AI Engineer NYC 2026 Online track · 2 min

Agents in Orbit: Workflows, Not Autopilot

Eduardo SimonFlywire

Javier CasalFlywire

Flywire’s Orbit brings engineering agents into an existing GitLab and AWS environment. This opening excerpt covers the company’s infrastructure and privacy constraints before the livestream returns to the live stage.

A platform built inside the existing engineering environment

Flywire processes complex payments across education, healthcare, travel, and business services. That makes the placement of an engineering agent consequential: customer information and payment details cannot simply be handed to an outside service without governance.

Eduardo Simon introduces the work of Flywire's AI Platform Experience team alongside Javier Casal. The team's aim is practical agentic infrastructure that follows the company's existing engineering standards. Simon describes an organization of roughly 400 engineers working across Java, Ruby, Go, Python, .NET, and PHP, with most systems deployed through Victoria, an internal platform built on GitLab and AWS. 5:06:03

Orbit aims to remove repetitive engineering work within that environment. It has to follow the same engineering standards and controls as the systems it helps operate.

The livestream cuts away before the architecture is explained. This opening excerpt ends there; the complete presentation continues Simon and Casal's account of how Orbit works.

Further reading

Watch the complete Flywire presentation ↗AI Engineer’s full separate recording of Eduardo Simon and Javier Casal’s Agents in Orbit presentation.

Full transcript

Timestamps follow the original livestream. Select a time to watch that moment. Transcripts are machine-generated with reviewed name and terminology corrections; occasional recognition errors may remain.

Hello everyone and welcome. My name is Edu and alongside Javi, we represent the AI Platform

Experience team at Flywire. Our core mission is to build practical agentic infrastructure

that empowers our software engineers while following our established engineering standards

and practices. Today, we'll share how structured workflow automation delivers real enterprise value,

ensuring control, safety, and reliability across our development process.

Before we dive into the deep technical details of our AI platform, let us give you some essential

context about Flywire. Flywire is built to process the world's most complex payments

across global industries like education, healthcare, travel, and business services.

Today, we serve over 5,000 clients across more than 240 countries around the world.

Because we process high-value international transactions,

regulatory compliance, privacy, and security are not optional add-ons.

They are core requirements of our business.

We operate under strict compliance frameworks like PCI, DSS, and SOC2.

This means that customer data, personal identification, and payment details must remain completely safe.

We cannot simply take sensitive context and pass it to third-party services without strict governance and architectural boundaries.

To give you an idea of our engineering organization, we have around 400 software engineers distributed globally.

Across our teams, we maintain diverse technology stacks, including Java, Ruby, Go, Python, .NET, and PHP.

Almost everything we build and run is deployed on Victoria, our internal platform as a service that operates on top of GitLab and AWS infrastructure.

This brings us to Orbit, our own toil killer.

Orbit is an internal platform that eliminates daily engineering.

It's called only where we talk every day.

It also gives the code that the other AI services and tools we use across Flywire can start

workflows directly. For example, an engineer will be able to ask Claude in Slack use cases.

Send prices can start workflows directly.

Victoria, it starts...