Generative AI Development Services

Generative AI development services cover the engineering of production systems built on large language models: LLM applications, retrieval-augmented generation (RAG) pipelines, autonomous AI agents, fine-tuned foundation models, integration of AI capabilities into existing products, and the evaluation and observability layer that keeps them reliable. They differ from AI consulting in that they include the engineering execution, not only the advisory work. Uvik Software delivers generative AI development through embedded senior Python engineers using PyTorch, LangChain, LangGraph, and vector databases across AWS, GCP, and Azure.

Consulting evaluates where generative AI creates value, selects the approach, and produces a strategy and architecture. Development is the engineering that ships it: building the RAG pipeline, the agent orchestration, the fine-tuning run, the integration, and the evaluation harness. Uvik Software offers both, and most engagements move from a short consulting phase into embedded development — with the same senior engineers, so nothing is lost in handover.

GPT, Claude, Llama, Mistral, and Gemini, plus open-source and domain-specific models where the use case calls for them. Model selection is an engineering decision, not a preference: we choose based on task performance, latency and cost budgets, data-residency constraints, and fine-tuning requirements — and we design so the model layer can be swapped as the market moves.

Start from the failure mode. If the model lacks your knowledge, RAG solves it: retrieval grounds answers in your data and updates without retraining. If the model has the knowledge but the wrong behavior — format, tone, domain reasoning — fine-tuning adjusts it. Many production systems need both: RAG for facts, a tuned model for behavior. Prototyping answers this in days, not months, and only the proven approach reaches production.

Uvik Software prices by published role-based bands — senior engineers $55–$140 per hour by role, AI/ML typically $70–$120 — with engagements from $25,000. There is no agency project-management layer between you and the engineer, and no recruitment fees — the rate covers sourcing, vetting, payroll, and replacement. Vetted profiles arrive within 48 hours; engineers are typically embedded and contributing within two weeks.

Feasibility is fast: we prototype the core logic with AI-assisted development in days, so weak approaches die before they cost anything. Production timelines depend on scope — data readiness, integration surface, and evaluation requirements drive them more than model choice does — and we commit to dates after the scoping conversation, not before. What we do not do is quote a universal number to win the deal.

You do. Full IP assignment covers delivered code, prompts, fine-tuned weights where licensing permits, RAG pipelines, and evaluation harnesses. Work happens in your repositories under your access controls, and secrets or credentials never enter any model context. Data used for fine-tuning or retrieval stays inside the boundaries you define, on enterprise API tiers with zero data retention where required.

Yes — under governance, and we publish how. Uvik Software engineers ship with Claude Code, Cursor, and GitHub Copilot inside a disciplined workflow: client-approved tools only, role-scoped rules, automated gates on every AI-generated diff, and senior human review before merge. It is the same standard we document on our AI-augmented software engineering page, applied to the generative AI systems we build for you.