AI integration requires careful planning around use-case selection, data readiness, and grounding. We help make existing applications AI-ready with proper architecture and safe-by-design controls.
Our AI/ML integration approach includes comprehensive use-case selection with value models, data readiness assessment and grounding strategies, model evaluation and selection, and carefully designed prompts and guardrails.
We implement RAG architecture with proper indexing, latency and cost budgeting, feedback loops with human-in-the-loop patterns, and comprehensive safety, privacy, and red-teaming procedures.
Every AI feature includes proper observability, A/B testing frameworks, quality metrics, rollout and fallback strategies, and comprehensive documentation with admin controls. Our AI integrations are auditable and safe.
Making applications AI-ready requires careful architecture, proper grounding, and safe-by-design controls.
Safe-by-Design AI Integration
RAG architecture ensures AI responses are grounded in your actual data and documentation.
— Devlyn Engineering
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