In the field guide

datagaps

datagaps.com

Datagaps offers an AI-powered DataOps platform that automates data testing, validation, and quality monitoring to ensure trusted data for analytics and compliance. It provides end-to-end data validation across ETL pipelines, BI dashboards, data quality, and AI model inputs with embedded Agentic AI and patented validation methodology.

The product, beyond the pitch

Automatically researched · Not editorially reviewed · Sources checked Nov 1, 2026

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A good fit for

Enterprises requiring end-to-end data validation and governance across complex data pipelines and BI platforms.

Know the limitations

Not confirmed yet.

What you can do

Automated SOX reconciliation across trading and risk pipelines for banking and financial services.
HIPAA-compliant validation and automated EHR migration testing for healthcare and life sciences.

Features

Automated data validation and ETL testing with agentic AI.
Smarter BI validation for Power BI, Tableau and Oracle Analytics accelerated by AI agents.
Proactive data quality monitoring with agentic AI to predict, prevent, and govern data quality issues.
Compliant, realistic synthetic test data generation enabled by agentic AI.

Integrations

Open APIs, webhooks, and connectors to integrate with existing data stacks and DevOps pipelines.

Platforms & data export

Supports cloud data warehouses like Snowflake, Databricks, Azure Synapse, BigQuery, Redshift, and BI platforms including Power BI, Tableau, Oracle Analytics.

datagaps pricing

No plans recorded yet.

THE COST FOR YOUR TEAM

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Published plan prices for your team size and usage. Results update as you type. Taxes, currency conversion and unlisted add-ons are excluded, and anything the source did not state is called out rather than guessed.

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Known monthly subtotal

$0.00/month

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Tool / plan	Monthly	Per year	What this assumes
datagaps	No pricing recorded yet. Check the official site, or ask the owner to add it.

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What changed

2 recorded changes · latest 11/1/2026

Changes to the facts recorded here, not a live scan of every vendor update. Save this tool to follow updates in your account.

11/1/2026
Updated: best for, features, integrations, platforms, sources, summary, use cases, walkthrough
See recorded changes
bestFor
Before: ["Enterprises requiring end-to-end data validation and compliance across complex data pipelines and BI platforms"]
After: ["Enterprises requiring end-to-end data validation and governance across complex data pipelines and BI platforms."]
features
Before: ["Automated data validation and ETL testing with agentic AI","Smarter BI validation for Power BI, Tableau and Oracle Analytics accelerated by AI agents","Proactive data quality monitoring with agentic AI to predict, prevent, and govern data issues","Compliant, realistic synthetic test data generation enabled by agentic AI","PII data masking to protect sensitive data during ingestion, preview, and processing"]
After: ["Automated data validation and ETL testing with agentic AI.","Smarter BI validation for Power BI, Tableau and Oracle Analytics accelerated by AI agents.","Proactive data quality monitoring with agentic AI to predict, prevent, and govern data quality issues.","Compliant, realistic synthetic test data generation enabled by agentic AI."]
integrations
Before: []
After: ["Open APIs, webhooks, and connectors to integrate with existing data stacks and DevOps pipelines."]
platforms
Before: []
After: ["Supports cloud data warehouses like Snowflake, Databricks, Azure Synapse, BigQuery, Redshift, and BI platforms including Power BI, Tableau, Oracle Analytics."]
sources
Before: [{"url":"https://www.datagaps.com/","label":"Datagaps | Gen AI-Powered Automated Cloud Data Testing"},{"url":"https://www.datagaps.com/video/","label":"DataOps Demo Videos | Datagaps"},{"url":"https://www.datagaps.com/blog/dataops-suite-release-2025-3-0-0-product-features-updates/","label":"DataOps Suite Update v2025.3.0.0: Product Boost & New Features"}]
After: [{"url":"https://www.datagaps.com/","label":"Datagaps | Gen AI-Powered Automated Cloud Data Testing"}]
summary
Before: "Datagaps is an AI-powered DataOps platform that automates data testing, validation, and quality monitoring across the entire data lifecycle, including ETL pipelines, BI dashboards, and AI model inputs. It offers a unified platform with embedded Agentic AI, ensuring data trustworthiness, compliance, and governance with features like automated test generation, self-healing tests, and audit trails."
After: "Datagaps offers an AI-powered DataOps platform that automates data testing, validation, and quality monitoring to ensure trusted data for analytics and compliance. It provides end-to-end data validation across ETL pipelines, BI dashboards, data quality, and AI model inputs with embedded Agentic AI and patented validation methodology."
useCases
Before: ["Automated SOX reconciliation across trading and risk pipelines for audit-ready reports in banking and financial services","HIPAA-compliant validation, PII-safe AI pipelines, and automated EHR migration testing in healthcare and life sciences"]
After: ["Automated SOX reconciliation across trading and risk pipelines for banking and financial services.","HIPAA-compliant validation and automated EHR migration testing for healthcare and life sciences."]
walkthrough
Before: ["Set up ETL Validator connections across sources with reusable tests","Validate BI reports using golden records and AI for accurate KPIs and dashboards","Define and automate data quality rules for accuracy, completeness and consistency"]
After: []
9/24/2026
Updated: best for, features, summary, use cases, walkthrough
See recorded changes
bestFor
Before: ["Enterprises requiring compliance and complex data validation across industries such as banking, healthcare, retail, and hospitality."]
After: ["Enterprises requiring end-to-end data validation and compliance across complex data pipelines and BI platforms"]
features
Before: ["Automated data validation and ETL testing with agentic AI.","Smarter BI validation for Power BI, Tableau and Oracle Analytics.","Proactive data quality monitoring with agentic AI predict, prevent, govern.","Compliant, realistic synthetic test data generation enabled by agentic AI.","PII data masking to protect sensitive data during ingestion, preview, and processing."]
After: ["Automated data validation and ETL testing with agentic AI","Smarter BI validation for Power BI, Tableau and Oracle Analytics accelerated by AI agents","Proactive data quality monitoring with agentic AI to predict, prevent, and govern data issues","Compliant, realistic synthetic test data generation enabled by agentic AI","PII data masking to protect sensitive data during ingestion, preview, and processing"]
summary
Before: "Datagaps is an AI-powered DataOps platform that automates data testing, validation, and quality monitoring to ensure trusted data for analytics and compliance. It provides end-to-end data validation from source models to BI dashboards and AI outputs, supporting enterprises across various industries with compliance and data complexity requirements."
After: "Datagaps is an AI-powered DataOps platform that automates data testing, validation, and quality monitoring across the entire data lifecycle, including ETL pipelines, BI dashboards, and AI model inputs. It offers a unified platform with embedded Agentic AI, ensuring data trustworthiness, compliance, and governance with features like automated test generation, self-healing tests, and audit trails."
useCases
Before: ["Automated SOX reconciliation across trading and risk pipelines for audit-ready reports in banking and financial services.","HIPAA-compliant validation, PII-safe AI pipelines, and automated EHR migration testing in healthcare and life sciences."]
After: ["Automated SOX reconciliation across trading and risk pipelines for audit-ready reports in banking and financial services","HIPAA-compliant validation, PII-safe AI pipelines, and automated EHR migration testing in healthcare and life sciences"]
walkthrough
Before: ["Set up ETL Validator connections across sources with reusable tests.","Validate BI reports using golden records and AI for accurate KPIs and dashboards.","Define and automate data quality rules for accuracy, completeness and consistency."]
After: ["Set up ETL Validator connections across sources with reusable tests","Validate BI reports using golden records and AI for accurate KPIs and dashboards","Define and automate data quality rules for accuracy, completeness and consistency"]