MetaDors Service 02
AI Integration
AI integration is the practice of embedding large language models and related ML capabilities into your product so users get automated, intelligent outcomes inside everyday workflows.
What AI Integration includes
AI integration at MetaDors means shipping features users feel — not demos that die in a slide deck. We connect OpenAI and Anthropic models into real product workflows: assistants, semantic search, document intelligence, scoring engines, and automation agents. Implementation covers prompt architecture, retrieval (RAG), evaluation harnesses, rate limits, cost controls, and privacy boundaries so AI stays reliable in production. We specialize in SaaS and FinTech contexts where accuracy, latency, and auditability matter as much as novelty.
How does MetaDors deliver AI Integration?
- Map high-ROI AI use cases against your data and UX
- Prototype prompts, tools, and retrieval pipelines
- Evaluate quality, cost, and failure modes
- Ship guarded production features with monitoring
Outcomes you can expect
- Production AI features with measurable user value
- Controlled spend via caching, routing, and usage metering
- Safer releases with evaluation and fallback paths