# DGCA Develops AI-driven eGCA 2.0 for Aviation Oversight > Source: > Published: 2026-06-20 15:08:07.190127+00:00 # DGCA Develops AI-driven eGCA 2.0 for Aviation Oversight According to tender documents reviewed by The Hindu BusinessLine, India's Directorate General of Civil Aviation (DGCA) is working on a next-generation **eGCA 2.0** platform that would incorporate **artificial intelligence (AI)**, **machine learning (ML)**, **blockchain**, decision-intelligence and **predictive surveillance** capabilities. The tender seeks a Technology Project Management Unit (Tech-PMU) to support implementation and places emphasis on regulatory-technology solutions, cybersecurity and data-protection compliance, per The Hindu BusinessLine. The documents describe use cases including decision-intelligence solutions and predictive surveillance tools intended to strengthen regulatory oversight, streamline approvals and enhance monitoring mechanisms. #### What happened According to tender documents reviewed by The Hindu BusinessLine, the Directorate General of Civil Aviation (DGCA) is developing a next-generation **eGCA 2.0** platform intended to integrate **AI**, **ML**, **blockchain**, decision-intelligence and **predictive surveillance** capabilities. The tender documents state the regulator is seeking a Technology Project Management Unit (Tech-PMU) to support implementation and integration work. The same documents emphasise cybersecurity frameworks and data-protection compliance as core requirements for the proposed system. #### Technical details According to the tender materials cited by The Hindu BusinessLine, the proposed framework will focus on application framework design, integration planning and risk management while incorporating decision-intelligence and predictive-surveillance modules. The reporting describes these modules as intended to support approvals, monitoring and oversight rather than naming specific models, vendors or technical stacks. Editorial analysis - technical context: Regulatory deployments that combine predictive surveillance and decision-intelligence commonly rely on time-series anomaly detection, risk-scoring pipelines and explainability layers for auditability. Blockchain is often proposed for immutable provenance and audit logs, though it adds integration and scalability trade-offs. For practitioners, key technical workstreams typically include data ingestion from heterogeneous flight and maintenance systems, model validation, explainability tooling and secure key management for any ledger-based components. ### Industry context: Public reporting frames this effort as part of a broader push toward digital regulatory technology in safety-critical sectors. Observed patterns in comparable government projects include long procurement cycles, a focus on compliance and auditability, and elevated emphasis on cybersecurity and privacy impact assessments. #### What to watch - •Publication of the final RFP and vendor shortlist, which will reveal technical scope and procurement timeline. - •Released technical specifications or privacy impact assessments that disclose data sources, model validation requirements and audit procedures. - •Any pilot deployments or interoperability tests with airlines, maintenance databases or air-traffic management feeds. ## Scoring Rationale This is a notable regulatory-technology initiative with practical implications for data integration, model validation and security in aviation oversight. It is not a frontier-model or industry-wide paradigm shift, but it signals meaningful demand for applied ML and secure ledger solutions in a safety-critical domain. Practice interview problems based on real data 1,500+ SQL & Python problems across 15 industry datasets — the exact type of data you work with. [Try 250 free problems](/problems)