About the session
Every team has a list of things AI should be doing for them. Most are still waiting. Not because the technology isn't there — but because building agents that actually work in production has required engineering resources, long timelines, and a tolerance for things breaking in ways you can't see.
Agent Studio changes that equation. It's DevRev's end-to-end environment for building, testing, deploying, and observing AI agents — without needing to write a line of code to get started. Agents built in Agent Studio aren't generic bots. They run on Computer Memory, which means they understand your customers, your product, your tickets, and your team's history from day one. The result: agents that don't just answer questions — they take action, with full traceability and human-in-the-loop controls when it matters.
In this session, we go inside the Studio. You'll see what it actually takes to move an agent from a blank canvas to something running in production — the decisions that matter, the controls that give you confidence, and the architecture that makes agents genuinely useful rather than just impressive in a demo.
You'll walk away knowing:
- What separates agents that work in production from ones that stall in pilot.
- How to build, test, and deploy an agent in Agent Studio — and what each phase of that lifecycle looks like in practice.
- Why context is the hard problem in agent-building, and how Computer Memory solves it in a way standalone builders can't.
- What "human in the loop" actually means when it's built into the platform — not bolted on as an afterthought.
Agenda
Production agents versus stalled pilots
Build, test, and deploy in Agent Studio
Computer Memory and business context
Human-in-the-loop controls
