AI agent architecture
Business-oriented agent flows with tools, memory, evaluation and operational boundaries.
Technical consulting
Applied AI with backend, data and operations judgment.
I help teams move AI, automation and cloud backend work from prototype to production.
RAG and enterprise knowledge
Retrieval pipelines, chunking, evaluation and observability for using internal knowledge responsibly.
Cloud backend and data
Microservices, Pub/Sub, BigQuery, APIs and reliable jobs underneath AI workflows.
Applied automation
n8n, Python and API integrations to reduce manual work while preserving traceability and human control.
How I work
Systems first, models second.
- Diagnosis
Understand the process, data, constraints, operating cost and risk before proposing AI.
- Architecture
Design APIs, agents, RAG, queues, monitoring and human checkpoints.
- Implementation
Build incremental integrations with testing, traceability and real operations in mind.
- Improvement
Measure quality, latency, cost and feedback to iterate with evidence.
Available for selected collaboration
If the workflow is complex, start by making it observable.
The best business AI usually starts with good data, clear limits and integrations the team can maintain.