Real-Time Multi-Modal Fact-Checking with Gemini and Kafka
Build a real-time fact-checking architecture capable of analyzing live video and audio streams using Kafka and Gemini.
Step-by-step production AI workflow architectures, event loops, and agent orchestration for builders.
Build a real-time fact-checking architecture capable of analyzing live video and audio streams using Kafka and Gemini.
Automate the ingestion and synthesis of scientific research papers using a multi-agent system orchestrated by Airflow.
NHIs now outnumber human identities ~144:1 in cloud-native environments. This workflow automates the full agent identity lifecycle: least-privilege scoped provisioning, automatic rotation, and de-provisioning, backed by a central identity store.
CUA agents operate the real GUI instead of emulating an API. Build a production workflow that captures screenshots, decodes action tokens (click, type, wait, validate), and guards every step with accessibility-tree validation and HITL checkpoints.
Accounts payable is now the top enterprise agent deployment. Architect a PydanticAI + Temporal workflow that does three-way invoice matching (PO, receipt, invoice), resolves exceptions with LLM judgment under deterministic business rules, and reconciles payments with an audit trail.
Make long-running agent workflows crash-proof: LangGraph 1.x checkpoints resume interrupted runs, while Temporal handles durable scheduling and human-in-the-loop approval gates that pause and resume safely.
Ship trustworthy agents by measuring what matters: a CLEAR-based evaluation harness that runs your agent dozens of times, computes pass@k consistency, and gates deploys on reliability scores.
Architect a self-updating market intelligence pipeline where Firecrawl MCP scrapes the web, LangGraph orchestrates analyst agents, and Qdrant vector memory prevents redundant re-research across weekly sweeps.
Build a hyper-efficient, edge-native AI architecture where TinyML models detect local anomalies, triggering cloud-based LangGraph agents via MQTT to dynamically reconfigure IoT fleets and deploy self-healing patches.
Deploy a real-time, event-driven multi-agent system that ingests global supply chain data via Apache Flink, predicts disruptions using LLMs, and autonomously negotiates alternate sourcing with suppliers via CrewAI.
Architect a robust, self-healing automated QA testing pipeline using multi-agent architectures to intelligently navigate DOM changes, dynamically generate assertions, and validate complex UI flows with zero human intervention.
Construct a high-performance, real-time video processing pipeline that ingests live streams, extracts keyframes with FFmpeg, and uses Gemini 2.5 Flash Vision to generate instant highlights and summaries.