01
Discovery
Separate experimentation from serving. Define inputs, outputs, and SLAs.
Service
Python services for AI pipelines, data processing, and APIs where the ecosystem fits—FastAPI, workers, and notebooks that graduate into production code.
Teams with data/AI workloads that need production packaging without losing iteration speed.
01
Separate experimentation from serving. Define inputs, outputs, and SLAs.
02
Package services with typed models, config, and dependency pins.
03
Add tests around parsing and critical transforms before widening traffic.
API layer for sync work; workers for heavy jobs; shared libraries for schemas.
Dependency scanning, secret management, and least-privilege cloud roles.
Batch sizing and queue depth tuned to data volume. GPU choices only when measured need exists.
Yes. We often keep product UI in Next.js and specialized pipelines in Python behind clear HTTP or queue contracts.
AI Development
Production-ready AI features, model integrations, and LLM applications designed around real workflows—not demos.
LLM Applications
Retrieval-augmented apps, assistants, and internal copilots grounded in your documents, systems, and permissions.
API Development
Clean APIs and integrations that connect products, CRMs, payment systems, and internal tools.
Share the notebook or script and the reliability bar you need.
Productionize Python services