensuring all findings are billed.
Read the case study

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Other solutions

Let’s build your Computer Vision advantage

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