Agentic AI, LLM engineering, and the models behind modern automation — multi-agent systems, LLM evaluation and comparisons, RAG, fine-tuning, AI infrastructure, security, and production AI engineering.
From the blog
Build an AI agent that detects when patients need medication refills, routes approval requests to providers, coordinates with pharmacies via NCPDP SCRIPT, and tracks prescription fulfillment end to end.
Build an AI agent that manages property inspection workflows, handles checklist tracking, categorizes issues from photos, and generates professional inspection reports.
Build an AI agent that aggregates neighborhood data, identifies market trends, scores investment opportunities, and generates comprehensive property market analysis reports.
Build an AI agent for public health departments that provides vaccination eligibility information, finds nearby clinics with appointment availability, and distributes outbreak alerts with actionable guidance.
Build an AI agent that aggregates restaurant reviews across platforms, performs sentiment analysis, generates contextual responses, and tracks trends to drive operational improvements.
Learn how to build a comprehensive ROI model for AI agent deployments, including cost modeling, savings calculation, productivity gains, and a practical formula that quantifies business value for stakeholders.
Build an AI agent for roofing companies that assists with damage assessment from photos, generates insurance claim documentation, manages insurance workflows, and schedules repair crews.
Build an AI agent that parses human-written runbooks, converts them into executable automation workflows with verification steps, handles edge cases, and supports safe rollback.
Learn how to architect a multi-tenant AI agent platform with proper service decomposition, tenant isolation, shared infrastructure, and API design patterns that scale from one customer to thousands.
