Beyond the Demo: Engineering AI for Mission-Critical Systems
Most AI proof-of-concepts fail in production due to high latency, unpredictable API cost spikes, or fragile error handling. I engineer robust AI architectures designed to withstand high concurrency and rigorous enterprise compliance.
Low-Latency Token Streaming
Asynchronous Server-Sent Events (SSE) and WebSocket streaming built with Python (FastAPI), providing immediate character-by-character UI rendering for end users.
Semantic Caching & Cost Control
Vector database integration (pgvector, Qdrant) to cache and serve semantic query embeddings instantly, slashing third-party LLM API bills by up to 70%.
Resilience & Intelligent Fallbacks
Circuit breakers, automatic secondary model fallbacks, and exponential backoff retry algorithms ensuring 99.9% uptime despite upstream provider rate limits.
EU AI Act & GDPR Privacy Compliance
Privacy-first architectures featuring upstream PII scrubbing, European audit trails, strict data-retention controls, and Human-in-the-Loop (HITL) safeguards.
High-Impact Enterprise AI Use Cases
Practical, measurable AI systems that streamline manual operations and elevate customer experience.
Autonomous Research & Outreach Agents
Privacy-compliant prospecting pipelines that query public registries, evaluate legitimate interest under GDPR, and generate contextual draft emails for manual human sign-off.
RAG Assistants & Knowledge Bases
Enterprise Retrieval-Augmented Generation (RAG) engines indexed against proprietary corporate documentation, delivering factual, hallucination-free answers.
Intelligent Parsing & Extraction
Automated ingestion and structured data extraction from invoices, technical manuals, and contracts directly into relational databases (PostgreSQL / SQL Server).
Let's discuss your project
Tell us what you're building - a secure microservice, a custom AI chatbot, or a high-performance enterprise application. You'll get a scope, a price, and a timeline. In writing, within 48 hours.