Applied AI engineering
Applied AI Development
Discuss feasibility directly with the developers who will build and evaluate your AI solution. Our work extends beyond API integration to computer vision, model training, semantic search, and GPU-backed operation. We connect model development with application engineering, explaining data requirements, measurable results, costs, and limitations before recommending a production approach.Start a conversationResearch before expensive assumptions
AI work often begins with a paid feasibility or discovery phase. We examine available data, required accuracy, operating environment, computing cost, privacy constraints, and how success can be measured before recommending a production direction.
Beyond connecting a hosted model
Experience includes aerial-image recognition, realtime sports-video analysis, data preparation, training and fine-tuning, evaluation pipelines, computer vision, graphics and video processing, and deployment on GPU infrastructure. LLM integrations, RAG, recommendations, and document automation are also available.
AI within dependable software
Models are integrated with the surrounding application, monitoring, review workflows, fallback behavior, infrastructure, and data lifecycle. Accuracy limitations and human checkpoints are made explicit where fully autonomous behavior would be unsafe or misleading.