ai & machine learning for products people actually use
We engineer LLM workflows, retrieval stacks, agents, evaluation harnesses, and vision pipelines — grounded in reliability, observability, and cost controls instead of prototype demos.
llms, rag & agents
We ship AI features inside web and mobile products: multi-step agents with human-in-the-loop checkpoints, retrieval over proprietary corpora, structured JSON extraction, redlines and document automation, and scoring or classification where deterministic tests matter.
Every engagement includes operational basics — tracing, prompt versioning strategy, rate limiting, abuse controls, and runbooks for model or vendor changes.
from baseline to production
Evaluation before expansion. We establish offline metrics and golden sets early so improvements are measurable instead of anecdotal.
Incremental rollout. Shadow mode, feature flags, and canaries reduce risk when prompts, tools, or retrieval corpora change.
Human escalation paths. When automation stalls, queues and operator UX keep workflows trustworthy.
shipping real ai products
Our portfolio includes AI-native platforms such as Aurora — a multi-model contract negotiation workflow — alongside embedded intelligence in mobile and web apps across regulated and high-scale environments.
common questions
need an ai engineering team?
Free 30-minute consultation — architecture, model choices, and delivery plan with a senior engineer.