AI Platform Architecture

As a Specialist in High-Performance Data Pipelines & LLM Context Engines, I help organizations evolve data platforms into intelligent AI platforms. I focus on productionizing GenAI safely for enterprise-scale knowledge retrieval and security analysis, with deep expertise in RAG, vector search, LLMOps, governance, and latency trade-offs.

Discovery & Architecture

  • Capability mapping and platform roadmap
  • Data contracts, lineage, and governance alignment for AI
  • Reference architectures and decision frameworks

Data Foundations

  • Batch/streaming pipelines, feature stores, quality gates
  • Retrieval-ready data modeling for RAG
  • Security, PII handling, and access patterns

RAG & Vector Search

  • Retrieval orchestration, chunking, and indexing strategies
  • Vector DB selection (Pinecone, Weaviate, Qdrant, pgvector)
  • Evaluation frameworks and guardrails

LLMOps & Reliability

  • Observability, tracing, feedback loops, metrics
  • Latency and cost optimization across providers
  • Governance, safety, and policy enforcement

Outcomes

  • Faster time to value

    Blueprints and guardrails that reduce POC-to-prod friction.

  • Lower risk

    Security, governance, and evaluation built-in from day one.

  • Predictable costs

    Architectures tuned for scale and cost/latency trade-offs.

Request an AI architecture review

I’ll assess your use case, data foundation, and propose a practical path to production.

Contact me on LinkedIn