Tepun vs Looker

Analytics without a LookML modeling project

Last updated: 2026-07-20

Tepun is a no-code AI report builder and an alternative to Google Looker. Looker deployments commonly use engineers to define a semantic model in LookML. Tepun instead uses AI-assisted schema understanding for its reporting workflow.

Both serve governed analytics on top of your warehouse. Tepun's difference is time-to-value — you can ask a question the day you connect, without a multi-week modeling phase.

Tepun is an AI report builder that connects to databases such as PostgreSQL, MySQL, and Snowflake and turns plain-English questions into reviewable reports, charts, and dashboards while reducing manual SQL authoring.

Tepun vs Looker at a glance

Comparison of Tepun and Looker capabilities
CapabilityTepunLooker
Setup Connect, inspect the schema, and ask Modeled deployments commonly begin with LookML
Skill required Designed for business users; results should be reviewed Modeled Looker deployments commonly involve LookML and data engineering
Report authoring Ask in plain English; AI builds it Explore within modeled dimensions/measures
Time to value Designed for rapid first-report workflows Depends on the modeling and governance scope
Natural-language queries Core capability Limited (Gemini in Looker, model-dependent)
Data connections PostgreSQL, MySQL, Snowflake, CSV, and more Warehouse-centric via LookML

Why teams choose Tepun

No LookML authoring

Tepun uses schema metadata and AI-assisted query generation instead of requiring users to author LookML.

Business-user friendly

No engineering team needed to stand up or maintain a modeling layer.

Faster time-to-value

Ask a real question on day one instead of after a modeling sprint.

Frequently asked questions

Is there an alternative to Looker that doesn't need LookML?

Yes. Tepun is a no-code AI report builder that reads your database schema directly, so there is no LookML semantic model to build or maintain before you can explore data.

How is Tepun different from Looker?

Looker relies on a LookML model that data engineers define up front. Tepun uses AI to interpret your schema and your plain-English question, so business users get answers without an engineering-led modeling project.

Can non-engineers use Tepun instead of Looker?

Yes. Tepun is designed for non-technical business users — there is no modeling language or SQL to learn.

Comparison information is a general product overview and may change. Verify current capabilities, packaging, and pricing with each vendor. Third-party product names and trademarks belong to their respective owners.

See it on your own data

Build a report from your own database using a plain-English question, then inspect the generated logic.

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