TextQL

Deploy Enterprise Scale Data Analyst Agents to handle your messy data workloads.

Pricing model

Free Tier

Rating

★ People love it

Time to value

Quick Setup (< 1 hour)

You can use TextQL to analyze your data by asking questions in natural language instead of writing SQL queries. It connects to your existing databases and data warehouses, automatically understands your data structure, and provides AI-powered analysis. You can integrate it with Slack for team collaboration, create dashboards and reports, and get insights from messy data sources. The AI agent called Ana can break down complex requests, run analyses autonomously, and deliver actionable insights with complete audit trails of every query.

What TextQL does

Connect databases and data warehouses to the systemAsk business questions using everyday languageCreate automated dashboards for executive reportingSet up Slack integration for team data accessBuild organizational data definitions and ontologiesGenerate fraud detection analysis from healthcare dataTrack customer metrics and churn analyticsCreate financial performance reports and visualizationsAsk questions in plain English without SQL knowledgeAI agent autonomously breaks down complex data requestsIntegrates directly with Slack for team collaborationAutomatically learns database schema and structureMaintains complete audit trail of all queriesWorks with existing data warehouses and sourcesCreates shared organizational data definitionsProvides instant answers where teams already work

Pricing breakdown

Pricing model: Free tier, Paid

PlanList price

AnalystFree

Team$250 / mo

Tutorials & Demos

Frequently asked

Teams, Azure, GCP, Snowflake, Databricks, BigQuery, PostgreSQL, dbt, Slack, Microsoft Teams, Tableau (Output), Tableau, Slack App Directory, Snowflake Data Cloud, Google BigQuery, dbt (Data Build Tool), Amazon S3, Microsoft Azure, dbt (Semantic Layer), Tableau (as an output destination)