Home/Solutions/Aviation
Solutions · Civil aviation

An intelligent co-pilot for every passenger, airport and regulator.

Bud AI Foundry trains, deploys, governs and serves generative AI across private, cloud and air-gapped environments. Applied to civil aviation, it puts a multilingual assistant in front of every passenger and a document-intelligence layer behind every regulator - on infrastructure the state controls.

The problem this solves

Enterprise GenAI today resembles enterprise software before SAP — dozens of fragmented tools for inference, training, guardrails, governance and orchestration, integrated by hand and maintained by whoever built them. That fragmentation is why 95% of GenAI pilots produce no measurable business impact.

Generative AI suits aviation particularly well, because the sector’s core problems are fundamentally language problems: a passenger who cannot read the signage, a complaint that nobody triages, a regulation buried in thousands of pages, a disruption nobody communicates.

Priority use cases

Ranked by value, ROI, speed-to-deploy and public impact.

01

Multilingual AI passenger assistant

16,591 complaints, a broken AirSewa, no Indian-language support, and 1.44 crore UDAN first-time flyers left without guidance.

02

AirSewa 2.0 — AI complaint resolution

A Delhi High Court PIL, generic airline replies and no accountability. 98% of 2024’s complaint volume arrived in H1 2025 alone.

03

DGCA regulatory document intelligence

3,890 inspections, 352 notices and thousands of CARs searched by hand, against a 25–53% staff vacancy. Semantic search makes it instant.

04

Fog and disruption communication

550 flights delayed in a single day in December 2025, with no proactive multilingual alerting and passengers stranded without information.

05

Natural language to insights

Parliamentary questions answered manually, with no real-time analytical capability over DGCA and AAI flight operations data.

06

Airline safety document processing

263 violations found in a single audit. Maintenance logs, FDR records and pilot training documents all processed by hand.

07

Crew scheduling AI advisory

4,500 IndiGo cancellations from an FDTL compliance failure, and ₹22.68 crore in compensation in one month.

08

DigiYatra sovereign AI processing

61 million biometric journeys on shared infrastructure, where anti-spoofing and fraud detection need sovereign GenAI.

09

Air cargo documentation

India handles 3.3 MMT against Hong Kong’s 4.5 MMT, with paper-heavy customs processing as the bottleneck.

10

National Aviation AI Grid — federated

AAI, DGCA, BCAS, AERA and the airlines all operate siloed systems with no shared intelligence layer. A federated deployment gives each party its own control while still allowing shared learning.

The roadmap

From vision to value, in three phases.

Phase 1

Every Indian passenger gets an AI assistant in their own language

“From chappal to chatbot: India gives first-time flyers an AI guide in every language.”

Multilingual AI passenger helpdesks — speech-to-text, LLM and text-to-speech — deployed at the top 25 airports over WhatsApp, IVR and kiosks.

Phase 2

India’s aviation regulator becomes the smartest in the world

“DGCA goes AI-first.”

Document intelligence across every CAR, audit report and safety directive, with AI-assisted inspection workflows behind it.

Phase 3

The world’s first fully sovereign AI-powered aviation ecosystem

“From consumer to creator: India exports sovereign aviation AI to the world.”

Full multilingual coverage across all 157+ airports including UDAN destinations, with sovereign processing throughout.

Key benefits

Sovereign by construction.

Deployment modelFully air-gapped, on-premises or private cloud. Data never leaves your infrastructure, and an open-source version is available.
Language coverageMultilingual by design rather than English-first with translation bolted on — which is what makes it usable for first-time flyers.
GovernanceGuardrails, audit and access control present from the first deployment, which is the precondition for a regulator adopting it at all.
FederationEach authority keeps its own data and control while still contributing to and benefiting from a shared intelligence layer.

Planning a national aviation AI programme?

We can walk through the phasing, the sovereignty model, and what runs air-gapped versus private cloud.