Your teams can find data. They can't tell if it means what they think it means.
Actian connects every data asset to its business context, lineage, and trust signals, so every user, from data architect to business analyst to AI agent, discovers data through meaning.
One cargo airline. 100+ data sources.
Every employee finding data without an IT ticket.
Data sources unified
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Employees with self-serve access
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Native connectors syncing in real time
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Lufthansa Cargo unified 100+ data sources and gave 4,100+ employees self-serve access to trusted data. Without a single folder path required.
Lufthansa Cargo is one of Europe’s leading cargo airlines, serving 300 destinations across 100+ countries. €3B in annual revenue. 530,000 tons of freight handled annually. Core systems calculate 30,000+ global flights daily.
Their discovery problem was specific: legacy search required knowing the exact asset name or folder path before you could find anything. Business teams were locked out of self-serve discovery entirely. Unconnected BI reporting caused data overlaps that forced employees to manually validate numbers before trusting them. And integrating metadata across 100+ disparate sources in real time had no automated path.
The challenge
- Legacy search blocked business teams from finding data without knowing exact asset names or folder paths upfront.
- Unconnected BI reporting caused massive data overlaps, forcing employees to manually validate before acting.
- Syncing metadata across 100+ disparate sources in real time had no scalable solution.
- Legacy architectures stripped business meaning from physical assets the moment data moved.
What Actian did
- Deployed a single Federated Knowledge Graph so humans and technical teams finally operate from the same context layer, discovering data through meaning, lineage, and relationships.
- Studio App automated documentation for data producers and architects, building a live, continuously updated metadata layer.
- Explorer App gave business consumers graph-based search driven by meaning and relationships, removing the requirement to know asset names or paths in advance.
- 75+ native connectors replaced static spreadsheet inventories and point-in-time scans with continuous, real-time metadata synchronization.
What Lufthansa Cargo achieved
100+ data sources unified into a single trusted source of truth across the full cargo operation.
4,100+ employees with autonomous access to data, building hypotheses and routing critical global cargo faster.
75+ native connectors continuously ingesting and synchronizing real-time metadata, replacing manual spreadsheet inventories entirely.
Built for every user who needs to find and trust data fast
The flexible metamodel adapts to any topology without re-architecting. Every user and every AI agent discovers data through current, governed context, because the graph connects physical datasets to business meaning automatically.
Studio serves data producers. Explorer serves data consumers. Both run on the same graph-based search layer, so every role from data architect to business analyst to AI agent discovers data through meaning, lineage, and context rather than asset names and folder paths.
75+ native connectors continuously ingest and synchronize metadata across cloud, on-prem, and hybrid environments. The live context layer updates automatically. Teams stop maintaining spreadsheet inventories and start working from a catalog that reflects reality.
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The flexible metamodel adapts to any topology without re-architecting. Every user and every AI agent discovers data through current, governed context, because the graph connects physical datasets to business meaning automatically.
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Studio serves data producers. Explorer serves data consumers. Both run on the same graph-based search layer, so every role from data architect to business analyst to AI agent discovers data through meaning, lineage, and context rather than asset names and folder paths.
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![AI Analyst Connectors]()
75+ native connectors continuously ingest and synchronize metadata across cloud, on-prem, and hybrid environments. The live context layer updates automatically. Teams stop maintaining spreadsheet inventories and start working from a catalog that reflects reality.
Recognize any of these?
If your team is dealing with this… |
Actian addresses it with… |
|---|---|
Business teams locked out of self-serve discovery without IT help |
Explorer App surfaces data through meaning and relationships, requiring zero prior knowledge of asset names or paths |
Different teams validating the same numbers independently |
Federated Knowledge Graph enforces a single governed context layer across every role |
Metadata documentation that drifts the moment a pipeline changes |
75+ native connectors sync metadata continuously, no manual refresh cycles |
AI agents that can’t find relevant data without exact field IDs |
Graph-based search surfaces assets by meaning, lineage, and context |
Where data discovery connects to the bigger picture
Ready to give every team self-serve access to data they can trust?
Talk to a solutions engineer about your discovery environment. We’ll show you how the Federated Knowledge Graph maps to your specific sources, roles, and architecture.
Book a Solutions Call
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