AI & Machine Learning
AI agents and applications that handle real work — not chatbot demos that stall in pilot.
OpenAIClaudeGeminiVector databasesComputer Vision
The problem
Everyone wants 'AI in the product.' Few teams have the infrastructure to ship a model into production safely, evaluate its output, or contain what it costs at scale.
Our approach
We start with the decision or task you want automated, not the model. That determines the architecture — retrieval, tool use, fine-tuning, or plain deterministic code doing the job better than an LLM would. We build in evaluation and guardrails from day one, so accuracy is measured, not assumed.
What you get
AI agents for internal and customer-facing workflows
Support and sales chatbots grounded in your data
LLM application architecture and prompt systems
Computer vision pipelines for inspection and capture
Evaluation harnesses and cost/latency guardrails
Human-in-the-loop review for high-stakes decisions
Typical outcomes
40–70%
of routine requests handled without a human
< 2s
typical agent response latency
100%
of outputs logged and evaluable
Related case studies
Let's talk about what's slowing you down.
Book a 30-minute call. We'll tell you honestly whether we're the right fit before we talk about scope.