Findly

A one-sentence summary

Findly is a tool for natural language data analysis and reporting; it allows integration of marketing and business data, enabling teams to query metrics using everyday language, compare dates, create visual reports, and share the results.

Tool Introduction

Findly is operated by Conversion Pattern Inc., a company based in Delaware, United States. Its products are designed as business intelligence tools and AI-based natural language generation tools. The goal is to enable users who are not familiar with SQL or Python to obtain actionable insights from existing data.

The current free and Standard plans are focused on marketing data, with data sources including Google Analytics, Facebook Ads, Google Search Console, Shopify Ads, and BigQuery. The Enterprise plan offers additional support for any SQL database, as well as white-labeling and embedded assistants.

Findly can generate explanations and reports, but it should not replace data governance. The team still needs to determine the data sources, metric definitions, attribution windows, time zones, currencies, and filtering criteria, in order to avoid arriving at conclusions that may seem reasonable but are actually based on incorrect parameters.

Main functions

Natural language query data

Users can ask questions in plain language regarding traffic, conversion rates, advertising, or business-related data, and Findly will generate the corresponding analyses. The questions should include a time range, relevant dimensions, metrics, and a comparison benchmark, thereby reducing the need for the model to add conditions on its own.

Marketing data connection

The free version connects to Google Analytics and Facebook Ads; the Standard version adds Shopify Ads, Google Search Console, and BigQuery. The Enterprise version allows connection to additional channels as well as any SQL database.

Date comparison and visualization

Findly allows for the comparison of different date ranges and converts the query results into visual formats. When using comparisons based on year-on-year or month-on-month trends, as well as comparisons before and after certain events, it is important to take into account factors such as the number of days, seasonality, time zones, and data latency.

Report generation and export

Users can generate and export reports for use in team presentations, client reviews, and project summaries. Before exporting, it is necessary to check the chart titles, unit of measurement for the indicators, missing values, abnormal data, as well as the AI-generated textual explanations.

Report template

The platform allows for the creation and reuse of report templates, which are useful for regular weekly, monthly reports as well as client reports. The channels, objectives, and metrics included in these templates need to be adjusted according to each individual client; it is not sufficient to simply change the names.

Scheduled email reports

Plans at Standard and above offer the capability to send reports on a scheduled basis via email. When enabling this feature for the first time, the reports should be sent to an internal test email address to verify data updating, recipient permissions, attachments, and time zone settings.

Team conversations and sharing

The price comparison page lists collaboration features such as team conversations, public sharing, and save prompts. When customer data is involved, public sharing should not be used, unless access controls and link expiration mechanisms have been implemented.

Multilingual support

Findly considers multilingual support to be a core capability, enabling teams in different regions to query the same data in various languages. Professional metric names and automatic translations can still lead to ambiguity; therefore, it is necessary to have a unified glossary.

Guidance at the semantic level

The Standard approach includes semantic layer guidance, which helps teams map business terminology to consistent metrics and fields. The semantic layer needs to be maintained by business stakeholders; it cannot be entirely left to the model to define on its own.

White-label and embedded assistants

Enterprise supports white-label and embedded assistants, making it suitable for consultants, agents, or software companies to integrate analysis capabilities into their own brands and products. Authentication, data isolation, and the scope of integration must be specified through a corporate contract.

Data source and solution coverage

Working principle

1. Create a Findly workspace and invite members who truly need access to the data.
2. Connect to marketing platforms, BigQuery, or approved SQL data sources.
3. Define business metrics such as revenue, conversion rate, customer acquisition cost, channels, and dates.
4. Pose questions in natural language that include indicators, dimensions, time, and comparison criteria.
5. The system queries data and generates results, visualizations, and textual explanations.
6. Users verify the numbers and attributions by comparing them with the source platform and the semantic layer.
7. Save the confirmed analysis as a template, export it, or set up scheduled emails.
8. Update connectors, metrics, and reports based on new data and business changes.

Usage tutorial

Create a weekly marketing report

1. Connect Google Analytics to the corresponding advertising account, and ensure that the time zone and currency are consistent.
2. Define this week, last week, and the corresponding period from the same year, while excluding data that has not yet been fully returned.
3. Inquire separately about traffic, conversions, expenses, revenue, and customer acquisition cost.
4. Break down significant changes by channel, campaign, device, or region.
5. Check the original figures in the data source platform to ensure that the attribution window is consistent.
6. Save the correct chart as a template and add manual business explanations.
7. Send the test report to internal members first, and then make it available to customers or management.

Connect to BigQuery

1. Create a read-only service identity and restrict it to the datasets and tables required for analysis.
2. Delete or mask unnecessary personal identity and sensitive fields.
3. Define field descriptions, time fields, and criteria for business metrics for key tables.
4. Use limited-range queries to verify the number of rows, perform aggregations, and control costs.
5. Check whether the results generated by Findly are consistent with the manually entered query.
6. Set query budgets, log and exception alerts, and then make them available for team use.

Create a customer white-label assistant

1. Confirm the scope of white labeling, embedding, and authentication through the Enterprise solution.
2. Create a separate workspace, connectors, and access roles for each customer.
3. Define the data, metrics that are allowed to be queried, and the maximum level of detail.
4. Verify cross-client isolation and error handling in the testing environment.
5. Set the brand, prompts, support process, and sensitive questions that cannot be answered.
6. After going live, review query logs, public sharing, and member permissions.

Which users are it suitable for

• Marketing team: Use natural language to query channels, campaigns, and conversion performance.
• Digital marketing agencies: Generate standardized periodic reports for multiple clients.
• E-commerce team: Attracts customers by leveraging Shopify Ads as well as data analysis of traffic and advertisements.
• SEO team: Include Google Search Console and website analytics in the same report.
• Business Intelligence professionals: Create controlled self-service analysis interfaces for non-technical colleagues.
• Consulting firms: Deliver analyses to clients through white-label solutions and embedded assistants.
• Data team: Connects to BigQuery or SQL databases and maintains a unified semantic layer.

Typical use cases

• Compare the changes in traffic, conversions, and advertising spending between this week and last week.
• Analyze the customer acquisition costs and revenue contributions of different channels.
• Generate monthly customer reports and send emails at regular intervals.
• Save frequently used prompts and report templates to reduce repetitive configuration.
• Combine Search Console, analytics, and advertising data to create SEO reports.
• Embed a white-label data Q&A assistant within enterprises or their customer products.
• Allow sales staff to query BigQuery data while retaining read-only permissions.

Product advantages

• The free version provides 3 users and unlimited message entries, making it suitable for low-cost testing.
• Use natural language to reduce the barrier to using SQL and complex BI interfaces.
• It covers popular marketing platforms, search data, data warehouses, and SQL databases.
• It extends from ad-hoc queries to templates, exports, and scheduled email reports.
• The semantic layer provides guidance to standardize the names of metrics and the methods used for their calculation across the team.
• Enterprise offers white-label and embedded solutions, suitable for agents and software products.
• The privacy policy clearly states that customer data will not be used to train AI models without written permission.

Usage restrictions and precautions

• When natural language queries are imprecise, the system may use incorrect metrics, dimensions, or time ranges.
• Different advertising and analytics platforms use varying attribution methods, so it is not possible to directly compare all the figures.
• The free version allows only 3 users, and the data sources are limited to Google Analytics and Facebook Ads.
• The current price of Standard includes a 70% launch discount; the price may change after the promotion ends.
• Unlimited messages are subject to reasonable usage limits and speed constraints on sending, and this does not imply unlimited concurrency or automatic batch calls.
• Timed reports may be sent before the data has been fully refreshed, so it is necessary to set an appropriate delay.
• Public sharing may expose customer data; it is preferable to use controlled team permissions.
• The SQL version, white-label option, embedded solution, SAML SSO, and scope of implementation for Enterprise require confirmation through a separate contract.
• Paid services are governed by separate SaaS agreements and orders, and may override or modify the general terms on the official website.
• The platform does not provide public details regarding its complete API, SDKs, rate limits, or service status.
• AI-generated conclusions must be reviewed against the source system and the business context; they cannot be used directly for major business decisions.

Prices and packages

The prices listed below were verified on August 22, 2026, and are expressed in US dollars. The Standard plan shows a regular monthly price of $497 as well as a discounted monthly rate of $149; the total cost for an annual subscription is $1,788.

The price of $149 represents a 70% discount as clearly indicated; it should not be considered the permanent price. Before making the purchase, it is necessary to verify in the order details the duration of the discount, the price for renewal, the number of users and workspaces, the data sources, query restrictions, as well as the conditions for support and cancellation.

Platforms and integration

Privacy and data processing

Findly collects information such as names, email addresses, optional profile pictures, chat history, search results, web addresses, browser details, and the pages visited. Users can delete their chat and search history on the platform, and they can also request to view, edit, or delete their personal information.

Customer data and model training

The privacy policy states that customer data sets will not be retained, stored, or combined for use in AI training or the improvement of algorithms; nor will any AI models be trained using data from customers or data providers. Unless explicitly authorized in writing by the customer, data processing is limited to providing the services requested.

This description applies to customer data sets only; it does not mean that the platform does not store accounts, chat histories, and query results at all. The team should determine separately the actual retention periods for source data processing, result caching, chat histories, and backups.

Third parties and tracking

• When selecting the Slack integration, limited information required to establish the connection is shared with Slack.
• The platform states that it will not sell personal information to third parties.
• Google Analytics is used to collect technical data on visits and product usage.
• The website’s cookie settings also list marketing purposes such as Meta Pixel, Twitter Pixel, and Rewardful.
• Users can opt out of marketing communications and manage their preferences regarding unnecessary cookies.
• The privacy policy does not specify a fixed retention period for all categories of data.

APIs, SDKs, and open-source status

Findly offers enterprise-grade embedded assistants and database connections, but no public API documentation, official SDKs, a page detailing developer keys, or clear information regarding billing for calls is available. The embedding capability cannot be considered equivalent to a standard public API.

As of the time of verification, no official open-source repository or open-source license for Findly, as confirmed by Conversion Pattern Inc., was found. The platform and analysis engine are commercial and closed-source; projects with the same name available on the Internet cannot be considered as the official source code.

Contracts and fair use

• Users must be at least 18 years old or reach the legal age of majority in their respective region.
• Paid services are primarily governed by separate SaaS agreements and orders; in the event of any conflicts, the specific agreements take precedence.
• The general terms prohibit unauthorized automated tools, scraping, reverse engineering, and service disruptions.
• Infinity Messages have a maximum sending speed and reasonable usage limits.
• The service is provided as it is, without any guarantee of uninterrupted operation, security, or error-free performance.
• The service level, termination, responsibilities, and dispute resolution mechanisms for paid services may be specified separately in the specific agreement.

Basic information

Recommendation score

Recommendation score: 4.1 / 5. Findly combines marketing data integration, natural language queries, visualization, and periodic reporting; its free version is sufficient for small teams to test out the basic features.

The main shortcomings are that Standard operates at promotional prices, there are speed limits on the number of messages that can be sent, and no detailed information is available regarding the API and certain enterprise features. Before carrying out a formal deployment, it is necessary to standardize the metrics used, as well as to review data permissions, sharing links, and the specific terms of the SaaS contract.

Frequently Asked Questions

What does Findly do?

It allows users to query marketing and business data using natural language, and it generates visualizations, reports, and explanations. The team does not need to write SQL queries manually for each question.

Is Findly free?

There is a free version available for up to 3 users; it allows integration with Google Analytics and Facebook Ads, as well as the creation and export of reports and the use of templates.

How much is Standard?

The current page shows a 70% discount, resulting in a monthly price of $149; the original price is $497 per month. The annual payment amount is $1788. Promotional prices and renewal rates may change.

What are the limitations of the free version?

It supports a maximum of 3 users and two primary marketing data sources; it does not include scheduled email reports, advanced models, semantic layer guidance, BigQuery, or any other connectors.

Are infinite messages truly infinite?

There is no unlimited concurrency or unlimited speed. The terms specify upper limits on the sending speed as well as rules for reasonable use, in order to prevent automatic bulk submissions and abuse of the system.

Does Findly support BigQuery?

Yes, the Standard and Enterprise plans include BigQuery. When establishing a connection, read-only accounts with minimal permissions should be used, and query costs need to be controlled.

Can it be connected to any SQL database?

The Enterprise plan specifies that it supports any SQL database; however, the specific database engine, deployment network, and connection security requirements need to be confirmed by the sales team.

Can automatic reports be sent to customers?

Versions Standard and above support scheduled email reports. Before sending them automatically, it is necessary to confirm the refresh interval, recipients, access permissions, and the scope of customer data.

Are customer data used to train AI?

The privacy policy states that, without the customer’s written permission, customer data sets will not be retained or combined for training AI systems or improving algorithms. Chat histories and query results may still be stored by the account, but users can delete them.

Does Findly provide an API?

No public API or SDK documentation was found. The integration method for Enterprise’s embedded assistant needs to be determined through specific arrangements.

Is Findly open source?

It is not open source; no official open-source product repository or license issued by the operating company has been found.

Is it suitable for making major business decisions?

It can be used to identify problems and prepare for analysis, but the model may choose the wrong metrics or misinterpret the data. Major budget allocations, marketing efforts, and customer commitments must be reviewed by those in charge of data and business operations.

Summary

Findly is suitable for teams that want marketing, consulting, and management personnel to have more direct access to data. It offers everything from free self-service queries to scheduled reports, database connections, white-label solutions, and embedded assistants.

What truly determines the quality of analysis are still the data, metrics, and governance of permissions. First, use the free version to test the two core data sources; thereafter, choose between Standard and Enterprise based on the needs related to connectors, collaboration, reporting, and integration.