Editor’s Brief1
Last Week, was part III in a series on the Shipbuilding “Crisis.” Find parts 1 and 2 Here and here
This week, back to company analysis with Nominal.
Special thanks to Co-Founder and CEO Cameron McCord for sitting down to chat all things Nominal.
Signal Brief: Nominal: The Test Infrastructure Layer for Modern Hardware
Nominal provides a unified software platform for testing, validating, and monitoring hardware systems across development and operational environments. Its platform integrates data from multiple sources into a single environment where engineers can analyze system performance and collaborate on validation workflows.
Origins & Vision
Founded in 2022, Nominal emerged from the realization that hardware innovation moves at the speed of test. Co-founder Cameron McCord, a former Navy Submarine Officer who went on to work at Anduril and Applied Intuition, partnered with Bryce Strauss, a Lockheed Martin spacecraft engineer, and Jason Hoch, a Palantir and Vercel veteran.
The founders recognized that manual data aggregation across hundreds of disparate sources is a primary obstacle to rapid hardware iteration. If it takes an engineering team five hours to review telemetry from a thirty-minute flight test, the learning loop is effectively broken.
Initially focused on telemetry visualization and analysis, Nominal now has two main products: Nominal Core, a unified environment for ingesting and analyzing test data, and Nominal Connect, which enables automation and data collection at test stands and field environments.
Early Air Force engagements validated the platform's approach. The company gained traction among next-generation defense contractors, including a large enterprise deployment with Anduril Industries that has since expanded into what the company describes as a de facto standard across Anduril's autonomous programs.
Key Takeaways
Testing infrastructure as a bottleneck. The U.S. is trying to build faster hardware, but its test infrastructure is still too fragmented, manual, and slow. Nominal is attacking that bottleneck directly.
The AFTC IDIQ a Major Win. Awarded a $53 million sole-source IDIQ contract to standardize data infrastructure across the Air Force Test Center's three Test Wings: the 412th (flight systems), 96th (weapons), and Arnold Engineering Development Complex (propulsion and hypersonics).
Edge-cloud architecture for classified environments. Nominal's platform runs locally on test infrastructure while synchronizing data to collaborative environments when connectivity allows
Tech Radar:
Credit: Nominal
Nominal Core — Unified Test Data Environment
Foundational data platform for hardware engineering teams. An all-in-one collaborative workspace that brings together telemetry, logs, video, and simulation results into a unified, searchable database.
Key Capabilities
Real-Time Data Consolidation: Ingest and process data from hundreds of disparate sources simultaneously, allowing teams to monitor system health and perform trend analysis in real-time.
Customizable Visualizations: Create high-fidelity dashboards, such as flight path visualizations for satellite constellations, without the need for custom frontend development.
AI Readiness and Data Cataloging: Use natural language queries to interrogate years of test history, such as asking the system to "plot the kinematics of the drone during every incident where engine temperature exceeded the nominal threshold".
Credit: Nominal
Nominal Connect — Edge Automation for Test Systems
The company's edge compute platform, designed to deploy on a factory floor, a remote launch pad, or an air-gapped facility and manage field operations in minutes.
Key Capabilities
Real-Time Hardware Interfacing: Reads from and writes to hardware instruments in real-time with deterministic timing, ensuring accurate data capture.
Python-First Test Apps: Leverages Python as a primary interface to build and deploy Python-based test apps to capture data and control hardware.
Air-Gapped and Offline Capabilities: Stores data locally and automatically syncs with Nominal Core for analysis once a secure connection is re-established.
Manufacturing Scalability: Enables the same test code to be used from prototype validation through to full-rate production
Market Signals
Funding & Growth
Total Funding: $182M+ across four rounds
Latest Round: $80M Series B-2 (March 2026)
Notable Investors: Sequoia Capital, Founders Fund, General Catalyst, Lux Capital, Lightspeed Venture Partners, XYZ Ventures, Haystack VC, Overmatch, PAX, PSP Growth
Valuation: $1 billion (March 2026)
Contracts & Government Traction
$53M sole-source IDIQ with the Air Force Test Center (April 2026), supporting AFTC’s component Test Wings as well as the broader Department
Phase III transition contract supporting the Navy's MQ-25 Stingray unmanned carrier aircraft program
Phase III transition contract with the Air Force Test Pilot School, following AFWERX Phase I and Phase II STTR with MIT, focused on flight test data analysis and AI-enhanced anomaly detection
Providing data backbone for DARPA’s CyPhER Forge program, which aims to revolutionize digital testing
Customer Impact (selected)
Adopted by four of the five largest global defense contractors
Shield AI: Data review time reduced from 6 hours to 30 minutes
Hermeus: First hypersonic flight completed in 7 months, an 80% reduction from projected timelines
Anduril: 18-month deployment described as reaching a tipping point as the de facto solution across autonomous programs
Mach Industries: Selected Nominal to run all test infrastructure
Looking Ahead
In 1943, Clarence “Kelly” Johnson and his Skunk Works team designed, built, and delivered the XP-80 in 143 days.
23 engineers and 105 production workers. They worked under secrecy in a guarded shop and a circus tent on Lockheed’s Burbank facility with No modern computing, digital test infrastructure, or enterprise data stack.
And they still delivered seven days ahead of schedule.
How? In part because World War II was raging and failure wasn't an option. But Johnson also built an operating system for speed. His 14 Skunk Works rules remain as applicable today as they were then:
Keep the team small, minimize reporting, keep testing close to the people doing the work, agree on specifications early, and be explicit about what the team will not comply with and why.
In short, remove everything that does not contribute to the outcome, and protect the people doing the actual work from the overhead that accumulates around them.
However, modern defense programs face a problem Johnson never had to solve. A modern F-35 test event generates more raw data than an entire program produced in Johnson's era. Telemetry, logs, video, sensor data, maintenance records, and historical artifacts measured in terabytes.
And the worst part is more data hasn’t made us better decision makers.
I recently sat in a meeting about a “mechanical issue” that has never occurred in 2.2 million flight hours across the F/A-18 fleet. When I asked why we were still talking about it, the answer was that we needed to continue to monitor it because we just couldn't be certain.
Perhaps it will occur in the future. But If 2.2 million flight hours is not enough to inform a decision, the problem has nothing to do with the amount of data. The problem is whether the organization has the tools, incentives, and authority to act on what the data already says.
This is where Nominal becomes interesting.
Nominal does not solve the institutional problems that have made defense acquisition slow. It doesn’t fix requirements creep, budget instability, risk aversion, or the incentive structure that rewards process compliance over fielded capability.
But it does attack one of the most expensive forms of hidden drag in modern hardware programs: the gap between a test event and an actionable conclusion.
A small team running a tight program should not need a dedicated backend staff just to understand what its hardware did last Tuesday. A test pilot supporting multiple programs shouldn’t have to wait weeks for a question can be answered in minutes. And a contractor shouldn’t be able to pass endless data overhead back to the government.
Nominal will deliver faster testing but the real value is that it forces attention back toward the failures that actually matter: the ones breaking aircraft, delaying programs, and killing people.
Challenges
Data integration risk. Nominal must continue to normalize telemetry, logs, video, and test artifacts across legacy systems, classified environments, and disconnected ranges.
Institutional follow-through. The engineers who feel the pain will understand the value immediately. The organizations that control procurement budgets may not. Faster analysis does not automatically produce faster decisions.
Mission-critical scaling. Becoming default test infrastructure means higher expectations for uptime, security, and auditability without losing the speed that justified adoption in the first place.
Bottom Line:
Kelly Johnson ran his operation on the principle that a small number of good people, given real authority and freed from unnecessary process, will outperform a large team buried in coordination overhead every time.
Nominal is building the infrastructure that makes that possible in a modern test environment.
And the question of whether a component has ever failed in two million flight hours shouldn’t require another meeting.
1 The views expressed in this newsletter are my own and do not represent the views of the U.S. Navy, Department of Defense, or any government agency. Mention of companies, technologies, or products is not an endorsement or recommendation. The content is for informational purposes only and should not be considered investment advice.