Airside provides an agentic infrastructure that links legacy aviation data to mission‑critical flight and regulatory operations, enabling airlines and travel firms to integrate AI safely and efficiently.
Funding
Funding not disclosed
Founders
Product
Problem
Airlines and travel companies rely on legacy aviation data systems that are fragmented and not designed for modern AI integration, creating risks of bias, regulatory non‑compliance, and unpredictable behavior when deploying large language models in mission‑critical operations.
Solution
Airside offers an agentic infrastructure that securely bridges legacy aviation data with AI-driven flight and regulatory workflows. The platform embeds automated bias detection and EU AI Act compliance checks, ensuring that personal data is protected and models do not leak sensitive information. Continuous risk assessment monitors LLM outputs in real time, preventing unsafe agent actions from reaching production. By providing a curated library of over 6,000 aviation‑specific AI use cases and expert technical advisory services, Airside helps organizations adopt generative AI safely and avoid the common pitfalls that cause many projects to fail.
Target Audience
Primary customers are airlines, travel management firms, and aviation regulatory agencies that need to incorporate AI into safety‑critical operations while maintaining compliance and data security.
Features
- Proprietary bias‑detection framework that automatically evaluates AI models against aviation‑specific fairness criteria
- Built‑in EU AI Act and GDPR compliance modules that audit data flows and prevent personal data leakage
- Real‑time risk assessment engine that monitors LLM behavior and flags anomalous outputs during flight and regulatory processes
- Seamless integration layer that connects legacy aviation databases to modern AI pipelines without extensive re‑engineering
- Library of 6,000+ pre‑validated AI use cases covering flight planning, maintenance, crew scheduling, and regulatory reporting
- Technical advisory and board‑level expertise to guide safe AI deployment and governance in aviation contexts