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Query data in plain english

Query data in plain english

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About

Findly: The AI Chatbot for Your Data Warehouse.

Get accurate, actionable data insights in minutes, without needing to learn SQL or Python. Ask questions in plain English and see results that are easy to understand.

Bridge the Gap Between Business Questions and Data Queries

Natural language processing allows even those without training in programming to access data insights by simply asking questions. This technique makes it quick and easy for business personnel to find the answers they need without any extra help.

Reduce Time to Insight (TTI)

Get the information you need to make decisions right away, rather than wasting days between zoom meetings, back and forth, miscommunication, slack threads and waiting time.

Reduce Turnover Impact

Too often, companies rely on a few data professionals and their in-depth knowledge of the company’s data warehouse. If these key staff members leave the organization, it can have drastic negative consequences for operations. Findly.ai mitigates this issue by lessening the reliance on individual data professionals and their specific know-how of the data warehouse

.Improve Onboarding Efficiency

Simplify the onboarding of data professionals by allowing them to ask business questions and see them translated into SQL queries. Streamline the onboarding of any professional by allowing them to ask any question about the business and receive an answer in seconds.

Free Up Software Engineering Time

With findly.ai, businesses can get employee-generated insights without needing any SQL or data interpretation expertise. This makes life easier for software engineers who are often bombarded with requests to run queries and frees them up to focus on what they’re good at.

Ask Questions Directly On Slack

Simply ask a question on Slack, and get an insightful response directly from your data warehouse

Database & Data Warehouse Support

All databases and data warehouses that can run SQL queries are compatible with this product.

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