For years, we've heard bold claims about how AI will transform work—creating visions of virtual assistants that magically automate away digital drudgery. Yet organizations experimenting with AI agents have encountered a sobering reality: most agents only work sometimes, failing to deliver the reliability needed for mission-critical workflows.
This challenge has been at the heart of our work since establishing the AGI Lab a year ago. In that time, we've made a lot of progress—first launching Nova Act as a research preview and later introducing an IDE extension to streamline the agent building process.
Which brings us to today: Nova Act is now generally available as a service on AWS for building and managing highly reliable AI agents at scale. Nova Act provides the fastest and easiest path to build and manage fleets of agents that are truly enterprise-ready, with customers achieving 90% reliability on UI-based workflows, like updating a customer record in a CRM system. We’ve also added new features like a no-code playground and human-in-the-loop oversight as well as preview capabilities like tool calling to accelerate builders throughout their journey. Our endgame: deliver trusted teammates for business-critical work.
Reliable agents at scale
Think of an AI agent that submits perfectly formatted bug reports across multiple repositories, updates data in 87 different tools (yes, the ones that don’t have APIs), and even orders celebratory pizza when your team hits a major milestone with everyone's preferred toppings. That's what Nova Act can help you build: highly reliable agents that excel at automating routine browser-based workflows that previously required human attention.
Nova Act prioritizes what developers and users actually need: reliability . Our user research shows that reliability is the critical factor preventing broader agent adoption in enterprise environments. Nova Act achieves high reliability through a fundamentally different training approach. Powered by a custom Nova 2 Lite model, Nova Act has state-of-the-art browser-use capabilities—performing better than other models on benchmarks like WorkArena and REAL Bench V1 and V2.
Unlike other offerings that bolt together separate components, we train the model, SDK, orchestrator, and browser controllers as a single unified system. By training all components together as one system, Nova Act achieves the reliability that's missing when models and tools are developed separately and combined later. To deliver this tightly integrated performance, we train our custom Nova model using reinforcement learning in synthetic environments called RL gyms that simulate real-world tools like CRM systems, travel sites, and project management tools. Nova Act learns in these replica environments via trial and error, like how a chess-playing AI gets to grandmaster status by playing against itself in a chess simulator ad nauseam. To help visualize this, our team built Nova Act Gym, which provides a sanitized set of demo environments akin to our RL gyms.
Example of Amazon Nova Act's reinforcement learning (RL) gyms:
Built for developers who ship
Great models aren't enough. Developers need a streamlined path from ideation to production. Nova Act delivers exactly that: a complete solution that dramatically simplifies agent development while enabling you to achieve enterprise-grade reliability.
The journey starts in Nova Act Playground, where you can prototype agents in minutes using natural language descriptions of your workflow. There's no downloading or complex configuration required—just describe what you want to automate and start testing immediately.
Once you've established a proof of concept, you can use the Nova Act extension to rapidly refine your agent in IDEs like VS Code, Cursor, or Kiro using an intuitive mix of natural language and Python, giving you precisely the control you need. The notebook style coding interface and embedded browser testing environment enable immediate iteration— catching issues before they reach production through live debugging. What you build locally is what you'll deploy—no translation layer, no surprises.
When you're ready to scale, just click "deploy" in the extension and it will use familiar AWS services to deploy to AWS. We've added a simple command-line tool to pair with the Nova Act SDK as well as a Nova Act console on AWS to round out our developer toolkit, so you can move from prototype to production in a few commands.
After deploying agents to production, you can use the Nova Act Console in AWS to manage activity and review past workflow runs—keeping you in control without the overhead of constant supervision. The end result? A dramatically streamlined agent builder experience where you can stay focused on business outcomes rather than wrestling with complex agent infrastructure.
From Cars to Space: How customers use Nova Act today
The best validation isn't just benchmarks—it's what happens when real developers use Nova Act to solve real problems. Here's what customers are saying about their experience building agents:
From brittle to battle-tested: How Sola Systems achieved high reliability for customers
Sola, a rapidly growing startup backed by a16z and Conviction, provides an agentic process automation platform for enterprises around the world. By integrating Nova Act, Sola has been able to scale their workflow offering while maintaining high reliability across business-critical workflows in healthcare, logistics, and other major industries. "Our customers were spending hundreds of hours per week on repetitive tasks across dozens of systems. Legacy automations broke every time something updated, and custom integrations were too slow to build. Our vision has always been to put automation in the hands of people who actually understand the work, not just technical experts. With powerful models like Nova Act, that vision is now a reality," said Jessica Wu, Co-Founder and CEO of Sola. "Nova Act has been essential to making that work at enterprise scale. It’s given us the reliability, speed, and cost efficiency to handle business-critical processes running hundreds of thousands of times per month where errors aren't acceptable."
Enterprise scale at startup speed: How Hertz eliminated its QA bottleneck
Hertz's rental platform processes millions in daily bookings, making website reliability critical to their business. Using Nova Act, Hertz automated manual test cases for their core rental flows—creating, modifying, and canceling reservations—across both modern and legacy web applications. Through the Amazon Nova Act AWS Console, they can now manage these tests as workflows and monitor results in real time, protecting against revenue leakage from even brief website disruptions. "Quality assurance used to be our biggest bottleneck, but Nova Act helps solve that. What used to take weeks now takes hours, accelerating our shipping velocity by 5x and democratizing quality ownership to everyone in SDLC," said Mu Qiao, Sr Director of Software Engineering, Hertz. "The AI-powered automation catches issues before they impact our customers or revenue, better enabling our QA team to keep pace with development and deliver a higher-quality customer experience." Following this initial success, Hertz is expanding Nova Act's coverage across their entire test suite, including mobile applications and automated exploratory testing for comprehensive global coverage.
One script, hundreds of websites: How 1Password scaled secure authentication
1Password used Nova Act to simplify everyday tasks like logging in to web apps, helping users and organizations securely access the tools they rely on while reducing manual steps and potential risks. Because Nova Act is purpose-built for UI understanding, 1Password was able to get a single prompt working across hundreds of diverse websites. "Nova Act’s ability to understand and adapt to complex sign-in patterns opens new possibilities for how people and systems securely access the web," said Nancy Wang, SVP of Engineering at 1Password. "For 1Password, this means delivering the same trusted, human-like login experience our users rely on, now powered by AI and scaled across more environments. As AI becomes a participant in work, not just a tool, security and identity need to evolve with it. That’s where 1Password comes in: serving as the trusted security layer for human, machine, and AI identities.”
No code, no problem: How Amazon Leo automated UX testing
Amazon Leo is targeting zero critical customer bugs across its website and mobile products ahead of its satellite internet service launch. The core constraint: executing thousands of test cases during development across all customer-facing applications and backend services running on multiple platforms. Maintaining separate automation codebases consumes significant engineering capacity and slows down velocity. Amazon Leo leverages Nova Act's agentic test automation framework to eliminate this constraint. Test scenarios are written in natural language, and then executed automatically across web and mobile, through a hybrid execution model that delivers speed, consistency, and repeatability. Initial test runs execute agentically, capturing all the details, and subsequent runs replay deterministically three times faster than the agentic execution with zero AI costs. When UI changes occur, the system adapts automatically, eliminating manual updates that slow development. "At Amazon Leo, we're working hard to delight our customers when we launch our low-Earth orbit satellite-based internet service to customers across the world. That demands flawless execution across every customer touchpoint," said Raj Kizhakkekalathil, Director of Engineering at Leo Commerce. "Nova Act has transformed our quality assurance approach. What previously took weeks of effort to create a comprehensive set of automated test scenarios now happens in minutes. This fundamentally changes how we build and validate customer experiences from design through delivery."
The path forward: From tasks to teammates
Today's launch is a significant milestone, but it's just the beginning of our journey. Real work is collaborative, multi-agent, and multi-person. To simulate these dynamics, we're investing heavily in capabilities that will transform agents from tools that handle narrow tasks to true collaborators. We're laying the foundation for a future where AI agents are reliable enough to handle business-critical work, experienced enough to adapt to changing conditions, and humble enough to ask for help when they need it.
Test it yourself
Get started today at nova.amazon.com/act.
