Vendor-Agnostic

Agnostic by design. About your data, and about your models.

LazyFox does not force a migration, and it does not tie you to one AI provider. It reads the stack you already run, in whatever shape it is in, and it lets you choose the model behind every answer. Change either side whenever you want. Your governed knowledge stays exactly where it is.

01
Any data source

Connect anything you run. Move nothing.

Enterprise stacks are never tidy. They are the result of years of acquisitions, migrations, and vendor decisions. You have systems on Snowflake and systems still on Redshift, a warehouse for some data and document stores for the rest, dbt models that are only half documented. LazyFox was built for that reality.

It connects to your sources read-only, structured and unstructured, wherever they live. Warehouses, documents, PDFs, and NoSQL such as MongoDB all sit in one governed semantic layer. Nothing gets copied, and nothing gets migrated before you can start.

  • Structured and unstructured data in one layer: warehouses, documents, PDFs, NoSQL
  • Read-only connection. No records copied, moved, or migrated
  • Databricks, Snowflake, and Redshift connected at the same time
  • Your stack keeps changing. Your semantic layer does not get rebuilt when it does
See how integrations work →
02
Any model provider

Swap models freely. Keep your context.

Model providers move fast, and the model you pick today may not be the one you want in eighteen months. You should never be trapped by that choice. With LazyFox you can swap your LLM without rebuilding the semantic layer, and without re-exposing a single record to the new provider, because your raw data never reaches a model in the first place.

You also do not have to pick one model for everything. Choose the model per task, so embedding, intent recognition, and code completion can each run on the model that fits it best. Bring your own provider, or start from the default set LazyFox ships with.

Choose the model per agent, not just per company

Every agent you set up on LazyFox can run on its own model. A finance agent and a support agent can sit on different providers, under the same governed knowledge layer, with the same definitions behind both.

  • Swap your LLM without rebuilding the semantic layer
  • No data re-exposure on a switch: raw values never reach a model
  • Pick the model per task: embedding, intent recognition, code completion
  • Pick the model per agent you build on the platform
  • Use your own provider or the default set
How data abstraction protects you →

What lock-in looks like, and what it does not

Typical AI setup
LazyFox
One data source at a time, migrations to add more
Every source connected read-only, no migration
Structured data only, documents left out
Structured and unstructured in one layer
Locked to one model provider's infrastructure
Swap models with no data re-exposure
One model for the whole company
A model per task, and per agent you build
Your context lives in someone else's system
Your knowledge layer runs in your environment
About this page

Is LazyFox vendor-agnostic on data sources and AI models?

LazyFox connects read-only to any data source where it already lives, structured or unstructured, including warehouses like Snowflake, Databricks and Redshift, document stores, PDFs, and NoSQL systems such as MongoDB. No migration or ETL is required before a source can be queried by AI.

LazyFox is also model-agnostic: teams can swap the underlying LLM without rebuilding the semantic layer or re-exposing data to a new provider, and can choose a different model per task or per agent, since raw data values never pass through the model as prompt context. This keeps both the data stack and the model choice free of vendor lock-in.

Two kinds of freedom

One governed layer, no lock-in on either side.

Change your data stack, change your model, or change both. LazyFox keeps one shared, trustworthy understanding of your business through all of it.

Book a demo Watch platform tour