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TextQL

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Enterprise AI data analytics platform that deploys data analyst agents to query and analyze messy data workloads in plain English.

Веб-сайт:https://textql.com/
Добавлено:13 июл. 2026 г.
Посетители в месяц:
19.7K
Социальные сети и электронная почта:
AI data analyticsdata analyst agentsnatural language queryingno SQLenterprise AISlack integration
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TextQL
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Информация об инструменте

Что такое TextQL?

TextQL is an enterprise AI data analytics platform that deploys scalable AI data analyst agents. These agents connect to existing warehouses, databases, and apps to deliver actionable insights from complex, messy data without requiring SQL or data migration.

Основные функции

  • Natural Language Querying

    Ask business questions in plain English and receive immediate analysis that can be acted on without writing SQL.

  • Slack Integration

    Query data and receive AI-powered insights directly inside Slack conversations.

  • Shared Ontology

    Establish a single accurate source of truth so the entire organization uses consistent definitions and language for data.

  • Data Connectors

    Connect to existing warehouses, lakes, databases, and apps with no data migration or pipeline rebuilds required.

  • Automated Playbooks

    Schedule recurring analyses and automatically deliver critical insights via email or other channels.

  • Flexible Secure Deployment

    Deploy in public cloud, VPC, or on-premises environments, including air-gapped setups that keep data and infrastructure under full customer control.

  • Live Persistent Dashboards

    Generate auto-updating dashboards from data sources in minutes.

  • Large-Scale Table Handling

    Work across hundreds of thousands of tables with minimal configuration.

Варианты использования

  • #1

    Customer Metrics Analysis

    Answer questions such as customer churn rates by segment and identify drivers directly from data.

  • #2

    Provider Fraud Analysis

    Analyze risk and revenue data for Medicare provider fraud detection.

  • #3

    Population Health Analytics

    Merge clinical and business data sources to analyze population health trends and extract real-time insights.

  • #4

    Automated Business Reporting

    Schedule and deliver recurring reports such as weekly revenue summaries.

Лучше всего для:Data teamsBusiness teamsClinical and engineering teamsEnterprise organizations with messy multi-source data

Тарифные планы

Homepage states 'Bring everyone in, for free' for rolling out self-serve access to business teams; no full pricing tiers or costs are detailed.

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Часто задаваемые вопросы

What is TextQL?
TextQL is an enterprise AI data analytics platform that deploys scalable AI data analyst agents to connect to existing warehouses, databases, and apps, delivering actionable insights from complex data without requiring SQL or data migration.
Does TextQL require users to write SQL?
No. Users can ask business questions in plain English and receive immediate analysis that can be acted on without writing SQL.
What data sources can TextQL connect to?
TextQL connects to existing warehouses, lakes, databases, and apps with no data migration or pipeline rebuilds required. Supported connectors include BigQuery, Redshift, Snowflake, Supabase, ClickHouse, Postgres, Azure, Aurora, Tableau, Power BI, Databricks, MotherDuck, MySQL, SQL Server, Slack, API Connectors, and MCP Connectors.
Where can TextQL be deployed?
TextQL can be deployed in public cloud, VPC, or on-premises environments, including air-gapped setups that keep data and infrastructure under full customer control.
How is TextQL priced?
Full pricing tiers or costs are not clearly published by the official source. The homepage states 'Bring everyone in, for free' for rolling out self-serve access to business teams.
Can TextQL work with large numbers of tables?
Yes. TextQL can work across hundreds of thousands of tables with minimal configuration.

TextQL Контакты и социальные сети

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AI data analyticsdata analyst agentsnatural language queryingno SQLenterprise AISlack integration
Языканглийский
Последнее обновление16 июл. 2026 г.
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