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Embrasure

The warehouse
built for agents.

Build agents that know your business. Give them your data and a place to learn from every question.

How it works
WarehouseLast sync 6:10 AM · next 6:10 PM
Warehouse

27 tables from 4 sources · 1.9 GB

Postgres13 tablesSupabase6 tablesStripe7 tablesSlack1 table
Tables24
core.customersPostgres · Stripe12,480 rows6:10 AM
core.subscriptionsStripe3,912 rows6:10 AM
events.checkout_eventsPostgres12.4m rows6:08 AM
Metrics3
metrics.trial_to_paid_7dPostgres · Stripe11.4% · 7-day avg6:12 AM
metrics.refund_rate_30dStripe1.7% · 30-day6:12 AM
metrics.trial_first_session_dailynewdbt6,412 rows9:58 AM
Backed bya16z Speedrun

Built by engineers from

OpenAIPalantirUberLinkedIn

From your sources
to your agents.

Explore sources

Your sources

  • Postgres
  • Snowflake
  • BigQuery
  • Stripe

Embrasure

Built-in Realtime Ingestion
Industry leading sub-second ingestion via Embrasure Flow.
Apache Iceberg + Agent-Accelerated Formats
Open tables you own, with Embrasure’s agent-accelerated formats and indexes layered on top.
Compute at Agent Speed
The Embrasure Engine reads those formats directly. Agent queries come back 8× faster.
Self-Improving Memory
Embrasure learns from query patterns, errors, and context to improve query accuracy

Query with

MCP
Your agents
CLI
Your terminal
Ember
In Slack

Iceberg,
agent-accelerated.

Your tables stay open in Iceberg, in storage you own. Embrasure layers agent-accelerated formats and indexes on top, so every agent query reads only the data it needs.

orderssnapshotindexIceberg+ agent-accelerated formats and indexes

Built for agents
that keep querying.

An agent rarely stops at one query. Embrasure sends every follow-up to the most efficient engine: the Embrasure Engine, DuckDB, Trino, or Apache Spark. Query costs run 90% lower than Snowflake.

SELECT sum(amount)FROM invoices304120843664amount
Powered byEmbrasure Engine · Example data

Memory that
improves itself.

60% more accurate agent queries. A recursive memory layer that learns from corrections, refines its context, and keeps improving with use.

Net revenueFirst querypaid invoicesSaved correction“Subtract refunds.”Next querypaid invoices− refunds

Your data.
Ready for agents.

Connect your sources. Bring your agents, or ask Ember in Slack.

Have a data warehouse already? Embrasure Enterprise