Nominal
by Nominal
The data and AI platform that drags hardware testing out of Excel, MATLAB and PDFs
Nominal is a data and AI platform for hardware engineering, unifying telemetry, logs, video and simulation output from physical test campaigns into one analysable system. It serves aerospace, defence, energy, robotics and manufacturing teams, and its customers include the U.S. Air Force, Anduril and Shield AI. The company reached a $1B valuation in March 2026.
Nominal is a data and AI platform for hardware engineering - the test, telemetry and analysis layer for teams building aircraft, satellites, defence systems, robots, reactors and vehicles. Founded in 2022 by Cameron McCord and a team drawn from Anduril, Lockheed Martin and Palantir, and headquartered in Los Angeles with offices in Austin, New York and elsewhere, it sells against a status quo its CEO describes bluntly as 'Excel, MATLAB, PDFs - old pieces of software that have not kept pace.' The product is three pieces. Nominal Core is a secure cloud workbench that ingests telemetry, logs, video and simulation output from instrumented test rigs, structures it automatically, and gives engineers dashboards, automated checks and shareable records across an entire campaign. Nominal Connect runs at the edge for hardware-in-the-loop automation, turning Python scripts into operator-ready applications for repeatable test sequencing, and works fully offline in air-gapped facilities before streaming results back to Core. Nominal Instro is an open-source Python instrumentation library. Deployment covers AWS, Azure, on-premise and air-gapped environments, which is what makes it usable inside classified defence programmes. Customers include the U.S. Air Force, Anduril, Shield AI, Regent, Hermeus and Scout AI; the company says four of the five largest U.S. defence primes are customers, and reports roughly 60 customers and 7x ARR growth in 2025 across 135-150 staff. In an Anduril case study, unifying test analysis cut review time from over five hours to near real-time across more than 300 engineers. Nominal raised a $75M Series B led by Sequoia Capital in June 2025 and an $80M Series C at a $1B valuation led by Founders Fund in March 2026, then acquired Fid Labs in April 2026 to add AI agents purpose-built for hardware engineering workflows.
VPs of Test and Evaluation at hardware programmes - aerospace, defence, energy, robotics - whose senior engineers are spending their weeks reconciling telemetry in spreadsheets instead of interpreting it.
Test data from every rig, sensor and simulation lands in one queryable system, turning multi-hour post-test review into near real-time analysis.
At a Glance
- Category
- Data & Analytics
- Pricing
- Contact for pricing
- Target Market
- VPs of Engineering, Test and Evaluation Leads, CTOs, Systems Engineers, Defence Program Managers
- Deployment
- Cloud-first, Self-hosted, Hybrid, Edge-first, Multi-cloud
- Founded
- 2022
- Headquarters
- Los Angeles, United States
- Team Size
- 51-200
- Customers
- ~60 customers, including four of the five largest U.S. defence prime contractors
Key Features
- ✓Nominal Core unified data workbench
Ingests telemetry, logs, video and simulation output into one structured store so engineers analyse a campaign rather than assemble it.
- ✓Nominal Connect edge automation
Turns Python test scripts into operator-ready applications in minutes, sequencing hardware-in-the-loop runs at the test stand itself.
- ✓Full offline and air-gapped operation
Connect runs where the hardware lives with full capability offline, which is a hard requirement in classified defence facilities.
- ✓Nominal Instro open-source library
An open Python instrumentation library for hardware test, lowering the integration cost of getting sensor data into the platform.
- ✓Multi-environment deployment
Runs on AWS, Azure, on-premise infrastructure and air-gapped networks, so procurement is not blocked by a cloud-only architecture.
- ✓AI analysis layer from the Fid Labs acquisition
April 2026 acquisition adds hardware-native AI agents and an AI Analyst for contextual analysis across datasets without manual compilation.
Capabilities
Use Cases
- •Post-test review acceleration
Anduril used it to unify test analysis across autonomous vehicle programmes, cutting review from over five hours to near real-time for 300+ engineers.
- •Hardware-in-the-loop test automation
Engineers convert Python scripts into operator-run applications so a repeatable test sequence does not need its author present.
- •Cross-campaign trend analysis
Compare sensor behaviour across many runs and builds to catch drift that no single test report would ever surface.
- •Classified programme telemetry
Air-gapped deployment lets defence programmes run the full analysis stack inside facilities with no outbound network path.
- •Consolidating legacy spreadsheet workflows
Replaces the Excel, MATLAB and PDF pipeline the CEO identifies as the industry default with one versioned, queryable data layer.
Ideal For
Best For
- ✓Aerospace and defence test and evaluation programmes running instrumented ground and flight campaigns
- ✓Hardware-in-the-loop automation where Python test scripts need to become repeatable operator-run procedures
- ✓Air-gapped and classified facilities that need full analysis capability with no cloud connectivity
- ✓Robotics and autonomous vehicle programmes correlating telemetry, video and simulation across many test runs
- ✓Energy, nuclear and satellite operators replacing bespoke in-house telemetry stacks and spreadsheet reporting
Not Ideal For
- ✗Pure software organisations - this is instrumented physical-hardware telemetry, and a team without test rigs and sensors has nothing to feed it
- ✗Small hardware startups on a self-serve budget; there is no published pricing anywhere, deployment spans cloud and air-gapped environments, and the customer list is dominated by defence primes and well-funded programmes, which is not a low-touch motion
- ✗Buyers who need public third-party validation before purchase - Nominal carries no G2, Capterra or TrustRadius presence, so diligence means reference calls rather than review scores
- ✗Teams needing published compliance attestations up front; the company's public site names no SOC 2, ITAR or FedRAMP certification, so that has to be established in the sales process
Integrations
Deployment
Market & Ratings
~60 customers, including four of the five largest U.S. defence prime contractors
Market Analysis
Pros
- ✓Covers the whole loop - edge acquisition via Connect, cloud analysis via Core, and an open-source Python instrumentation library - rather than only one slice
- ✓Air-gapped and on-premise deployment is fully supported, which is the gating requirement for classified defence work most SaaS analytics tools cannot meet
- ✓Demonstrated outcome at scale: Anduril's test review dropped from over five hours to near real-time across 300+ engineers
- ✓Strong commercial validation - 7x ARR growth in 2025, roughly 60 customers, and an $80M preemptive Series C at a $1B valuation eight months after the Series B
Cons
- ✗No published pricing at all, no free tier and no trial, so evaluation requires a sales cycle before you can even estimate cost
- ✗No presence on G2, Capterra, TrustRadius or PeerSpot, and no substantive Hacker News or Reddit discussion, so there is effectively no independent practitioner review of the product to read before buying
- ✗The public site names no security or compliance certifications - no SOC 2, ITAR or FedRAMP claim appears - which is a conspicuous gap for a vendor selling into defence and means diligence has to establish it directly
- ✗Heavy concentration in aerospace and defence: four of five top U.S. primes are customers, which is excellent validation in that vertical and thin evidence for anyone outside it
- ✗The AI layer is brand new - the Fid Labs team joined in April 2026 and the AI Analyst was still described as launching soon, so the 'AI platform' positioning is ahead of shipped capability
Pricing
Enterprise
Contact for pricing
- ✓Nominal Core cloud workbench
- ✓Nominal Connect edge automation
- ✓AWS, Azure, on-premise or air-gapped deployment
- ✓Open API and SDKs
Nominal publishes no list pricing at any tier - there is no free plan, no trial and no self-serve signup, and every engagement runs through a sales conversation. That is consistent with the customer profile: defence primes, the U.S. Air Force and programme-scale aerospace teams buying air-gapped or on-premise deployments, where scope, classification level and integration work dominate the contract value rather than seat count. Expect a programme-level annual commitment rather than per-user licensing, and budget separately for the instrumentation integration that any telemetry platform requires.
Security & Compliance
Connect
Sources
This page was written from 5 sources, 4 on domains other than nominal.io.
- 1.nominal.io — nominal.iovendor
- 2.prnewswire.com — nominal raises 75 million led by sequoia capital to moderniz
- 3.tbpndigest.com — nominal raises 80m at 1b valuation to bring hardware testing
- 4.globenewswire.com — nominal acquires fid labs to bring ai to the full hardware e
- 5.sequoiacap.com — physics gets a vote nominal cofounders on hardware developme
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