Videos from AICowan
Explore Gary’s videos about Zentarra, data platforms and AI.
Visit the YouTube channel ↗ (opens in a new tab)RESOURCES
See the work.
Understand the approach.
A product walkthrough, practical data-platform insights and a short history of Zentarra’s development.
PRODUCT WALKTHROUGH
Trust and data quality in Zentarra
Gary’s recorded demonstration explores the checks that help a user assess an analytical answer: validation rules, trust scores, query-level signals, data freshness and validation history. It also shows analysis blocking when critical data-quality checks fail.
Watch on YouTube ↗ (opens in a new tab)
This is an earlier product recording, linked from AICowan’s original Videos page. It is useful context for the approach; the current Product page describes the 4.5 offer.
What to look for
- Which data-quality checks were applied to the underlying data?
- What does the trust score explain about this result?
- How current is the data, and what does validation history reveal?
- When do critical quality issues prevent analysis?
These are reading notes, not a transcript. A trust score summarises configured checks; it does not guarantee that an answer is correct.
KEEP EXPLORING
Product and practice.
Articles & updates
Follow AICowan’s posts on Microsoft Fabric, SQL, governed analytics and product development.
Read on LinkedIn ↗ (opens in a new tab)Getting started
Follow the first steps, learn what to check in an answer and export results before your evaluation expires.
Read the guide →See the worked example →
PRODUCT MILESTONES
How Zentarra has developed
A compact history, followed by the current early-access offer. Historical milestones describe their original release scope.
Version 1 — First working queries
Natural-language questions translated into SQL and executed against a database.
Version 2 — Visibility and validation
SQL transparency, query validation and improvements to the interface and reliability.
Version 3 — Reusable analysis
Clarifying questions, visible assumptions, charts, exports, saved queries and chat history.
Version 3.5 Alpha — July 2026
Data-quality validation, trust scoring, freshness, validation history and analysis blocking.
Version 4.5 — Current managed early access
The current offer brings governed definitions, workspace access controls, dashboards and reusable reporting together. Availability and configuration are agreed during onboarding.
See current capabilities →
Earlier milestones are drawn from AICowan’s published release history. This is a development overview, not a complete changelog or a promise of future functionality.