Overview
VaultSpeed automates the construction and maintenance of Data Vault 2.0 data warehouses. The platform takes a business model as input and generates production-ready code as output: DDL, loading procedures, transformation logic, and orchestration, across all major cloud and on-premise database platforms including Snowflake, Databricks, Azure Synapse, SQL Server, and Oracle.
Code generation is deterministic and template-based. Same input produces same output every run. Versioned, auditable, deployable through CI/CD.
VaultSpeed sits in the Belgian data software cluster alongside Collibra, Soda, and Luzmo, applying the AI-Native pattern at the data-infrastructure layer rather than the analytics layer.
Agentic Framework (2026)
In early 2026 VaultSpeed extended the platform with an agentic layer built on a graph-based knowledge model of an enterprise's full data landscape.
The knowledge model captures four layers:
- Business Entities: what the organisation cares about
- Integration Strategies: how concepts are resolved across sources
- Physical Structures: the vault implementation
- Semantic Definitions: what the data means in business terms
AI agents work above and below the vault. Upstream they handle source analysis, business key identification, entity mapping, and conflict detection. Downstream they generate governed semantic layers, metric definitions, and data product structures for tools such as Snowflake Cortex and Databricks Genie.
Agents propose. Humans approve. Production code generation stays deterministic.
The framework operates on metadata only. It never processes actual data. The layer is LLM-agnostic; customers connect their own model provider.
Funding history
- Seed, 2021 - led by Fortino Capital
- Series A, 2023 - led by Octopus Ventures (approximately EUR 15.9M)
Customers and Markets
Enterprise deployments across financial services, insurance, telecom, manufacturing, and legal/media. ISO 27001 certified. HQ in Leuven; additional offices in London and Boston.
Why It Matters
VaultSpeed compounds customer learnings into a shared platform: every deployment teaches the system new edge cases, source patterns, and integration strategies. That moves Data Vault 2.0 architectures from a discipline requiring the largest, most sophisticated data teams into reach for much smaller organisations. In the context of this wiki, VaultSpeed is a clear example of the B2B SaaS and Enterprise AI patterns applied to data infrastructure.
Positioning
VaultSpeed is relevant for organisations that are building or maintaining a Data Vault 2.0 warehouse, need deterministic and auditable code generation rather than AI-written production code, want a governed semantic layer on top of the vault for AI/BI consumption, or are migrating from a hand-built or dbt-based vault. It is not a general-purpose ETL tool, a data catalog, or a BI platform.
Links
- Website: https://www.vaultspeed.com
- LinkedIn: https://linkedin.com/company/vaultspeed
- Contact: info@vaultspeed.com
Leadership & org chart
In the news
- Quick test. Open the Microsoft Marketplace and search for VaultSpeed. We’ll wait. Found us? Good. Your team can now buy VaultSpeed where it already buys for Microsoft Azure, with one less vendor portal to log into. And the part your finance team will like: VaultSpeed is Microsoft Azure Consumption Commitment (MACC) enabled. Buy through the marketplace and the purchase counts toward the Azure commitment you already signed. Same budget, no new contract. You didn’t find us? Here’s the link: https://lnkd.in/e8N949RV #Azure
- If your "most recent wins" rule sorts on load time, your nightly ERP copy wins every day. Including the day it holds an exchange rate the central bank already withdrew. Part 4 of Dirk Vermeiren's series is about time and validity: which timestamp is the clock, why a bad rating never gets to compete, and an insurance claim that needs three separate decisions on one loss date. #DataModeling #FinancialServices #Insurance
- Customer 10443 is Lien De Smet in the CRM and Bram Peeters in the ERP. Join on the customer number and they become one person. Part 3 of Dirk Vermeiren's series is about matching: the step that decides who competes for the golden record before any value can win. Three worked examples, including a barcode that two different products share. #DataModeling #MasterData #DataQuality
- This week's shopping list: Milk. Coffee. An agentic data modeling platform that runs inside your own Snowflake account. Only one of those is on the Snowflake Marketplace. VaultSpeed installs as a Snowflake Native App, so it works inside your environment, and the Snowflake SQL it generates keeps running without any runtime dependency on us. Start the free trial from the Marketplace: https://lnkd.in/eCmzgbeY #Snowflake #DataModeling
- A wrong chart gets corrected in a meeting. A wrong parcel, a refused credit or a wrong tax return is already done by the time someone notices. That difference is why it matters where the choice between conflicting values gets made. Part 2 of Dirk Vermeiren's series looks at what happens when a stage is missing, and why AI should design the survivorship rule but never execute it row by row. #DataModeling #AI #DataQuality
- A wrong chart gets corrected in a meeting. A wrong parcel, a refused credit or a wrong tax return is already done by the time someone notices. That difference is why it matters where the choice between conflicting values gets made. Part 2 of Dirk Vermeiren's series looks at what happens when a stage is missing, and why AI should design the survivorship rule but never execute it row by row. #DataModeling #AI #DataQuality
- Want to get access to VaultSpeed for an hour, guided by Jonas and the team ? Better than a demo, a highly engaging and fun way to explore VaultSpeed 8.
- Agentic Data Modeling, a live online workshop on Thursday 19 November, 16:00 CET (10:00 ET). Sixty minutes, hands-on. You work in Omnigent, the VaultSpeed workbench where you build together with the agents. Bring the questions your team keeps asking about AI and data modeling. Register here: https://lnkd.in/eDx6CpRC #AgenticAI #DataModeling #DataEngineering
Alumni 1 went on to found or lead
- PPiet De WindtVP of Customer Experience and Strategic Partnerships→CEO at Mantyx
Marc CoppensCFO→CFO at NGDATA
Patrick Van DevenBoard Member
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