Enhanced Radar provides end‑to‑end, aviation‑grade AI training datasets of pilot‑controller communications, handling everything from live ATC radio capture to in‑house labeling and quality assurance. Their large, diverse, and safety‑certified datasets are delivered in ready‑to‑use formats, enabling AI developers, OEMs, airlines, and air traffic management organizations to build more accurate speech‑recognition and decision‑support systems for aviation.
Funding
$500K 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.
1OFounders
Product
Problem
Developing reliable AI systems for aviation requires large, high-quality datasets of pilot‑controller communications, but existing datasets are often limited, noisy, and not built to aviation safety standards. This hampers the training of models for tasks such as speech recognition, intent detection, and decision support in air traffic control.
Solution
Enhanced Radar addresses this gap by producing end‑to‑end, aviation‑grade AI training datasets for pilot‑controller communications. The company controls the entire data pipeline—from field collection of live ATC radio streams to in‑house labeling and rigorous quality assurance—ensuring the resulting datasets are diverse, large, and meet strict safety‑critical standards. These train‑ready datasets are delivered in formats optimized for machine‑learning workflows, enabling developers to build more accurate and reliable aviation AI applications without the overhead of data acquisition and cleaning.
Target Audience
Primary customers are AI developers, aerospace OEMs, airlines, and air traffic management organizations building speech‑based or decision‑support systems for aviation operations.
Features
- Full‑stack data pipeline covering capture of live ATC radio, transcription, annotation, and validation
- Aviation‑specific quality metrics and safety‑grade labeling guidelines
- Diverse coverage of communication scenarios, aircraft types, and operational environments
- Large-scale dataset volumes designed for deep‑learning model training
- Ready‑to‑use data formats compatible with common AI frameworks and cloud storage solutions