Meet Nominal Analyst, the agent for hardware teams

Ambition is timeless. Tools are not.

The engineers building the physical world have never lacked ambition. They're building the systems that will fly, launch, orbit, dive, and power the next generation of industry. But the tools used to test and understand those systems haven't kept pace with advances in software.

We started Nominal to change that.

We've spent years building the infrastructure connecting hardware test data with the engineering context and tools needed to make sense of it. Built alongside customers, this foundation enables agents to move beyond generic assistance and do meaningful work within the engineering environment.

Today, we're introducing Analyst, Nominal's first purpose-built AI agent, now available in public preview. Built on this foundation, Analyst brings the power of our platform to a new generation of tools for hardware engineering.

Working alongside these teams, we're proud to deliver tools that multiply what they can accomplish, so that the extraordinary software acceleration underway brings the next generation of hardware along with it.

Accelerating the whole program

Across design iterations, production acceptance, and monitoring of assets in operation, progress repeatedly depends on what a team can establish through test. Every investigation that takes weeks instead of days delays not just one decision, but the work of everyone waiting on it.

Analyst helps engineers find relevant data, build analytical views, search engineering files, and execute computations within Nominal. Instead of manually piecing together the information and tools needed to investigate a problem, engineers can use Analyst to find relevant context, examine evidence, and test hypotheses. They can inspect the results, challenge assumptions, and direct the next steps.

The impact extends beyond any single investigation. Bringing a failure to a sound conclusion sooner can release weeks of work for everyone downstream. As those gains compound across successive investigations and design cycles, teams can test more ideas, learn faster, and realize more of their ambition.

This is why we're building a Hardware Intelligence Platform: to help engineering teams turn complex hardware data into actionable insight, make better-informed decisions with greater confidence, and move their programs forward faster.

Putting Analyst to work

Analyst is designed to help engineers spend less time navigating the complexity of their engineering environment and more time understanding what their systems are telling them.

At Wisk Aero, Staff Systems Engineer Cooper Diamond works on battery-system verification. Changes to interface-control documents require updates to report automation and monitoring. Analyst is helping him move through that work faster:

Analyst has added a huge improvement to our iteration speed.

Copper Diamond, Wisk Aero

Staff Systems Engineer

At Mach Industries, Flight Test Engineering Intern Spencer Sharpe used Analyst to navigate unfamiliar flight data:

As a new employee, Analyst made it very easy to navigate the large dataset and understand which variables were most useful for analyzing certain situations and root causing issues.

Spencer Sharpe

Flight Test Engineering Intern, Mach Industries

These are early examples of what's possible when agents operate within an environment specifically built for engineering work. The goal isn't simply to generate an answer, but to help engineers navigate complex data, bring relevant context together, and move their investigations forward.

Learning across every system

Today, Analyst helps engineers work through analytical tasks. Over time, we see the opportunity to connect those investigations into a much larger source of organizational knowledge.

An investigation into a hardware failure can draw on everything an organization has learned from building, testing, and operating its systems. An anomaly on one aircraft could be examined against configurations, production history, and operating conditions across thousands of others.

As engineering environments become more connected, insights from one investigation can inform the next. A finding can improve a design, inform a production acceptance check, or help identify aircraft in operation that warrant attention. Subsequent tests and field data can help establish whether the change worked. What an organization learns from one system can inform decisions across every system where that knowledge applies.

We want that capacity to grow with each organization we serve. More hardware in operation gives engineers more evidence to learn from, more investigations leave more useful methods behind, and a team preparing its next generation of systems can draw on the experience of everything it has already built.

This is the promise of a Hardware Intelligence Platform: connecting data, context, and analytical tools so engineering teams can build on what they learn over time.

The next revolution

Engineering organizations will ultimately be able to develop, test, and deploy an order of magnitude more hardware, an order of magnitude faster.

Realizing that ambition requires more than general-purpose AI. It requires agents that can investigate anomalies across enormous volumes of test data and connect measurements to the contextual documents, diagrams, software, and decisions that explain a system. It requires an underlying architecture that gives agents access to the data and tools they need to do meaningful work. And it requires an open platform, so customers can bring their own agents, specialized models, and hard-earned methods into the same engineering environment.

We've been building toward this future for four years. Analyst brings that foundation to life in a new way, and we'll keep learning alongside our customers and expanding what's possible.

The people building these systems have always been willing to take on extraordinary challenges. Our responsibility is to give them tools that match the scale of their ambition. The years they recover help bring their technology into the world faster and make each further iteration more possible.

We see the next industrial revolution taking shape in our customers' daily progress, and we feel fortunate to be part of it. With Analyst's public preview, we're opening the next chapter of that effort.

We look forward to seeing what engineering teams accomplish with Analyst, and to making it better every day.

Explore Nominal's approach to agentic engineering investigations (opens in new tab)