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Assaia – The ApronAI Tech Stack

AI-powered ground operations optimization for airports and airlines

Information Technology & Services Zurich 51–200 employees Founded 2017 Privately Held

Assaia deploys computer-vision and ML systems into airport operations, running inference on live video feeds (FFmpeg, GStreamer, PyTorch, Triton) to optimize aircraft turnarounds and gate utilization. The stack reveals a production-heavy focus: Kubernetes orchestration, PostgreSQL + MongoDB for state, Celery for task queues, and FastAPI for real-time APIs — all necessary to handle continuous video ingest and low-latency ML predictions at airport scale. Active hiring is engineering-concentrated (5 of 9 roles), with seniority skewed senior, suggesting they're building out inference infrastructure and MLOps maturity rather than expanding headcount broadly.

Tech Stack 31 technologies

Core StackPython Docker Kubernetes Django FastAPI PostgreSQL MongoDB Redis Celery GitLab CI/CD TypeScript React GitLab Linux Java C++ Rust PyTorch Triton Inference Server MobX SQLAlchemy FFmpeg GStreamer Bash RTSP RTMP H.264 H.265 IPsec OpenVPN+1 more

What Assaia – The ApronAI Is Building

◆Challenges

Efficient and scalable ml pipelines
Improving airport turnaround efficiency
Improving mlops practices
Reducing technical debt
Allocation challenges
Regulatory requirements
Efficiency goals
Scalable automated financial processes
Improving internal controls
Building robust financial frameworks

▲Active Projects

Ml pipelines
Real-time production system
Inference software infrastructure
Apronai platform features
Internal design system
Hybrid mobile application
Ai-powered turnaround management solution
Cloud-based cctv streaming pipeline development
Proactive monitoring strategy implementation
Real-time video and neural network inference engine

Hiring Activity

Decelerating9 roles · 2 in 30d

Department

Engineering

5

Finance

1

Product

1

Sales

1

Seniority

Senior

6

Manager

1

Mid

1

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About Assaia – The ApronAI

Assaia provides AI software for optimizing turnaround operations at airports and airlines. The platform ingests live CCTV feeds, applies neural-network inference to predict and automate ground tasks, and surfaces insights to airport operations and airline crews via web and mobile interfaces. Deployments span Europe and North America, serving major airports (London-Gatwick, Seattle-Tacoma, Rome, Toronto Pearson, JFK) and carriers including British Airways, United Airlines, and Alaska Airlines. Core pain points in the platform roadmap center on ML pipeline scalability, MLOps practices, and reducing technical debt—typical signals of a company moving from prototype toward repeatable, multi-tenant production deployments.

HeadquartersZurich

Company Size51–200 employees

Founded2017

Hiring MarketsUnited States, Germany

Frequently Asked Questions

What tech stack does Assaia use?

Python, PyTorch, Triton Inference Server, Kubernetes, Docker, PostgreSQL, MongoDB, Redis, FastAPI, Django, TypeScript/React. Video handling via FFmpeg and GStreamer; CI/CD through GitLab.

What is Assaia working on?

ML pipelines, real-time inference infrastructure, cloud-based CCTV streaming, MLOps improvements, AI-powered turnaround management, and internal design systems. Active focus on reducing technical debt and building scalable systems.