Source proof for Thales InFlight Experience builds Databricks and Genie AI agents for self-service access to content, system health and passenger data

…I Agents at Scale: How Thales Transformed IFE with Databricks and Genie Summary Thales InFlight Experience unified data from 2,000+ aircraft serving 2 million daily passengers into the Databricks Data and AI platform, then built AI agents using RAG, Genie text-to-SQL, and custom MCP architecture to give business users real-time self-service access to content, health, and passenger data. The production deployment required solving three technical challenges: identity…

…I Agents at Scale: How Thales Transformed IFE with Databricks and Genie Summary Thales InFlight Experience unified data from 2,000+ aircraft serving 2 million daily passengers into the Databricks Data and AI platform, then built AI agents using RAG, Genie text-to-SQL, and custom MCP architecture to give business users real-time self-service access to content, health, and passenger data. The production deployment required solving three technical challenges: identity…

…ess users real-time self-service access to content, health, and passenger data. The production deployment required solving three technical challenges: identity propagation so agents respect per-airline permission boundaries, multi-tenancy across 90 airline customers, and tool management at scale in a regulated environment. Moving from static dashboards requiring data analyst support to autonomous AI a…

…so very happy to be here. So, let let's talk a little bit about uh our company. So, we are Thales InFlight Experience. So, we are part of Thales Group uh group that focus on very different businesses. For us, what we do is really…

…so very happy to be here. So, let let's talk a little bit about uh our company. So, we are Thales InFlight Experience. So, we are part of Thales Group uh group that focus on very different businesses. For us, what we do is really…

…ust contributes to the frustration of your business users. [07:57] And finally, we have the data, we have the lakehouse, we have the governance, but the access is still bottleneck. Like usually data scientists and data analysts, they are the only one who know…

…ntion. AI Agents at Scale: How Thales Transformed IFE with Databricks and Genie Enterprise teams across industries depend on static dashboards and data analysts to answer questions, creating bottlenecks that slow decision-making. Thales IFE demonstrates how Databricks AI agents powered by Genie, RAG, and vec…

…I Agents at Scale: How Thales Transformed IFE with Databricks and Genie Summary Thales InFlight Experience unified data from 2,000+ aircraft serving 2 million daily passengers into the Databricks Data and AI platform, then built AI agents using RAG, Genie text-to-SQL, and custom MCP architecture to give business users real-time self-service access to content, health, and passenger data. The production deployment required solving three technical challenges: identity…

…lly, agents for us are quite easy to deploy. They are pretty [09:31] light, and we leverage Databricks app to serve those agents, and we can deploy them very, very quickly. Whenever we want to do a front end update on our systems, you have to go throug…

…you want is your agent to be able to interact and take actions. And this is why we built custom MCPs on top of our APIs, and that provides the system layer, I mean, the action layer for our agent, so that he's [17:02] able to actually take action. So, this is the overall arc…

…90 airline customers, and tool management at scale in a regulated environment. Moving from static dashboards requiring data analyst support to autonomous AI agents reduced decision-making bottlenecks and enabled business teams to take action directly without engineering intervention. AI Agents at Scale: How Thales Transformed IFE with Databricks and Genie Enterp…

…44] agent natural language, no more dashboard update, or pinging the data team. Users can just go ask the question and get the answers that they're looking for. Uh the second thing, and I think this is the most critical piece for us, is age…

…e data and using the medallion [06:21] architecture to refine that data. Um and over the time we added additional capabilities like Unity Catalog, the SQL warehouse, now agents, etc. At the end the goal is to serve the end applications. This could be dashboards…

…that you don't get mixed up in the data. And finally, all the tools, right? So, by default, the way we built the the agent, we are using LangChain. Uh it exposes all the tools, right? Regardless of the user's permission. So, ba…

…endpoint as a Databricks uh app and this can be done with different frameworks. So, in this case, we're mentioning fast MCP, could be other ones. Uh and in this case, you have this MCP endpoint that acts as a stateless [15:25…

…lly, agents for us are quite easy to deploy. They are pretty [09:31] light, and we leverage Databricks app to serve those agents, and we can deploy them very, very quickly. Whenever we want to do a front end update on our systems, you have to go throug…

…90 airline customers, and tool management at scale in a regulated environment. Moving from static dashboards requiring data analyst support to autonomous AI agents reduced decision-making bottlenecks and enabled business teams to take action directly without engineering intervention. AI Agents at Scale: How Thales Transformed IFE with Databricks and Genie Enterp…

…architecture uses three components: RAG for retrieving unstructured documents, Genie for text-to-SQL queries against structured data, and custom MCP tools for interacting with APIs and taking autonomous actions.…