Datalang is an AI-powered platform that transforms the way teams interact with business data by enabling natural language queries instead of traditional code or SQL. It empowers business users, product managers, analysts, and operations teams to ask questions about their data in plain English and receive immediate, accurate answers.
Built with the vision to democratize data access, Datalang eliminates the bottlenecks caused by limited data engineering resources. It allows non-technical users to explore data, create reports, and derive insights without relying on technical teams or complex BI tools.
Features
Datalang offers a wide range of features that simplify data analysis and make business intelligence more accessible to everyone.
Natural Language to SQL
Users can type questions in plain English, and Datalang instantly translates them into optimized SQL queries. This feature allows anyone to retrieve and analyze data without writing code.
Instant Data Insights
Datalang connects to existing databases and delivers quick answers to business questions, enabling faster decision-making and insight generation.
Customizable Metrics
Teams can define their own business metrics and KPIs within Datalang, ensuring that queries return results aligned with company-specific definitions.
Secure Data Access
The platform respects role-based access controls and connects to databases without moving or replicating data, maintaining a secure data environment.
Multi-Source Compatibility
Datalang supports integrations with popular SQL databases such as PostgreSQL, MySQL, BigQuery, and Snowflake, making it adaptable to a wide range of modern data stacks.
Slack and Web App Integration
Users can ask questions via Slack or the Datalang web interface, making it easy to incorporate data querying into daily workflows without switching tools.
Self-Improving Query Engine
Datalang learns from user feedback and improves its query accuracy over time. This continuous learning ensures better performance with increased usage.
Version History and Audit Logs
The platform keeps a history of queries and results, providing transparency, auditability, and consistency across teams.
No-Code Experience
Everything is handled through intuitive interfaces, meaning no dashboards, coding, or manual SQL writing is required for everyday data analysis.
How It Works
Datalang connects securely to a company’s database using a read-only connection. Once connected, it indexes the data schema and begins learning the structure, relationships, and common terminology used in the data.
Users can then ask business questions using natural language through the web app or Slack integration. For example, a user might type “What were our top 5 selling products last quarter?” or “Show me churn rate by region for the last 12 months.”
The AI engine interprets the question, converts it into SQL, and runs the query on the live database. The result is returned in plain text or simple tables, allowing the user to make decisions quickly.
The platform also enables the definition of custom metrics and dimensions, allowing users to standardize how performance indicators are queried across teams. Admins can manage user permissions, ensuring that sensitive data is only accessible to authorized users.
Use Cases
Datalang supports multiple teams and departments across industries by simplifying access to data.
Product Teams
Product managers can analyze feature adoption, usage metrics, and customer behavior without depending on a data team to write queries.
Marketing Teams
Marketers use Datalang to track campaign performance, conversion rates, and customer acquisition metrics in real time.
Sales Operations
Sales teams query customer data, deal progression, and forecast metrics directly from the CRM database to make faster decisions.
Customer Success
CS teams monitor churn, engagement, and onboarding metrics, enabling proactive retention strategies based on live data.
Finance and Strategy
Financial analysts can quickly run revenue and cost breakdowns, operational KPIs, and model performance without building dashboards or waiting for reports.
Founders and Executives
Leadership teams use Datalang to get direct access to business-critical data, reducing dependency on manual reporting or data analyst bandwidth.
Pricing
Datalang offers a free plan and custom enterprise pricing based on team size, data complexity, and usage. As of the latest update on the official website:
Free Plan
The free version includes basic features, ideal for small teams or startups looking to explore natural language querying with limited data sources.
Enterprise Plan
Custom plans are available for larger teams and organizations. These plans include enhanced security, priority support, advanced configuration, and SLA-backed performance.
Interested companies can request early access or a personalized demo through the website to get more detailed pricing information tailored to their specific use case.
Strengths
Datalang’s core strength lies in its ability to democratize data access through natural language. This bridges the gap between technical and non-technical teams, enabling faster decision-making across organizations.
Its real-time SQL translation engine, combined with Slack and web app access, makes it highly versatile for teams working in fast-paced environments. Datalang’s learning system improves over time, meaning the more it’s used, the more accurate and useful it becomes.
The secure, read-only architecture also ensures data privacy and control, which is crucial for companies handling sensitive or regulated data.
Drawbacks
As a newer tool, Datalang may not yet support the same depth of visualization and reporting as full-featured BI platforms like Looker or Tableau.
Additionally, complex multi-join queries or advanced analytical functions may still require oversight or refinement by technical users, especially in the early stages of deployment.
The platform is still in its early access phase, and public customer case studies or testimonials are not yet widely available, making it difficult for some teams to evaluate without requesting a demo.
Comparison with Other Tools
Datalang can be compared to tools like ThoughtSpot, SeekWell (now part of ThoughtSpot), and ChatGPT plug-ins for SQL querying.
ThoughtSpot is known for search-driven analytics but may be more enterprise-focused with a steeper learning curve. Datalang, by contrast, is built for simplicity and integrates more naturally into daily workflows like Slack.
Compared to self-hosted AI tools or SQL agents, Datalang offers a more user-friendly, managed experience with security and usability prioritized. While GPT-based tools can answer general questions, Datalang is fine-tuned specifically for business data interactions.
Customer Reviews and Testimonials
As of now, the Datalang website does not display public customer reviews or case studies. The platform is currently in early access, and businesses are invited to request demos or sign up for access to test the product.
Given its focus on product-led teams, startups, and non-technical business units, Datalang is clearly targeting teams that need agile, self-service analytics without the complexity of traditional BI platforms.
Conclusion
Datalang is a modern, AI-powered natural language interface for business data that simplifies the way teams interact with databases. It removes the technical barriers that prevent business users from accessing insights, making data a shared resource across departments.
With natural language queries, real-time answers, and secure integrations, Datalang helps companies become more data-driven without increasing the burden on technical teams.
For organizations looking to improve data accessibility, speed up decision-making, and reduce reliance on SQL experts, Datalang offers a smart, intuitive, and scalable solution.
