Production Case Studies

Selected Work

Detailed engineering breakdowns of real-world intelligent systems. We document the problem context, architectural choices, empirical benchmarks, and lessons learned.

Case Study 01|Sports Technology & Analytics

Multi-Camera Sports Video Intelligence Platform

Automated player, ball and tactical event tracking from 60fps broadcast video feeds

A high-framerate computer vision architecture designed to track 22 players and match ball kinematics across varying broadcast camera angles, translating unstructured video into 3D pitch coordinate data.

Computer VisionMultimodal AIAI Product Engineering
Empirical Outcomes
< 16ms
Per-frame inference latency
Measured on 1080p60 multi-camera input streams utilizing TensorRT INT8 quantization
99.1%
Tracking ID preservation
Benchmark evaluated on benchmark match datasets with occlusions exceeding 1.8 seconds
Sub-centimeter
Canonical pitch accuracy
Verified against laser-measured pitch markings under varying stadium lighting conditions
Case Study 02|Enterprise B2B Software

Autonomous Enterprise Document Reasoning Platform

End-to-end multimodal document reasoning, policy validation, and automated ERP dispatch

An enterprise agentic system that extracts information from complex commercial contracts and invoices, reasons across regulatory compliance policies, and executes workflow actions with deterministic human approval gates.

Agentic AIMultimodal AIAI Product Engineering
Empirical Outcomes
99.4%
Extraction precision on tables
Empirically measured across 12,000 multi-page invoices with handwritten annotations
74%
Automated straight-through processing
Transactions completed with zero human intervention while strictly respecting policy gates
100%
Auditability trace coverage
Every committed ledger action contains verifiable spatial PDF coordinates and agent reasoning logs
Case Study 03|Logistics & Manufacturing

Edge Computer Vision for Industrial Operations

Sub-millisecond visual inspection and automated safety anomaly detection on local edge clusters

A distributed edge computer vision platform operating inside high-throughput manufacturing plants, monitoring assembly lines for micro-defects and operational safety violations without sending video to external cloud networks.

Computer VisionAI Product Engineering
Empirical Outcomes
11.2ms
End-to-end edge latency
From camera exposure trigger to PLC reject signal actuation on factory floor
0.15mm
Defect detection threshold
Validated across micro-solder bridges, surface fractures, and component misalignment
100%
Air-gapped data sovereignty
Zero visual data transmitted over public internet; full compliance with manufacturing IP protection