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 a complete document processing system with automated ingestion, AI-powered extraction and classification, a human review queue for quality assurance, and structured data export.
Build a complete help desk system with AI ticket classification, automatic agent assignment, SLA tracking, escalation workflows, and a reporting dashboard for support team performance.
Build an end-to-end AI sales development representative that ingests leads, generates personalized outreach, manages follow-up sequences, and syncs activity to your CRM using agent orchestration.
Build an AI-powered code review system that receives GitHub webhooks on pull requests, analyzes diffs with an LLM agent, posts inline review comments, and tracks code quality scores over time.
A full project walkthrough for building a production-grade customer support platform using multi-agent orchestration, tool integration, deployment pipelines, and real-time monitoring.
Build a unified AI agent backend that serves conversations across web chat, Slack, and WhatsApp using a channel abstraction layer, shared agent logic, and centralized conversation storage.
Build a production SaaS platform where multiple tenants can create and deploy AI agents with tenant isolation, a visual agent builder, usage tracking, and Stripe-based usage billing.
Build a complete retrieval-augmented generation knowledge base with document ingestion, semantic search, a chat interface for users, and an admin panel with analytics for managing content.
Build a production voice AI call center featuring WebRTC-based agent pools, real-time call monitoring, concurrent call handling, and a post-call analytics dashboard with sentiment and intent scoring.
