Production-GradeAI Systems
RAG pipelines, LLM deployments, autonomous agents, and internal copilots built for reliability.
Engineering backgrounds from EPFL, ETH Zurich, and MIT
How WeWork
From architecture review to production deployment. Built for real data, real users, and real constraints.
AI Architecture & Readiness Audit
Technical assessment of your data infrastructure, security posture, and AI readiness. Identify integration points, data governance gaps, and realistic deployment paths.
End-to-End System Development
RAG pipelines, LLM orchestration with LangChain, PostgreSQL-based vector search. Azure-native deployments with hybrid model architectures for cost control.
Long-Term AI Partnership
Production monitoring, model drift detection, and continuous optimization. We maintain systems with the same rigor we build them. Observable, maintainable, and scalable.
Overall now you have 48.9% better system as compared to previous week
Internal Knowledge Systems
Secure RAG systems over your internal documentation, codebases, and proprietary data. Role-based access controls. Reduced hallucinations through grounded retrieval.
Technical Architecture Review
Deep-dive sessions with your engineering team. Evaluate LLM selection, infrastructure choices, and cost projections. No sales pitch—just technical clarity.
TechnicalOutcomes
Production-level results for engineering teams who need systems that actually work in the real world.
Controlled Inference Costs
Hybrid LLM architectures that route queries intelligently. Use smaller models for simple tasks, premium models only when needed. Predictable monthly spending.
Reduced Hallucinations
RAG pipelines grounded in your actual data. Source citations for every response. Confidence scoring to flag uncertain outputs. Trustworthy AI your team can rely on.
Observable & Monitored
Full observability stack: latency metrics, token usage tracking, error rates, and model performance dashboards. Know exactly what your AI systems are doing.
Let's discuss
your architecture
30-minute technical call. No sales pitch. We'll review your current stack and discuss realistic implementation paths.