LakeFusion provides an AI-native master data management (MDM) platform purpose-built for the Databricks Lakehouse. Traditional MDM tools sit outside the lakehouse and require heavy integration, but LakeFusion embeds AI and automation directly into the MDM process and integrates natively with Databricks so organizations can deliver trusted, deduplicated, and governed master data for analytics and AI without moving data out of their platform. As enterprises rush to make data AI-ready, clean and reconciled master data becomes a prerequisite for reliable AI outputs, and LakeFusion targets exactly that gap. The company closed its seed funding round led by Carbide Ventures, capital it is using to build out its lakehouse-native MDM capabilities and serve enterprises standardizing their data foundations for AI.
LakeFusion
ActiveAI-native master data management on the Databricks Lakehouse
Total raised
$3.5M
1 round
Stage
Seed
Team
1-10
since 2024
Pricing
Freemium
free plan
Founded
2024
San Francisco, United States
Agent-ready
—
AI-native master data management
Native Databricks Lakehouse integration
Automated record matching and deduplication
Data quality and reconciliation
Governed trusted data for AI
No data movement out of the lakehouse
Enterprise-scale MDM workflows
Embedded AI and automation
10/100
Early
MCP server
Public API
Webhooks
OAuth 2.0
SDKs
No public agent surfaces detected yet.
— Seed $3.5M incl. Carbide Ventures
1 backer tracked. The network map fills in as more rounds and co-investors are recorded.
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- What is LakeFusion?
- LakeFusion is an AI-native master data management platform built natively for the Databricks Lakehouse.
- Does it require moving data out of Databricks?
- No, LakeFusion integrates directly with the lakehouse so master data is managed in place.
- How much has LakeFusion raised?
- LakeFusion closed a seed round led by Carbide Ventures.
- Why does MDM matter for AI?
- Clean, reconciled master data is a prerequisite for reliable analytics and AI outputs.
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