Software and SaaS

Ship data products as fast as you ship code.

One platform for catalog, glossary, lineage and data products, readable by people and by AI agents. Tell us what is on your desk and we will show you the part that matters.

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What is on your desk this quarter?

What your AI team needs

Answers grounded in your own definitions

A conversational analytics tool or coding agent only answers well when it knows what your metrics mean and which tables to use.

What breaks today

Agents write ad-hoc SQL and count the wrong thing
The same question returns different numbers
Context lives in Slack threads and wikis

With Dawiso

Governed glossary, lineage and data products in one context layer
Exposed to any MCP-compatible agent through the Dawiso MCP server

9,000+ MCP calls during implementation at Seznam.cz

In production at data teams running modern stacks

How it works

From the events table to the product metric, in one place.

Metadata scan · 4 sources

Snowflake · analytics warehousescanned
dbt · transformationsscanned
Databricks · ML featuresscanning
Tableau · product dashboardsqueued

Tables, columns, models and dashboards are picked up automatically, with no manual cataloguing.

Lineage · Weekly active users

app.events
stg_sessions
fct_active_users
WAU dashboard

SELECT date_trunc('week', s.started_at)
  AS activity_week,
  count(DISTINCT s.user_id) AS wau
FROM stg_sessions s GROUP BY 1

Column-level lineage parsed from your own SQL.

Regulation coverage

What each regulation asks for, and how you show it.

Regulation	What it asks	Your evidence in Dawiso
EU AI Act	Documented data and governance behind AI systems	Definitions, owners and lineage for the data that feeds each AI feature
GDPR	Know where personal data lives and how it flows	Personal data classified in the catalog and followed through lineage across services
SOC 2	Controlled, traceable changes to the data you rely on	Approval workflows and change history on every definition and asset
DORA	ICT risk management for vendors serving financial clients	Named owners and stewards per data asset, with lineage to show what depends on it

Customer story

One context layer for people and AI agents.

Seznam.cz · Czech internet leader

How Seznam.cz grounded its conversational analytics in governed definitions

Lineage across Keboola, Snowflake and Tableau, a registry of owned data products, and an MCP server that hands the analytics tool the company's own definitions before it writes a query.

681,000: governed objects
596,947: relationships between objects
31: MCP users

“Before Dawiso, 'data product' was more of a buzzword for us; now it's a concrete, owned entity our teams actually work with.”
Jakub Trefilík, Senior Product Manager, Seznam.cz

Read the Seznam.cz story

3,200+Metabase reports and dashboards connected via a custom ingestion application

100,000+scanned objects in Databricks

Go-live

A pilot that shows value within a few weeks.

Day oneConnect and scanScanners read the warehouse, dbt and BI. The MCP server can be on from the start.
First weeksLineage and glossaryColumn-level lineage from your SQL, product metrics defined once.
NextOwners and data productsDomain owners assigned, first data products published with contracts.
Around day 60Fully operationalThe working solution your teams and agents use every day.

Questions tech companies ask us

Does Dawiso work with our modern data stack?

Dawiso connects to 40+ data sources including Snowflake, Databricks, dbt, Kafka, PostgreSQL, Redshift, Power BI, Tableau, and more. The MCP server enables AI agent integration directly with your catalog. For internal services or custom sources, the REST API covers anything without a native connector. See the full list on our Connectors page.

How long does implementation take?

Most tech companies go live with a working catalog in weeks. Automated metadata scanning eliminates manual work, and the SQL Parser generates lineage from your existing code without custom development. SaaS deployment means no infrastructure setup on your side.

Can Dawiso help us with EU AI Act compliance?

Yes. Dawiso catalogs AI and ML models alongside data assets, documenting model inputs, training data, outputs, versions, and owners. This provides the documentation trail the EU AI Act requires for high-risk AI systems used in recommendations, pricing, content moderation, and other product features.

How does Dawiso support data products?

Data products in Dawiso let you package governed datasets with owners, descriptions, freshness SLAs, and quality scores. Business teams discover and consume data through a searchable marketplace. Data engineers define the product once and every consumer gets the same governed, documented dataset.

What deployment options are available?

Dawiso is available as SaaS, on-premise, or hybrid with full feature parity. Most software companies choose SaaS for zero-ops deployment. Enterprise authentication via Azure AD, LDAP, and SAML is included in every option.

How is Dawiso priced?

Dawiso is priced per user, not per data source or scanned object. You roll out governance to every team without per-connector fees. See our pricing page or book a demo for a quote tailored to your team size.

Bring one metric. We will trace it with you.

A 30-minute session with our team, built around your metric, your stack and the agents you want to ground.