Introduction
Every company in the world works with information, however unstructured. But, the most successful companies convert unstructured information into structured data and then utilise data driven decision making to progress.
We live in an age of Artificial Intelligence and there is a plethora of AI-based data extraction tools available in the market. In this article, we will take a look at what data extraction actually is, how it works and list down the top 10 best AI data extraction tools in the market. (Stay tuned till the end to see how you can pick the best data extraction tool for your business! 😉)
What is data extraction?
Data extraction is simply the process of retrieving data from any unstructured source into a structured format for further analysis.
Structured data follows a pattern that makes sense to a user. It can be exported to a database and subjected to analysis.
Why do we do it? Majorly, to get raw structured data that can be transformed into insights to drive business decisions. Take an example, you have an inbox full of PDF files with potential customer contacts that you want to reach out to, to simply sell your product or service. Do you manually copy and paste every email address? That can be tedious and time-consuming. Enter AI data extraction tools, which can extract data and enter it directly into your CRM to simplify mailing lists.
What are data extraction tools?
A data extraction tool is a software designed to extract specific data points from various sources, such as documents, databases, and websites. This type of software utilises advanced AI algorithms, coupled with Optical Character Recognition (OCR) and Natural Language Processing (NLP) to automate the extraction process, aiming for high accuracy and lower turnaround time. Latest advancements, including the use of Large Language Models (LLMs), have enabled AI data extraction tools to not require any training at all. These models are called Zero-Training models.
An AI-powered document processing platform (IDP) can categorise documents, identify relevant information based on document type, and even summarize content. It can then cross-reference this data with other documents, route it for approvals to different teams as well as export to any desired software. Additionally, AI-driven data extraction tools can identify inconsistencies and flag complex cases for human review.
Types of Data Extraction Tools
There is a wide variety of data extraction tools, each tailored to meet a specific set of requirements. They use diverse techniques such as PDF scraping, database querying, document parsing, optical character recognition (OCR), natural language processing (NLP), and artificial intelligence (AI) to accomplish data extraction. These tools are designed to effectively extract and transform data from various sources. Here are some common types:
- Web Scraping Tools:Web scraping tools retrieve data from websites by simulating human browsing behavior. They interact with web pages to extract text, images, links, tables, and other structured data from HTML or XML formats.
- Database Extraction Tools:These tools extract data directly from databases by connecting to the database management system (DBMS). They form the first step in Extract Transform Load (ETL) processes. They execute queries or use connectors tailored for SQL-based databases (e.g., MySQL, PostgreSQL) or NoSQL databases (e.g., MongoDB, Cassandra).
- Document Extraction Tools:Document data extraction tools extract information from files such as PDFs, Word documents, and Excel spreadsheets. They utilize OCR to convert scanned or image-based content into machine-readable text for further processing and analysis.
- Text Extraction Tools:Text extraction tools focus on extracting data from unstructured text sources like emails, chat logs, social media posts, and news articles. They employ NLP, text mining, and machine learning algorithms to extract specific information and perform tasks such as sentiment analysis.
These tools play a crucial role across various domains. For instance, in market research, sentiment analysis derived from text extraction tools helps companies understand customer feedback, guiding strategic decisions and facilitating product improvements.
Why do companies need Data Extraction?
It is often said that data represents the new oil in this digital age, fuelling processes for decision-making that enhance customer experience and maintain competitive advantages. Businesses, irrespective of size and industry, need this data extraction to thrive in an increasingly data-dominated world. Here are some facts on why data extraction is critical for businesses:
- Data Accuracy: It is important that the extracted data be accurate in order to minimise risk stemming from incorrect analyses. AI data extraction tools solve this problem.
- Real-time analytics: Real-time insight into data gives the user a competitive advantage, which is possible with accurate data that’s easily available.
- Improved customer experience: Data extraction helps personalize pivotal operations, like, marketing, sales and customer service and enhance the quality of product to yield greater customer satisfaction.
- Exponential Operational Efficiency: Less manual, error-prone effort means less cost associated with processes both in terms of time and money.
- Ease of Compliance: Successful data extraction helps the industry comply with its regulations and avoid all legal hassles that might occur from lack of compliance.
- Improved Data Quality: Automated extraction helps maintain accurate, consistent data that results in reliable insights.
- Scalability: Data extraction tools handle increasing volumes of data as businesses grow.
Businesses deal with data from customers, sales, social media, product feedback, and more. The data extraction software market growth rate provides insight into how data extraction software plays a crucial role in data management at companies.
Top 10 Data Extraction Tools in 2024
#1. Nanonets
Nanonets is an AI-driven data extraction software that helps businesses automate document processing and eliminate manual tasks through no-code workflows. It excels at extracting data from a variety of sources, including PDFs, documents, images, emails, scanned documents, and unstructured datasets with over 95% accuracy. The platform significantly reduces expenses by up to 50% and speeds up document processing times by 90%. Moreover, Nanonets can automate entire workflows from start to finish, streamlining operations comprehensively.
Pricing: SME-friendly pricing plans starting at USD 0.3/page with no monthly commitment. Contact our team to get the best price for your use case.
Pros:
- Easy to use
- 97%+ Accurate
- Excellent support team
- Fast information recognition
- Ability to intake large volumes of documents
- Reasonable pricing - Check Pricing
- 200+ languages supported
- 24x7 customer support
- Free Plans + Cost-effective Pricing Plans
- Personal training sessions
- In-built powerful OCR software
- Cloud and On-premise hosting
- White label options
#2. Airbyte
Airbyte is a data migration platform that offers 300+ pre-built connectors for smooth transition of data, from unstructured formats to structured data warehouses, databases and data lakes. It is less of a data extraction tool but stands out as a data migration tool. You can customize a connector to migrate your data from one place to another in minutes.
Pricing: Open-Source platform, with free deployments. Pricing for basic versions starts at $350 / month
Pros:
- Data Migration in minutes
- Open-Source Deployment
- User-friendly APIs
Cons:
- Inability to extract data from scanned documents
- No workflow automation features
- Expensive support plans
#3. Hevo
Hevo is a data extraction tool that helps you connect various sources to facilitate data flow and build a zero-maintenance data pipeline. It’s used to capture and process all the data on any website, supports over 50 file formats, and can scrape data from web pages or audio files.
The tool has an easy-to-use, no-code interface and primarily targets data teams within organizations. It offers free-trial plans.
Pricing: Forever free plans. Paid Plans start from $299/month.
Pros:
- Can manage a large number of pipelines
- Automatic detection of data sources
- Easy Integrations
Cons:
- Costlier pricing plans for more data sources
- Limitations for complex use cases [Source]
#4 Super.ai
Super.ai is an advanced Intelligent Document Processing (IDP) platform that leverages artificial intelligence to automate and enhance document management. Super.ai can extract, classify, and analyze data from diverse and complex document types with high accuracy. Its intuitive interface allows users to customize workflows and integrate seamlessly with existing systems, thereby streamlining document-heavy processes. The platform's scalability ensures it can cater to both small businesses and large enterprises, adapting to their evolving needs.
Pricing: Custom Pricing Plans
Pros:
- High Accuracy, utilises advanced AI to ensure precise data extraction and analysis.
- Offers flexible workflows and integration options.
- Suitable for both small businesses and large enterprises.
- AI-driven learning enhances performance over time.
Cons:
- Can be expensive, particularly for smaller businesses or startups.
- Initial setup and integration might be complex and require significant time and effort.
#5. Rossum
Rossum leverages Optical Character Recognition (OCR) technology to automate the extraction and processing of data from various types of documents. It uses AI-driven technology to handle invoices, receipts, and other business documents, enhancing efficiency and accuracy in data entry and management.
Pricing: Custom Pricing Plans
Pros:
- Flexible configurations for various document types
- Easy Integration capability
Cons:
- Can be relatively expensive, particularly for small to mid-sized businesses.
- Initial setup and configuration might be time-consuming and require some technical effort.
- Limited Out-of-the-Box Features
#6 Improvado
Improvado offers a wide range of tools to extract, analyze, clean, transform, and visualise data. Its platform for revenue data gives companies a real-time look at how well their sales and marketing efforts are paying off. This feature helps businesses make smart choices based on the latest performance data.
Pricing: Available on request
Pros:
- Streamlines data from 300+ data sources
- Full-cycle support
- Thorough data collection
Cons:
- Data Transformation functionality can be improved
- Limited customisations
- Dashboard UI is confusing
- Complex procedures require help from the support team
#7. Matillion
Matillion serves as a tool for data extraction that users can operate on their own.
This data extraction platform boasts a user-friendly interface eliminating the need for IT expertise or advanced programming skills. The platform's design allows for adaptability ensuring its features can expand to meet your changing requirements over time.
Pricing: $2/credit
Pros:
- Easy to use, intuitive UI
- Easy to monitor
- Data integration and transformation
- Easy to set up
Cons:
- Expensive
- Hard limit on the hardware
- No user community site
- Role-based access is absent
- No backup option
- Pricing is high
- Support is slower
#8. Octoparse
Octoparse is an easy-to-use web scraping tool. You simply insert the URL into the web crawler and the data gets extracted automatically, in a structured manner. The relative ease-of-use that Octoparse offers is unparalleled.
You can scrape all types of websites and generate structured tables of data with Octoparse’s cloud-based web crawler. You can schedule and run automated tasks 24/7 with Octoparse’s drag and drop workflows. It pulls text, links, image URLs, and more from across the web.
Pricing: Free plan for 10 web-crawlers. Plans start at $75/month.
Pros:
- Beginner-friendly UI to scrape websites
- No-Code Environment
- Handles complex websites effectively
- Offers scheduling and automation options for regular data extraction tasks
Cons:
- Mastering advanced features require time and practice
- Experiences slowdowns with large-scale data scraping
- High-tier pricing plans are expensive
- API capabilities are limited
#9. Mindee
Mindee offers an enterprise-grade OCR API with an average processing time of 1.2 s per page and 99.99% uptime. It ensures that your documents and images get processed smoothly and accurately, so you can focus on building your product while Mindee takes care of back-end data extraction processes.
Pricing: Offers Free-Forever pricing plans for developers. Basic volume-based pricing plans starting from $ 0.1/page.
Pros:
- High Accuracy
- User-Friendly Interface
- Enterprise-grade API
- Fast, with ~1.2s average processing time per page
- ~99.99% uptime
Cons:
- Custom plans can be expensive
- Limited flexibility for specific workflows
#10. Stitch
Stitch is a streamlined, fully-managed ETL solution designed for effortless data extraction from more than 130 sources. Although it may not offer advanced transformation capabilities, its strength lies in its ease of use and accessibility, making it particularly well-suited for small to mid-sized businesses. Equipped with strong security protocols, including SOC 2 and HIPAA compliance, Stitch maintains data integrity throughout the extraction process.
Pricing: Standard Pricing starts at $ 1000 / year with a 2-month free trial period
Pros:
- User-friendly interface makes setup and operation straightforward.
- Supports data extraction from over 130 different sources.
- Adheres to robust security standards, including SOC 2 and HIPAA compliance.
- Fully managed solution reduces the need for in-house maintenance.
Cons:
- Lacks advanced data transformation capabilities.
- May not be ideal for very large or complex data environments.
- Offers fewer customisation options compared to some more advanced ETL tools.
How to Select the Right Data Extraction Solution?
There are several factors you should consider when selecting a data extraction tool. Here are some of the most important to keep in mind:
Define Requirements
Sources: Where does the data come from?
Data Format: What types of data formats are needed?
Volume & Frequency: Define how much data and how often it’s needed.
User-Friendly Interface:
Friendly Design: Look for easy-to-navigate design
Short Learning Curve: Ensure quick adoption across the team
Integration Capabilities
Compatibility: Make sure it will work with other systems in place & with other applications, such as document management systems or ERP systems, for automated notifications about metadata and file structure changes.
APIs: Does it have APIs and connectors?
Configurability in Customisation and Flexibility
Configurability: Choose a tool that allows customisation to meet your specific needs.
Scalability: Can scale with the requirement of data as your business grows.
Validation of Data Quality and Accuracy
Cleansing: In-built inherent cleansing feature.
Accuracy: Ensures error handling.
Automation and Scheduling
Automation: Supports automated extraction.
Scheduling: Run jobs at scheduled intervals.
Security and Compliance
Security: Ensuring the confidentiality of sensitive information.
Compliance: Complying with regulatory standards.
Cost
Pricing Model: Understand the pricing structure (subscription, one-time payment, usage-based).
Total Cost of Ownership: Consider all costs, including licensing, implementation, and maintenance.
Conclusion
Data extraction is transforming semi- or unstructured data into structured data. To put it another way, this process transforms semi- or unstructured data into structured data.
Data extraction has become crucial due to the dramatic rise in unstructured and semi-structured data. However, the data extraction procedure makes your job precise, improves your chances of making sales, and makes you more agile.
You must use the best data extraction software according to your needs to realize the full potential of data at your company. We hope our blog helps you make the decision.
Rated 4.9 on Capterra and G2. Try Nanonets today. Start your free trial without any credit card details.
Recommended Reading:
