A GenAI platform for an airport, answered with working bots
Confidential · Aviation
The business said
- “Put a FAQ chatbot on the website”
- “Add more call-center staff for passenger queries”
- “Pilot one vendor's assistant and see”
- “Write a strategy paper first”
- “One platform for voice, video, and text AI, engineered to airport-grade uptime”
An airport does not need a chatbot. It needs a platform: voice, video, and text assistants on one architecture that survives peak traffic and audits alike.
A generative AI platform design, proven with working voice and video bots
One of the busiest international airports in the region went to formal tender for a generative AI platform: assistants that could speak with passengers by voice and video, transcribe and understand speech, work across languages, and do all of it inside the security and data-protection rules an airport operates under. The tender asked hard questions about architecture, availability, and support, the kind that eliminate slideware quickly.
We answered with working software. Alongside the written response went functioning voice bot, video bot, and speech-to-text demonstrations, so the evaluation committee could try the experience rather than imagine it. The functional response covered the full requirement set, including multilingual operation and data-loss-prevention controls for anything a passenger might say to a machine.
The platform design treated the AI as production infrastructure, not a demo. Kubernetes for self-healing services, geographic redundancy with load balancing and automated failover, auto-scaling for passenger-traffic peaks, Redis caching for hot paths, and continuous data replication. Everything provisioned as infrastructure-as-code with Terraform-style tooling, shipped through CI/CD across isolated UAT, staging, and production environments, and watched by Prometheus and Grafana with alerting wired to business rules.
Around the platform sat an operations spine sized for a facility that never closes: 24x7 support with a tiered model, critical incidents answered in thirty minutes and resolved in one hour, automated escalation, root-cause analysis on any breach, and minor enhancements such as prompt tuning and new dataset integration delivered on a weekly cadence. The premise throughout: passenger-facing AI is an uptime business first and a language-model business second.
- voice, video, text, modalities
- working bot demos, proof
- 30 minutes, critical response
- Prometheus + Grafana, observability
- UAT, staging, prod, environments
- 24x7 tiered, support
