Dataherald lets you embed Natural Language to SQL (“NL-to-SQL”) into your product. The NL-to-SQL API, built with an LLM (such as GPT), allows users to conduct no-code data analytics, pull reports, and conduct complex data queries using just natural language.
Hey Product Hunt community!
We’re Amir and Anuj from Dataherald. There have been countless game-changing applications of AI, but one area that has remained uncharted is NL-to-SQL. But fear not - we’re changing that. We’ve built a cutting-edge NL-to-SQL engine, meticulously crafted to be the fastest and most accurate in the market, delivering an unmatched developer experience!
The Problem
Developers struggle to build NL-to-SQL into products because LLMs do not work out-of-the-box. LLMs do not:
1. Utilize metadata and business definitions since they are not already stored in the relational database
2. Conduct complex SQL queries, such as self joins, multiple sub-queries, or rarer operations like windowing, partitioning, lags, temporal calculations, etc.
3. Create NL-to-SQL training dataset(s) for fine-tuned models
4. Assess the accuracy of AI-generated SQL
The Solution
Dataherald’s API solves these challenges by allowing developers to:
- Add business context from various sources (data dictionaries, DBT, Confluence docs, Google docs, etc.)
- Identify relevant data tables
- Fine-tune NL-to-SQL LLMs (including GPT-4!) specific to their data
- Assess confidence levels in AI-generated SQL
All this happens with a few simple API calls.
Dataherald’s NL-to-SQL API unlocks data access wherever needed:
1. Enabling Complex Data Queries in SaaS Apps: For example a large payroll software company uses Dataherald to embed NL-to-SQL into their front end so that users can ask questions like “How much did I spend on full stack engineers in our European offices in Q2 2023 and how is that trending?”
2. Democratizing Data Insights: Companies integrate our API into Slack, enabling self-serve data requests, and freeing up valuable time for data analysts.
3. Automate Customer Support with Chatbots: Customer support teams dealing with data-heavy queries leverage Dataherald in chatbots, automating inquiries regarding user data.
Seamless Integrations:
Dataherald is seamlessly integrated with all major data warehouses, including PostgreSQL, Databricks, Snowflake, BigQuery, and DuckDB.
Sign up before January 31 to get $500 in credits.
Happy heralding :)
interesting for users looking to integrate advanced data analysis into their regular workflows without the need for specialized skills.
About Dataherald on Product Hunt
“Embed NL-to-SQL into your product”
Dataherald launched on Product Hunt on January 24th, 2024 and earned 126 upvotes and 8 comments, placing #18 on the daily leaderboard. Dataherald lets you embed Natural Language to SQL (“NL-to-SQL”) into your product. The NL-to-SQL API, built with an LLM (such as GPT), allows users to conduct no-code data analytics, pull reports, and conduct complex data queries using just natural language.
Dataherald was featured in API (98.1k followers), Artificial Intelligence (466.8k followers) and Data & Analytics (5.6k followers) on Product Hunt. Together, these topics include over 101.2k products, making this a competitive space to launch in.
Who hunted Dataherald?
Dataherald was hunted by Michael Seibel. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
Want to see how Dataherald stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.
Michael Seibel