Business intelligence
Kater
Turn Data Into Decisions
- 0community votes
- 18DR by Ahrefs +1 (up) since last check
Ahrefs Domain Rating listed 6 Nov 2026, relisted 28 Oct 2026.
A data workflow builder that combines a unified data model with SQL to generate personalized reports and guide decision-making.
What it is
Kater: the homepage
Kater is a data workflow builder designed to transform how companies interact with data. Instead of static dashboards that only show what happened, Kater uses structured decision trees to guide teams toward actionable insights and clear next steps. The platform combines a unified data model with SQL, allowing both data professionals and business stakeholders to get answers without ambiguity. Kater's AI agents learn from past playbooks to provide relevant, context-aware answers, while its shared semantic layer ensures everyone works from the same metric definitions. The platform integrates with major data warehouses including Snowflake, BigQuery, Databricks, Redshift, and MS-SQL, with setup taking as little as 15 minutes.
Listed capabilities
- Data Playbooks - Structured decision trees that guide insights and next steps
- Butler AI - Self-serve answers to 80% of follow-up questions
- Shared semantic layer - Unified definitions and logic for consistent answers
- Business Question Mapping - Intuitive flowchart-style navigation
- Multi-warehouse integration - Snowflake, BigQuery, Databricks, Redshift, MS-SQL
- Enterprise security - SOC 2 Compliant, ISO 27001 Certified
- Encrypted data in transit and at rest
- PII column labeling for privacy compliance
- 15-minute setup time
Pricing
Pricing model: Free trial
Free trials available; annual contracts determined by data size and complexity. Contact for details.
Follow Kater for an email about each milestone, update and new product they post, in a daily summary.
Kater metrics
| Metric | Value |
|---|---|
| Domain Rating | 18 +1 (up) since last check |
| Trust Flow | 4 no change since last check |
| Citation Flow | 21 no change since last check |
| Referring domains | 157 no change since last check |
| External backlinks | 570 no change since last check |
Ahrefs Domain Rating listed 6 Nov 2026, relisted 28 Oct 2026. Listed under topic: Arts/Performing Arts (3). Majestic listed 26 Oct 2026, relisted 26 Oct 2026. Link data listed by Majestic. Trust Flow, Citation Flow and Topical Trust Flow are trademarks of Majestic-12 Ltd.
Kater domain listing data
Show the listing data
| Domain age | 3 years |
|---|---|
| Registered | |
| Expires | |
| Registrar | Cloudflare, Inc |
| DNSSEC | Not signed |
Kater launch receipt entry
| Measure | At launch, then latest |
|---|---|
| Domain Rating (Ahrefs) | 17 to 18 +1 (up) since launch 26 Oct 2026, then 6 Nov 2026 |
| Trust Flow (Majestic) | 4 first measured 26 Oct 2026 |
| Referring domains (Majestic) | 157 first measured 26 Oct 2026 |
Day 10 since launch. Next receipt: day 30, 25 Nov 2026. We show what changed, not what caused it: many things affect these numbers. Nothing here is estimated.
Before you launch
The playbook on SaaS Directory List lists what to prepare, what to post on launch day and where else to list your product.
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Quick answers
How much does Kater cost?
Kater offers free trials, with annual contracts determined by the size and complexity of your data and company. Contact Kater for specific pricing details.
What data warehouses does Kater integrate with?
Kater integrates with Snowflake, BigQuery, Databricks, Redshift, and MS-SQL. Custom connectors for unlisted warehouses can be built in approximately one day.
How long does it take to set up Kater?
Setup takes as little as 15 minutes. Kater provides white-glove onboarding and concierge services to ensure you start seeing value immediately.
How will Kater use my data?
Kater does not store any customer data in its application database or use data to train any LLM. All data is stored locally in your browser's cache, prioritizing privacy and security.
Does Kater use AI to write SQL?
Kater uses AI only to help data team members write SQL when building Playbooks, keeping humans in the loop. For non-technical users, it uses defined YAML data model files instead to ensure accuracy for business-critical functions.
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