What can you do with SemanticFed?
Scenario-driven use cases grounded in the product — from joining a live database to a warehouse in one query, to grounding an AI agent in a governed semantic layer. Pick a persona and follow the story. These are illustrative pre-launch scenarios, not real deployments.
Showing 24 use cases
Analytics & BI
Query Postgres, Snowflake, and S3 in one statement
Execute federated queries across Postgres, Snowflake, and S3 with SemanticFed, ensuring data remains at the source while filters are applied seamlessly.
Analytics & BI
Define a metric once, use it everywhere
Define metrics once in SemanticFed’s semantic layer and consume them from SQL, BI tools, notebooks, and APIs — one governed definition for every dashboard.
Analytics & BI
Give analysts safe, self-service access to everything
Browse a governed catalog of federated datasets and query them directly, with access policies and masking enforced automatically.
Data Engineering
Retire brittle ETL with virtual, federated views
Replace point-to-point ETL jobs with virtual views over federated sources, transformed and joined at query time with no copy to maintain.
Data Engineering
Cut warehouse spend with cost-aware planning
SemanticFed’s planner pushes predicates, projections, and aggregations down to each source, choosing the cheapest path so only the rows you need move.
Data Engineering
Cache the hot paths, federate the rest
Enable result caching or materialization for hot query paths that need millisecond latency, while everything else stays live and federated.
Governance & Security
Enforce row- and column-level policy at the query edge
Define row filters, column masking, and access rules once in SemanticFed and enforce them on every federated query, regardless of where the data lives.
Governance & Security
Prove who queried what, and where it came from
Track federated queries and dataset lineage for compliance. SemanticFed logs every query and traces data back to its origin for streamlined audits.
Governance & Security
Keep data in place to honor residency rules
Query data where it lives so regulated data stays inside its residency boundary while still part of a unified model.
AI & Semantic Layer
Give AI agents governed, trustworthy data context
Point AI agents at SemanticFed’s semantic layer so they reason over documented metrics with enforced access policy — grounded, reproducible answers.
AI & Semantic Layer
Turn a plain-English question into a governed query
Ask questions in plain language and resolve them against the typed semantic model, with real metric names, access policy, and inspectable generated queries.
AI & Semantic Layer
See how all your data connects on a live knowledge graph
Explore modeled entities and relationships as a live knowledge graph — trace lineage, run impact analysis, and give AI agents a documented map of your data.
Integration & Connectors
Connect databases, warehouses, lakes, and SaaS APIs
Register databases, warehouses, lakes, and SaaS REST/GraphQL APIs as federated sources — each connector handles auth, introspection, and push-down.
Integration & Connectors
Serve the whole model over one SQL and GraphQL endpoint
Expose the federated model through one SQL interface and GraphQL API so apps and tools consume governed data from a single endpoint.
Platform & Enterprise
Run governed federation for many teams and tenants
Operate SemanticFed as shared infrastructure where every source, model, and policy belongs to a workspace — isolated, governed federation per team.
Platform & Enterprise
See every query, plan, and source in one place
Monitor the query layer with per-query plans, latency and push-down metrics, and source-health signals to find bottlenecks fast.
Platform & Enterprise
Discuss models and queries inline with your team
Comment and start discussion threads directly on semantic models, entities, and saved queries so conversations live next to the work they change.
AI Native
Let an AI agent run your federation over MCP
Utilize AI agents to manage your data federation over MCP, accessing connectors, semantic models, and policies without custom integration.
AI Native
Start modelling from a draft the AI proposed, not an empty page
Transform federation modeling with AI-generated drafts, turning complex data source registration into a simple editing task.
AI Native
Make every AI answer openable, not just plausible
Ensure AI-generated analytics are auditable with SemanticFed's inspectable plan summaries, promoting transparency and accountability.
AI Native
Have an agent notice a degrading source before your analysts do
AI agents monitor data source health, notifying owners of issues before analysts notice, ensuring proactive lifecycle management.
AI Native
Get caching proposals from an agent that reads your run history
AI analyzes run history to suggest cache and push-down optimizations, enhancing query performance with actionable insights.
AI Native
Catch a new PII column the day it appears
AI identifies potential PII columns, proposing draft deny policies to maintain governance without altering access controls.
AI Native
Make sure AI is not a way around your access rules
AI operations in SemanticFed adhere to existing authorization protocols, ensuring AI adds value without bypassing access rules.
See your scenario here?
SemanticFed launches in 2026. Join the waitlist and be among the first data and platform teams to query everything in place — without moving it.