Capalyze Complete Review: Features, Pros, and Cons

Every company, business professional, data analyst, or researcher who wants to deliver tangible results needs data. According to NewVantage Partners, 3 in 5 organizations are using data analytics to drive business innovation.

Often, the data used for this analysis is obtained from the web using web scraping platforms. However, most available platforms focus on scraping raw data that requires further analysis to get useful business insights.

Capalyze aims to address this issue by offering an Artificial Intelligence (AI) agent that takes natural language prompts and turns web data into business-ready spreadsheets. It also includes detailed reports and downloadable charts that can be shared with stakeholders.

In this review, we examine Capalyze's features, strengths, limitations, and competitors. By the end, you'll know if Capalyze can support your team in improving efficiency, enabling faster data-driven decision-making, and boosting financial performance.

How Capalyze Supports Data Collection using AI

Caption: Capalyze home page

Capalyze builds upon Univer, an open-source SDK for creating spreadsheets, and uses AI to enable real-time public data collection and analysis. It does so in three key steps:

Step 1: The user provides the target URL or enters just their data request in plain English, depending on the mode they choose.

Beginner Mode only accepts the target URL, while Expert Mode accepts detailed prompts, and Capalyze decides where to extract relevant data from. In the sample below, I used Beginner Mode to scrape content from the YouTube search results for iPhone 17.

Note that you will need to install the Capalyze Chrome extension before you can perform a scraping task.

Caption: Capalyze Beginner Mode

Caption: Capalyze web scraping agent

Choose whether the result should include analysis. For this sample, I focused on the scraping component of Capalyze.

Step 2: Capalyze crawls the web page that contains the requested data and suggests fields for the table. The user can confirm or adjust the fields based on their preferences, as shown below:

Caption: Suggested fields from Capalyze

I accepted the suggested fields and began extraction. As Capalyze goes to work, it provides a live preview of the data collection process, which you can stop and save at any time if you’ve gotten the amount of data you want.

Caption: Extracting data from Youtube search results

I stopped the extraction after 193 items.

Step 3: Capalyze returns precise data that matches the user's query and turns it into spreadsheets or charts for organization and visualization, respectively.

Caption: Structured dataset from Capalyze AI agent

Capalyze successfully provided a table containing 193 videos with 12 columns of information, including video titles, channels, view counts, upload dates, and other metadata, in approximately seven minutes. I asked the agent to create a chart on the verified channels and features using a bar chart.

The result:

Caption: Bar chart visualizing verified channels

I loved being able to switch between different chart types. This is the same data as a Sankey chart:

Caption: Sankey chart vizualizing verified channels

Capalyze also proactively generated a report on its key findings and business implications, without any specific request for this analysis. Here’s a snippet of the report:

Caption: Capalyze report snippet

To view the report and my full conversation with Capalyze's AI agent, use this link.

Other features of Capalyze include:

• Basic and premium AI models: Capalyze can automatically select the best model for a specific use case (basic), or users can choose advanced AI models (premium). The sample above used a Premium Model.
• Local file analysis: The agent allows teams to upload and analyze their local Excel and CSV files using AI models. If you need to, for example, understand the relationship between two columns in a file, you can use the Data Chat feature to converse with the agent.

Caption: Capalyze Data Chat feature

• Text analysis: Businesses can prompt Capalyze to perform sentiment analysis or provide suggestions on a dataset.
• Data enrichment: Capalyze can enhance datasets (for example, adding a new column) of up to 30.000 rows, depending on your subscription plan.
• Editable Excel files: Teams can edit their extracted datasets within the Capalyze platform before downloading them to their local storage.

Businesses can use Capalyze to extract competitor information, product reviews, market trends, and social media analytics to understand customer behavior, refine marketing strategies, and anticipate market changes.

Strengths and Limitations of Capalyze

Below are some areas where Capalyze shines and where it might fall short:
Strengths:

• Abstracts extensive coding and manual data processing by outsourcing the work to its AI engine
• Accepts natural language prompts, so teams don’t need to write complex Excel formulas or fragile scripts that break frequently when used on dynamic sites
• Extracts data from high-traffic sites like Amazon, social platforms like LinkedIn and TikTok, and Google products like Google Maps and Play Store
• Turns data into spreadsheets so businesses and researchers can quickly inspect the records or export them for further analysis
• Visualizes data as charts to identify trends and communicate insights to stakeholders, with support for 19 chart types
• Can generate a detailed report to accompany the chart
• Supports batch scraping from multiple URLs
• Provides a Chrome extension for easy plug-in to your desktop and browser fingerprinting

Limitations:

• Capalyze does not provide detailed documentation on its product, so users who have questions may need to reach out via email or Discord.
• Users can only use the batch scraping feature for tables that include columns with links.
• The download and full-screen feature while viewing reports is still in development.

Despite these limitations, Capalyze simplifies data collection for businesses and enterprises through a no-code conversational workflow that returns visual and organized table summaries of web data. Let’s take a look at some competing tools and how they differ from Capalyze.

How Capalyze Compares to Other No-code Data Collection Platforms

ParseHub, Octoparse, Webscraper.io, and Browse AI are some popular no-code/low-code parsing and scraping options available in the market. The following table compares the strengths and challenges of each tool, along with the data needs they best serve.

Tool/Platform	Strengths	Weaknesses	Most Suitable For
ParseHub	- Provides cloud-based data collection and storage - Includes features like IP rotation, scheduled collection, and API integration	First-time users might experience an initial learning curve before becoming proficient	Extracting data directly into cloud storage like Amazon S3 or Dropbox
Octoparse	- Auto-generates selectors and builds workflow for scraping web pages in a point-and-click interface - Provides pre-built templates for popular sites like Amazon and eBay	More complex scraping jobs like pagination and infinite scrolling will require the user to manually adjust the workflow	Overcoming web scraping challenges like CAPTCHA solving, JavaScript rendering, and infinite scrolling
Webscraper.io	Free and configurable Chrome extension for scraping websites	Since users need to create a sitemap to extract data, it requires understanding of page structure and parent/child relationships	Simple web scraping tasks as it might break when extracting data from high-traffic or dynamic sites
Browse AI	- Enables bulk data extraction using “robots” that learn defined actions - Provides built-in scheduling feature for periodic scraping jobs	The robots might break when site layout changes or while performing more complex extraction like crawling each subpage of a domain	Real-time monitoring of web page changes and scraping data for large language models (LLMs)

Capalyze stands out by going beyond providing singular solutions for generating parsing scripts or training personalized scrapers. Rather, it abstracts the entire technicalities of the web data collection process and transforms raw data into actionable information, allowing businesses and analysts to understand the data at a glance. It also reduces the need for extensive downstream analysis by providing structured datasets and generating reports upfront.

Conclusion

If you need a no-code data analytics tool to reduce time-to-insight, Capalyze provides an AI agent that crawls web pages and returns structured data, detailed reports, and informative charts. For businesses seeking to improve operational efficiency, customer engagement, and market strategy, begin with Capalyze's free trial and experiment with its features to determine if they align with your team's needs.

Sign up to start using Capalyze.