AI Development Services That Ship to Production

AI development services cover the work of putting AI to use inside a business: choosing the right problem, preparing the data, building or fine-tuning models, integrating them with your existing systems, and monitoring them in production. At Digital Scientists that includes custom machine learning, generative AI, AI agents, computer vision and NLP, plus the data engineering, security and MLOps that keep them working.

It depends on what the AI has to do, how ready your data is, how many systems it connects to and how much it acts on its own. AI specs change once real data and real users show up, so we don’t quote a fixed price from a feature list. A Blueprint (from $25K) sets the architecture and a budget you can fund before the build. Or start with Build with Us: a senior architect building in your systems for two weeks, for $10K.

With Build with Us, an architect is writing code in your systems in the first two weeks. A production AI feature or agent typically takes 8 to 16 weeks. Enterprise deployments with complex data pipelines, compliance requirements and several integrations run 3 to 6 months. We work in two-week sprints, so you see working AI early.

It depends on the type of AI. Generative AI and LLM applications (document analysis, chat interfaces, content generation) can work with minimal proprietary data, the foundation models bring the intelligence. Custom ML models (predictions, classification, anomaly detection) do require training data, and we help you assess data readiness as part of the Blueprint. If your data is messy, incomplete, or siloed, our Assessment identifies gaps and gives you a practical plan to close them before investing in development.

Healthcare is where we go deepest, 9 of our 14 AI projects are in healthcare. We deploy AI on HIPAA-compliant infrastructure (AWS with BAA, encrypted at rest and in transit), implement role-based access controls, and maintain audit logs for all AI-processed PHI. For LLM-based features, we use API configurations that prevent model training on patient data. Our healthcare practice has shipped systems processing 100,000+ patient encounters across 130+ facilities in 7 states. We understand clinical workflows, EHR integration, and the real reasons AI fails in health systems.

A chatbot responds to questions in a conversation. An AI agent takes autonomous action, it reads emails, updates your CRM, generates documents, makes API calls, and orchestrates multi-step workflows without human intervention. Agents can work in swarms where multiple specialized agents collaborate on complex tasks. We build both, but the biggest ROI we see comes from AI agent systems that replace entire manual workflows, like our SBIR grant automation that reduced a weeks-long screening process to daily automated digests.

Yes, integration is usually the hardest and most important part of an AI project, and it's where most vendors fall short. We've integrated AI systems with Epic, PointClickCare, Salesforce, SAP, and dozens of custom platforms via HL7/FHIR, REST APIs, and database-level connections. Our engineering team handles the full stack, from model development to the API layer to the frontend that your team actually uses. AI that doesn't connect to your systems stays a demo. We ship production integrations.

You do. The code, trained models, prompts, data pipelines and documentation belong to you. We build on the model providers that fit the job, Claude, GPT, Gemini or open-source models, so you are never locked into one vendor, and your data is never used to train someone else’s model.