Nominal provides a unified platform that integrates real-time observability, advanced data infrastructure, and automated validation logic for mission-critical engineering tasks. This solution enables hardware teams to streamline testing processes, reduce operational costs by 400%, and enhance the reliability of their systems.
Funding
$27.5M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Hardware engineering teams often struggle with siloed data and disparate tools across development, testing, and operations, leading to inefficiencies and increased operational costs. Integrating and synchronizing data from various sources, such as test stands, embedded software, and flight tests, is complex and time-consuming. This lack of a unified data stack hinders the ability to quickly identify trends, detect anomalies, and diagnose root causes, ultimately slowing down the engineering process.
Solution
Nominal provides a unified industrial data stack that integrates real-time observability, advanced data infrastructure, and automated validation logic into a collaborative workspace. The platform enables hardware teams to synchronize high-scale data from hundreds of sources into named, searchable assets using a native time-series database, throttled InfluxDB connector, and integrated Python client. Nominal facilitates the tracking of trends with continuous metrics and synchronized configurations, including a historical data catalog and automatically computed KPIs. The system detects anomalies early with validation logic and provides a dedicated triage workflow integrated with Slack and autoscaled stream processing. Nominal also accelerates root cause diagnosis by enabling rapid investigation and sharing of multi-modal data with collaborative annotations and a units-aware compute engine.
Target Audience
The primary target audience includes hardware engineering teams in aerospace, defense, and automotive industries focused on mission-critical engineering tasks, including flight testing, test stand operations, embedded software testing, space operations, and secure test ranges.
Features
- Native time series database for synchronizing high-scale data
- Throttled InfluxDB connector for integrating with existing data sources
- Integrated Python client for custom data ingestion and analysis
- Historical data catalog for tracking trends over time
- Automatically computed KPIs for real-time performance monitoring
- Configuration management for synchronizing test parameters
- Dedicated triage workflow for anomaly detection and resolution
- Integration with Slack for real-time notifications
- Autoscaled stream processing for handling high-volume data
- Collaborative annotations for shared insights
- Units-aware compute engine for accurate calculations
- Git-based version control for validation logic
- Low or no-code logic editor for easy rule creation
- Integrated unit testing for validation engine optimization
- AWS GovCloud, single-tenant, and on-premise deployment options