Where Latttice fits in the modern data stack.
Most organizations already have cloud platforms, data warehouses, governance tools, analytics platforms, and AI initiatives. The challenge is not collecting more data. The challenge is turning enterprise data into trusted, governed data products that people and AI can confidently use. This page explains where each technology fits and how Latttice connects them to business outcomes.
Every enterprise already has a modern data stack.
The layers are well understood. Investments have been made. Teams are in place. And yet trusted data remains difficult to reach.
If organizations already have all of these technologies, why is trusted data still difficult to access?
The layers already exist. What is missing is what connects them.
Latttice is not another layer sitting on top of your stack. It is the connective fabric that joins the layers you already own so their combined output becomes trusted, reusable business data products.
Latttice transforms existing enterprise data into trusted, reusable, governed data products that support reporting, analytics, operational decisions, AI models, and AI agents. It does this by joining what you already own, not by inserting anything new between existing layers.
A vendor-neutral view of the modern enterprise data stack.
Existing layers stay in place. Latttice is the connective fabric that joins them so their combined output becomes trusted, reusable business data products.
What each layer is responsible for.
Every layer solves a real problem. None of them, on their own, produces the trusted business data products AI and decision-makers need.
| Layer | Primary responsibility | Typical platforms |
|---|---|---|
Cloud Infrastructure | Storage and compute | AWS, Azure, Google Cloud |
Enterprise Data Platform | Store and process enterprise data | Snowflake, Databricks, Microsoft Fabric, Redshift, BigQuery |
Integration | Move and transform data | ETL and ELT tools |
Governance | Policies, lineage, catalog | Collibra, Purview, Alation |
Analytics | Visualize information | Power BI, Tableau, Looker |
AI | Consume trusted, governed data | LLMs, AI agents, copilots |
Latttice | The connective fabric that joins the layers above so their combined output becomes trusted, reusable business data products. Not another layer inserted between them. | |
Technology investments alone do not create trusted decisions.
Enterprise data platforms, governance tools, and analytics platforms are necessary. They are not sufficient. Trusted decisions and trusted AI require something these layers were never designed to produce.
Latttice is the connective fabric of the modern data stack.
Latttice does not replace enterprise data platforms, governance tools, or analytics platforms. It joins them together. The result is a new category of software: a workbench where business teams turn existing enterprise data into trusted, governed, reusable data products, without inserting anything new between the layers you already own.
Bring in data from Snowflake, Databricks, Fabric, Collibra, SAP, and other enterprise systems without moving or duplicating it. Existing investments stay in place.
Business teams shape data into products in a zero-code workbench. Meaning, ownership, and business context are captured where the work happens.
Policies from your governance platform are enforced inside the product itself. Freshness, quality, access, and lineage travel with the data.
Products are published to a catalog with a clear owner, contract, and audience. Reuse replaces reinvention.
Reporting, analytics, applications, AI models, and AI agents consume trusted products at the point of decision, not raw pipelines.
From enterprise data to trusted decisions.
A maturity model organizations follow as they move from stored data to a decision-driven enterprise. Latttice is the connective fabric that makes each step deliberate rather than accidental.
Common questions from architects, analysts, and executives.
Do I still need Snowflake?+
Yes. Snowflake, Databricks, Microsoft Fabric, Redshift, and BigQuery remain the enterprise data platforms where data is stored, processed, and shared at scale. Latttice does not replace them. Latttice connects to them and turns the tables, views, and models inside them into governed business data products that people and AI can use with confidence.
Does Latttice replace Databricks?+
No. Databricks is a lakehouse platform for data engineering, machine learning, and large-scale processing. Latttice is not another platform stacked on top of it. Latttice is the connective fabric that joins Databricks with your governance, analytics, and AI tools so the assets Databricks already manages become trusted, reusable business data products.
Does Latttice replace Collibra, Purview, or Alation?+
No. Governance platforms catalog and describe enterprise data. Latttice consumes that governance and carries it through into the data products business teams actually use. Policies, ownership, and lineage from your catalog become enforceable properties of the data products themselves, without introducing a parallel layer.
Can Latttice work with Microsoft Fabric?+
Yes. Latttice complements Microsoft Fabric the same way it complements Snowflake and Databricks. Fabric provides the enterprise data platform. Latttice is the connective fabric that ties Fabric together with governance, analytics, and AI, turning Fabric data into business data products for reporting, AI, and decision support.
Where do AI agents connect?+
AI models, copilots, and agents connect to Latttice data products, not directly to raw tables. Because each product carries governance, ownership, freshness, and semantic context inherited from your existing stack, agents receive trusted data with the guardrails they need to act safely.
Isn't Latttice just another layer in the stack?+
No. Latttice is deliberately not another layer. Your enterprise data platform, governance tools, analytics platforms, and AI initiatives already exist and should keep doing what they do best. Latttice is the connective fabric that joins them together and turns their combined output into trusted, reusable business data products. Nothing new is inserted between existing layers.
How does Latttice support AI readiness?+
Latttice transforms AI ready data into decision-ready data products. Governance, freshness, semantics, and access policy from your existing stack are bound to every product so AI systems consume trusted, contextual data instead of raw pipelines. This is how AI initiatives move from prototype to production with confidence.
Continue exploring.
Cornerstone resources that explain the ecosystem, the category, and the practice.
Turn your existing enterprise data into trusted business outcomes.
Most organizations already own the technology they need. Latttice helps them activate it.
See Latttice with your own use case.
Bring us a business challenge, decision or data product idea. We'll show how Latttice can bring it to life using realistic synthetic data, without requiring access to your private data.
No sales pitch. Just a tailored demonstration for your scenario.