The company provides an integrated software platform that combines model‑based systems engineering with GPU‑accelerated multi‑physics digital‑twin simulations for airframe, propulsion, and avionics. It ingests telemetry, test logs, and maintenance data to deliver real‑time analytics, predictive‑maintenance alerts, and automated requirements traceability, and can be deployed on‑premise with air‑gap security or via cloud APIs that integrate with PLM, ERP, and C4ISR systems.
Funding
Funding not disclosed
Founders
Product
Problem
Aerospace and defense engineering programs often contend with fragmented data sources, limited simulation fidelity, and opaque performance metrics, making it difficult to predict system behavior and maintain mission‑critical reliability throughout the hardware‑software lifecycle.
Solution
The company delivers an integrated software platform that unifies high‑fidelity multi‑domain simulation, real‑time analytics, and lifecycle management for complex aerospace and defense systems. Leveraging model‑based systems engineering (MBSE) and digital‑twin technology, the platform runs GPU‑accelerated simulations of airframe, propulsion, and avionics subsystems to generate predictive performance data. An analytics engine applies statistical modeling and machine‑learning techniques to ingest telemetry, test logs, and maintenance records, producing actionable dashboards and automated alerts. Engineers can trace requirements through design, test, and operational phases, shortening iteration cycles and supporting certification compliance. The solution offers secure, air‑gapped on‑premise deployment alongside optional cloud processing, and integrates with existing PLM, ERP, and C4ISR tools via standards‑based APIs.
Target Audience
Primary customers are systems engineers, program managers, and test‑and‑evaluation teams at aerospace OEMs, defense contractors, and government acquisition agencies that require end‑to‑end performance analytics for mission‑critical platforms.
Features
- Model‑based systems engineering (MBSE) framework with built‑in digital twin generation for airframe, propulsion, and avionics subsystems
- GPU‑accelerated multi‑physics simulation engine supporting CFD, structural dynamics, and electromagnetic analysis
- Real‑time data ingestion pipeline that normalizes telemetry, test logs, and maintenance records for unified analytics
- Machine‑learning‑driven anomaly detection and predictive maintenance models with configurable confidence thresholds
- Interactive web‑based dashboard offering drill‑down visualizations, KPI tracking, and automated report generation
- Secure REST/GraphQL API layer for integration with PLM, ERP, and C4ISR command‑and‑control systems, compliant with DoD STIG requirements
- On‑premise deployment option with air‑gap support, encrypted data storage, and role‑based access control meeting NIST 800‑171 standards
- Automated requirements traceability matrix linking simulation outcomes to certification criteria and change‑management workflows