Custom AI, Built for Production

ML systems for real-time process monitoring, autonomous decision-making, and predictive intelligence. Covers batch inference pipelines through to sub-100ms prediction systems — engineered to your SLA, with model monitoring and retraining infrastructure to prevent performance drift.

Predictive models built from your historical operational data and deployed into planning, procurement, and risk workflows. Surfaces leading indicators of demand, failure, or financial exposure — before they become operational events.

Object identification, defect detection, and behavioral analysis integrated with cameras, production lines, and edge devices. Built for high-throughput, accuracy-critical deployments with 20+ years of domain experience behind the architecture.

AI embedded directly into hardware, wearables, and robotics for latency-sensitive or data-sovereign use cases. Compact neural networks run on low-power edge devices — real-time inference, no cloud dependency, no data leaving the facility.

RAG pipelines grounded in your proprietary data — not hallucinated outputs. Your system pulls from internal documents, synthesises the relevant content, and routes structured outputs to the right team. LLM-powered copilots and domain-specific agents also developed to scope.

End-to-end AI integration across workflows — analytics, ML-driven process intelligence, NLP automation, and computer vision deployed where they create the most leverage. Systems engineering for multi-team, multi-system deployments at scale.

NLP-powered agents for customer service, internal helpdesks, and structured data capture from unstructured interactions. Handles variable input formats at scale, integrated with your existing support and operations infrastructure.

When no existing solution fits, we build from first principles — problem definition, data assessment, model development, and a production system instrumented for monitoring, retraining, and drift alerting. Full explainability, no vendor lock-in.