Query all your data in place — without moving it
SemanticFed is the data federation platform that unifies your databases, warehouses, lakes, and APIs behind one governed semantic layer. Write one query, get one answer — with access policy, lineage, and audit built in.
- Zero-copy federation
- Governed semantic layer
- Policy at the query edge
- Trustworthy AI context
One query interface across every source
- PostgreSQL
- MySQL
- Snowflake
- BigQuery
- S3 / Object storage
- Parquet & Iceberg
- REST & GraphQL APIs
- Redshift
- MongoDB
Built for the work SemanticFed customers actually do
Real scenarios, start to finish — pick one to see how it plays out.
Query Postgres, Snowflake, and S3 in one statement
Join a transactional table to warehouse facts and lake files without an ETL pipeline
Read the story24 scenarios across 7 areas of SemanticFed.
Explore every use caseAI that answers from your governed data model — and shows its work
Your agents get a typed, permission-checked map of your business instead of raw tables. Here is exactly what works today, what is half-built, and what is still planned.
Let an AI agent run your data platform
The shipped surface: 40 tools, guided recipes and your live catalogue — under exactly the permissions you already have.
Read the story8 shipped · 2 in progress · 4 on the roadmap
See how SemanticFed is AI-nativeStop copying your data just to ask a question
Most analytics stacks answer questions by moving data — pipeline after pipeline, copy after copy, each one a thing to schedule, monitor, and reconcile. SemanticFed takes the opposite path: it queries data where it already lives.
Built for the whole data team
Whether you analyze data, engineer it, or govern it, SemanticFed gives you one consistent, governed way to reach every source.
For Analytics Teams
Query every source through one governed semantic model. Define a metric once and have it mean the same thing in every dashboard, notebook, and API.
Browse use casesFor Data Engineering
Retire brittle ETL with virtual, federated views. A cost-aware planner pushes work to the source so you move bytes, not terabytes.
Explore featuresFor Governance & Platform
Row- and column-level policy, masking, lineage, and a full audit trail enforced at the query edge — across every source, for every tenant.
See governanceProblems we solve
Data teams adopt SemanticFed because these everyday blockers stop being blockers.
Data lives in too many places to query together
SemanticFed registers databases, warehouses, lakes, and SaaS APIs as federated sources and joins them in one query — without moving the data.
See the storyEvery dashboard reports a different number for the same metric
Define entities, dimensions, and metrics once in the governed semantic layer so every tool resolves the same definition.
See the storyGovernance fragments across sources and tools
Row filters, column masking, and access rules are enforced at the query edge across every federated source.
See the storyFederated queries are slow and expensive
A cost-aware planner pushes filters, projections, and aggregations down to each source so you move bytes, not terabytes.
See the storyAI agents reason over raw tables and guess wrong
Point agents at the typed semantic layer so they query documented metrics with policy applied — grounded, reproducible, and safe.
See the storyOne platform, end to end
Everything you need to federate, model, govern, and serve your data — in a single control plane.
Federated Query Engine
A cost-aware planner that pushes filters, projections, and aggregations down to each source and joins the results — no copy required.
Governed Semantic Layer
Model entities, dimensions, and metrics once in a typed layer that every tool, notebook, and AI agent resolves consistently.
Policy at the Edge
Row filters, column masking, and access rules defined once and enforced on every federated query, whatever source the data lives in.
Trustworthy AI Context
Point agents and copilots at the semantic layer so answers reason over documented metrics with access policy applied — not raw tables.
Lineage & Observability
End-to-end lineage and per-query plans show what ran where, what was pushed down, and where every number came from.
Connect Anything
Databases, cloud warehouses, object-storage lakes, and SaaS APIs register as federated sources behind one SQL and GraphQL interface.
Give your AI a source of truth
Agents pointed at raw tables guess at schemas and ignore access rules. Point them at SemanticFed instead: a typed semantic layer of documented metrics, with the same policy enforced on the agent as on a human — so answers are grounded, reproducible, and safe to act on.
- Agents query documented metrics, not mystery columns
- Access policy and masking apply to every generated query
- Every answer is inspectable back to its query plan
Ready to unify your data?
Be among the first data and platform teams to run SemanticFed when we launch in 2026.
Launching 2026 • Sign up for early access
What we're building
SemanticFed is launching in 2026. Here is the platform we are bringing to data teams.