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January 30, 2023
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Findly

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Outputs:
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Query data in plain English, no coding required.
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Findly is an artificial intelligence-powered Natural Language Generation tool designed for seamless integration with databases for the purpose of easily obtaining business data insights.

Findly's capabilities encompass query generation for business data, visualization of data, and report generation. The tool enables users to communicate with their data effectively and promotes insightful collaboration.

Specific use cases of Findly include identifying hidden trends, optimizing operations, and leveraging analytics for content optimization. Findly supports various export formats offering flexibility for users.

Furthermore, the tool features easy integration with other platforms including Slack, facilitating a user-friendly, graphical view of query results. Findly offers a template feature enabling quicker data analysis by providing a range of pre-designed templates catered to various business needs.

The tool also allows for manual creation and customization of data comparison. Findly has an AI-powered query generator designed for accuracy and reliability, which allows data teams to validate queries with ease.

Security is a priority with Findly as data remains on the user's server, ensuring privacy and integrity of information. Lastly, the tool supports swift data integrations with its flexible architecture.

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Pricing

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Freemium
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Billing frequency
Monthly
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Findly was manually vetted by our editorial team and was first featured on January 30th 2023.

Pros and Cons

Pros

Easy-to-use chatbot
Generates actionable data insights
No SQL or Python knowledge required
Uses natural language processing
Reduces Time To Insight (TTI)
Eliminates reliance on data professionals
Simplifies onboarding process
Saves software engineering time
Allows questions on Slack
Compatible with all SQL databases
Provides easy-to-understand results
Mitigates turnover impact
Supports database and data warehouse
Reduces miscommunication and waiting time

View 9 more pros

Cons

Lacks APIs integration
Limited to SQL databases
Only works on Slack
No Python interpretation support
Possibly long chatbot response times
User-specific data interpretation issues
Lacks multi-platform support
No direct databank integration
Dependent on English proficiency
Limited onboarding efficiency improvements

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Q&A

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