AI Engineering

What ai engineering includes

We build AI assistants, retrieval-based search and model integrations for defined business tasks.

The release is scoped around a real user journey, with accessibility, performance, security and maintainability reviewed before launch.

• Smart Assistant Integration: Custom prompt engineering, context retention, and fine-tuned system instructions using Gemini models.
• RAG & Vector Search: Chunking, embedding generation, and fast semantic search across your proprietary company knowledge base.
• Automated Content & Vision: Multimodal processing for invoice extraction, visual asset classification, and automated email reply generation.
• Guardrails & Safety: Rate limiting, prompt sanitization, cost budgets, and fallback strategy for enterprise reliability.

Technology and delivery

The working stack may include Gemini 2.5 API, LangChain, Python, Vector DB, RAG Engine. The final choice follows the product constraints and the team that will maintain it.

• Typical starting point: $1,800
• Typical timeline: 2 - 4 Weeks

A focused first release

Before development starts, BuiltbyGSV identifies the core outcome, the smallest useful release and the checks that prove it is ready. Optional features stay separate so the launch does not depend on untested assumptions.