01 · Architecture
The platform runs in your cloud. Not ours.
Every managed data platform — Databricks, Snowflake, BigQuery — runs your workloads in their infrastructure. Zetaris deploys directly into your cloud account. You own the cluster, the keys, and the bill. Your data never leaves your environment. IAM role trust — we never hold a long-lived credential.
Learn about BYOC deployment →
02 · In-situ analytics
One query. Every source stays put.
You've written the same query three different ways this week. One for Snowflake. One for the Postgres instance nobody wants to migrate. One for the S3 bucket that only works if you know the right IAM role. With Zetaris, you define the connection once. Query Director routes each subquery to the right engine at runtime — in-situ, at the source. No pipelines. No copies. No sync lag.
See how Zetaris queries data in place →
03 · AI data access
Connect your data to your LLM.
Your agent ships — and it hallucinates, because the data it needed was sitting in a system it couldn't reach. Not a model problem. A data access problem. The Open Agentic Lakehouse gives your LLM governed, AI-ready access to your entire data estate — the context it needs to reason accurately, without copies, without prep, without waiting.
Explore the MCP integration →
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Your apps & AI agents
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Python / Spark SDK
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JDBC / ODBC
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MCP / REST
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SQL Editor
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↓
Zetaris Cloud — your cloud account · your environment · your keys
Query Director
Trino · Spark · Presto
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Semantic Layer
AI Data Steward · context
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AgentFlow
MCP · orchestration
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Data Catalog
Iceberg · Delta · metadata
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↓ in-situ analytics — nothing copied ↓
Your data — stays where it is
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S3 / Delta
Object storage
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-- Three live sources. No ETL. No copies.
SELECT
c.customer_id, c.segment,
SUM(o.order_value) AS total_spend,
r.risk_score
FROM snowflake.crm.customers c
JOIN databricks.sales.orders o
ON c.customer_id = o.customer_id
JOIN postgres.compliance.risk_scores r
ON c.customer_id = r.customer_id
WHERE o.created_at >= '2026-01-01'
GROUP BY 1, 2, 4 ORDER BY total_spend DESC;
✓ 84,201 rows · 1.4s · Query Director: Trino
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# Connect your agent to the Zetaris MCP server
from zetaris import DataSteward
# Your IAM role — not ours
steward = DataSteward(
endpoint="https://z-gateway.your-domain.com",
auth="iam-role"
)
result = steward.query(
"Total revenue by segment Q2 2026,
excluding churned accounts"
)
# result.sql shows exactly what ran
✓ Data product: revenue_by_segment · SQL logged · 0.9s
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