LLM & Generative AI

LLM solutions that survive production.

From POC to production with predictable costs. LangChain/LangGraph, RAG systems, voice and video AI — plus the guardrails and cost control an enterprise expects.

Capabilities

Eight areas, one architect.

LangChain & LangGraph

  • AI agents and multi-agent systems
  • Complex chains and workflows
  • Tool calling and function integration
  • Memory and state management

RAG & knowledge systems

  • Vector databases (Pinecone, Weaviate, pgvector)
  • Document processing pipelines
  • Hybrid search (semantic + keyword)
  • Enterprise knowledge bases

LLM cost optimization

  • Model selection (GPT-4, Claude, open-source)
  • Prompt caching and optimization
  • Hybrid deployments (cloud + local)
  • Token usage analytics and budgeting

Speech-to-text & voice AI

  • Whisper, AWS Transcribe integration
  • Real-time transcription systems
  • Voice assistants and IVR
  • Multi-language support

OCR & document intelligence

  • Document parsing and extraction
  • Invoice and form processing
  • AWS Textract, Azure Document AI
  • Structured data extraction

Video AI & generation

  • Video content analysis and indexing
  • AI-powered video generation
  • Automated video summarization
  • Scene detection and tagging

AI guardrails & safety

  • Content moderation and filtering
  • Prompt injection protection
  • Output validation frameworks
  • Compliance and audit trails

LLM evaluation & testing

  • Quality metrics and benchmarks
  • A/B testing frameworks
  • Regression testing for prompts
  • Performance monitoring dashboards
Why me

AI projects with engineering discipline.

Predictable costs

Token budgeting, caching and model selection — no surprise bills.

POC to production

Error handling, monitoring and scalability from day one.

Hands-on delivery

Working implementations in Python, TypeScript and Go, with architecture documentation.

Enterprise experience

17 years of production systems: security, compliance, integration with existing infrastructure.

Measurable results

An AI solution that saves >$1.2M a year. The metric comes before the technology.

Flexible engagement

From a one-time architecture review to ongoing development.

Stack

Technology stack.

LLM providers
OpenAI GPT-4/GPT-4o, Anthropic Claude, AWS Bedrock, Azure OpenAI, open-source models (Llama, Mistral)
Frameworks
LangChain, LangGraph, LlamaIndex, Haystack, Semantic Kernel
Vector databases
Pinecone, Weaviate, Qdrant, pgvector, Milvus, ChromaDB
Cloud & infrastructure
AWS (Bedrock, SageMaker, Lambda), GCP (Vertex AI), Azure, Kubernetes
Let's talk

Tell me about your AI project.

Free consultation: project scope, architecture options, cost estimates.

Free 30-min strategy call

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