AI Workflows

Deploy a multi-agent AI system utilizing AutoGen 0.4 to automate hardware verification, analyze Cadence simulation logs, and pinpoint RTL bugs in complex semiconductor chip designs.

Architect a multi-agent AI system that processes healthcare claims autonomously, validates medical records using FHIR APIs, and detects fraudulent billing patterns with Qdrant hybrid search.

From deepfake regulatory pressure to a scalable detection architecture: this pipeline layers perceptual hash, audio-biometric, and LLM-forensics agents to score media and escalate high-risk claims and payments to human review.

A comprehensive guide to architecting a fully autonomous multi-agent pipeline capable of parsing, reviewing, and scoring legal contracts for risk using AutoGen 0.4 and Milvus.

Learn how to extract structured intelligence from complex PDFs, images, and scanned documents in real-time using cutting-edge OCR and LlamaIndex orchestration.

Automate enterprise churn prevention with stateful AI agents that analyze product telemetry and intervene in real-time.

Scale your e-commerce AI operations with distributed agentic swarms that optimize pricing strategies and manage inventory on the fly.

A deep dive into architecting an enterprise-grade autonomous software engineering pipeline. Learn how to combine AutoGen 0.4's multi-agent capabilities with SonarQube's Abstract Syntax Tree (AST) analysis to create a self-correcting loop that generates, audits, and fixes code without human intervention.

Cloud and LLM API costs can spiral out of control without constant monitoring. Learn how to deploy an autonomous FinOps AI agent that continuously analyzes AWS CloudWatch metrics, tracks LiteLLM usage, and automatically scales infrastructure or routes models to optimize enterprise spend.

Modern cyber threats outpace human response times. Discover how to build a distributed Cyber Threat Intelligence (CTI) gateway using CrewAI, where specialized autonomous agents monitor security feeds, analyze anomalous network patterns, and execute automated remediation hooks to isolate compromised systems instantly.

Embodied AI is moving out of the lab. This workflow shows how to wire a VLA model (vision frames in, natural-language commands in, low-level action tokens out) into a warehouse pick-and-place robot with real-time budgets, safety interlocks, and full telemetry.

Architect a LangGraph-powered orchestrator that polls real-time wholesale energy markets (PJM, ERCOT), forecasts prices, and time-shifts or migrates AI workloads to the cheapest, greenest compute region - including SMR-powered data centers.