Generative AI development for production.

It designs, builds, and deploys applications that use large language models to solve specific business problems. The work covers the full lifecycle: data preparation, prompt design, fine-tuning where it helps, production deployment, and ongoing evaluation.

Cost depends on scope, how ready your data is, and how much has to be built rather than integrated. Our pricing page explains what moves the cost, and a discovery call is the fastest way to get a real estimate for your project.

Traditional ML companies build predictive models: classification, regression, forecasting. Generative AI companies build systems that create new content, such as text, code, images, and structured outputs, typically using foundation models and open-weight LLMs.

Discovery takes 1 to 2 weeks, architecture another 1 to 2, and build phases run 4 to 12 weeks depending on complexity. Discovery ends with a roadmap that sets the real timeline for your project.

We work with hosted models from providers such as OpenAI and Anthropic and with open-weight models, chosen per engagement. We assess each use case against cost, latency, privacy requirements, and task fit. Where rules require data to stay in your environment, a self-hosted open-weight model such as Llama or Mistral is an option to evaluate.

We decide where the model runs, what gets logged, and who can see which data during architecture, before the build. We can work with your data inside your environment, including VPC and on-premise deployments. Your compliance team decides which rules apply to your project, such as HIPAA or the EU AI Act, and we build to the requirements they set.

Our industry pages cover healthcare, fintech, SaaS, e-commerce, legal, and enterprise software: where generative AI fits in each and what shapes the build. Our published work so far is on the case studies page.

You need three things: a specific measurable use case, access to relevant data, and an internal champion. With those in place we can scope a discovery and tell you honestly whether to build, wait, or buy.