Building an AI agent is the easy part. Keeping it reliable, observable, and cost-effective in production is where most teams struggle.

Next week, our own @lakshyaag joins speakers from Nebius and LangChain for a live session where they’ll build a compliance audit AI agent based on a real case study.

The session covers:

➤ Adding production capabilities in a real agent stack ➤ What the cost and quality tradeoffs look like between open-model architecture and a frontier-model approach ➤ How to build with LangChain Deep Agents, Tavily and NVIDIA Nemotron 3 Ultra without model fine-tuning

If you’re moving from prototype to production, this one’s worth a bit of your Tuesday.

Register here:

Architecture behind production AI agents

Source: https://nebius.com/events/webinar-architecture-behind-production-ai-agents Most teams can build an AI agent. Far fewer can deploy one that is reliable, observable, and cost-effective in production.

In this live session, we’ll build a compliance audit AI agent based on a real-world case study using the Nebius Agents Blueprint. Then we’ll replace the standard agent configuration with LangChain Deep Agents optimized for NVIDIA Nemotron 3 Ultra and demonstrate how to achieve frontier-level quality at roughly one-tenth of the cost.

What you’ll learn

• Deploy an AI agent using theNebius Agents Blueprint
• Build withLangChain Deep Agents,TavilyandNVIDIA Nemotron 3 Ultrawithout model fine-tuning
• Compare an open-model architecture with a frontier-model approach to understand the trade-offs in quality and cost
• Add production capabilities including grounding, retrieval, observability, and simulation testing with Tavily, Pinecone, LangSmith, and Snowglobe
• Reproduce the complete implementation using the architecture and code shared during the session

Who should attend

• AI/ML engineersbuilding agents who want a production-ready architecture
• Platform and infrastructure teamsresponsible for deploying AI systems
• Technical leadersevaluating open-model agents versus closed frontier models for cost, control, and reliability
• Teams moving from prototypes to production and looking for practical architecture patterns

Devang Sachdev

Vice President of Strategy

Tikhon Roshchupkin

Senior Program Manager

Srimanth Tangedipalli

Partner Engineer at LangChain

Lakshya Agarwal

Forward Deployed Engineer at Tavily

Fill out the form to register and get the recording

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