Custom AI applications, LLM integrations, production-grade MLOps, and AI SaaS platforms — delivered in 8–12 weeks.
AI Product Development covers the full process of designing, building, and shipping custom AI applications — from prototype to production. That includes LLM integration, MLOps pipelines, API design, and ongoing model operations.
Norvik builds custom AI products that solve specific business problems — not generic chatbots or off-the-shelf tools. We cover the full stack: product discovery, model selection, application development, API design, and production MLOps. We are LLM-agnostic, which means we pick the right model — GPT-4, Claude, Gemini, Llama, or a fine-tuned open-source model — based on your requirements, not vendor relationships.
A proven four-phase methodology that takes you from first conversation to production AI — with full accountability at every step.
We run a product discovery sprint: requirements gathering, technical feasibility check, model selection, and architecture design. Output: an approved technical spec.
We complete UX design, data pipeline design, API contract definition, and infrastructure architecture. All decisions are confirmed before we write a line of application code.
We build in two-week sprints with working software at every checkpoint. Model integration, API development, frontend, and MLOps pipeline run in parallel.
We deploy to production with monitoring, alerting, and model drift detection. Handover includes full source code, architecture docs, runbook documentation, and 30 days of hypercare.
We run a product discovery sprint: requirements gathering, technical feasibility check, model selection, and architecture design. Output: an approved technical spec.
We complete UX design, data pipeline design, API contract definition, and infrastructure architecture. All decisions are confirmed before we write a line of application code.
We build in two-week sprints with working software at every checkpoint. Model integration, API development, frontend, and MLOps pipeline run in parallel.
We deploy to production with monitoring, alerting, and model drift detection. Handover includes full source code, architecture docs, runbook documentation, and 30 days of hypercare.
We run a product discovery sprint: requirements gathering, technical feasibility check, model selection, and architecture design. Output: an approved technical spec.
We complete UX design, data pipeline design, API contract definition, and infrastructure architecture. All decisions are confirmed before we write a line of application code.
We build in two-week sprints with working software at every checkpoint. Model integration, API development, frontend, and MLOps pipeline run in parallel.
We deploy to production with monitoring, alerting, and model drift detection. Handover includes full source code, architecture docs, runbook documentation, and 30 days of hypercare.
We select tools based on your requirements, not vendor relationships.
“Intelligent intake that routes patients faster — and frees clinicians to care.”
Read the full story“From 3-week backlogs to same-day review — at a fraction of the cost.”
Read the full story“Predicting demand before it happens — so shelves are never empty.”
Read the full storyStraight answers to the questions we hear most often.
Still have questions? Talk to our team
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