Total Products under this Category: 338
Last updated: September 01, 2026
Why You Can Trust G2's Software Rankings:
G2's software rankings are built on verified user reviews, rigorous moderation, and a consistent research methodology maintained by a team of analysts and data experts. Each product is measured using the same transparent criteria, with no paid placement or vendor influence. While reviews reflect real user experiences, which can be subjective, they offer valuable insight into how software performs in the hands of professionals. Together, these inputs power the G2 Score, a standardized way to compare tools within every category.
Highlighted products: Apify, Oxylabs, Fivetran, Bright Data, NetNut.io, IPRoyal, Boomi Data Integration, and Decodo (formerly Smartproxy).
Underlying data: [Grid® JSON](https://www.g2.com/categories/data-extraction-tools/grids.json?focus%5B%5D=apify&focus%5B%5D=oxylabs&focus%5B%5D=fivetran&focus%5B%5D=bright-data&focus%5B%5D=netnut-io&focus%5B%5D=iproyal&focus%5B%5D=boomi-data-integration&focus%5B%5D=decodo-formerly-smartproxy)
Instantly extract business leads from Google Maps with Bolt Scraper. Get names, emails, phone numbers, addresses, and 50+ data fields. Our tool offers API modes, multi-keyword scraping, Telegram/email notifications, and auto-saving for unparalleled efficiency.
Browser automation for Selenium, Puppeteer, and Playwright in the Cloud: Headless browser service for data scraping with captcha solving and more!
Canopy API is an Amazon product data API that provides programmatic access to real-time information from Amazon.com. Developers and ecommerce teams use it to retrieve Amazon product details, pricing, customer reviews, sales estimates, stock and availability, and search result rankings without building or maintaining an Amazon scraper. Products can be queried by ASIN, product URL, GTIN/UPC, or search keyword. Responses are returned as structured JSON and include fields such as title, description, brand, images, current price, list price, deal badges, Buy Box information, star ratings, review text, sales rank, sales estimates, stock status, product variations, and category data. Canopy API is offered as an alternative to the Amazon Product Advertising API (PA-API) and Amazon SP-API, which require approval processes and have strict eligibility restrictions, as well as to self-managed Amazon scraping setups. Access methods: REST API for standard HTTP requests GraphQL API for field-specific queries MCP (Model Context Protocol) server for integration with AI clients such as Claude and Cursor AI Skills for use with large language models and AI agents Common applications: Amazon price monitoring and repricing Competitor and ASIN tracking Customer review collection and sentiment analysis Amazon keyword and search rank tracking Sales estimate and demand analysis Inventory and stock monitoring Price comparison and affiliate content MAP pricing and brand monitoring AI shopping assistants and ecommerce agents Product research workflows for Amazon sellers and agencies Canopy API offers a free Hobby tier, pay-as-you-go pricing with volume discounts, and a Premium plan for higher-volume usage. Documentation and open-source examples are available for both REST and GraphQL endpoints.
CazaLead is a Google Maps Scraper that extracts verified business emails, phone numbers, and contact data — built for sales teams.
Chisel AI's Data Extraction solution leverages advanced Machine Learning and Natural Language Understanding to rapidly process and extract data from unstructured digital insurance documents, such as policies, submissions, applications, binders, quotes, statements of value, and loss run reports. Designed specifically for the commercial insurance sector, it comprehends industry-specific terminology, enabling the automatic identification of key data points like broker and insurer names, addresses, coverage limits, premiums, deductibles, coverages, and exclusions. This automation significantly accelerates data processing, allowing underwriters and brokers to access critical information in seconds, compared to the traditional manual extraction process that could take up to 30 minutes for a fraction of the data. Key Features: - Advanced Machine Learning and Natural Language Understanding: Enables the system to read and interpret unstructured insurance documents with high accuracy. - Contextual Data Recognition: Understands the relationships between various data points within documents, ensuring accurate extraction. - Versatile Document Processing: Capable of extracting data from multiple formats, including emails, Word documents, Excel spreadsheets, and PDFs. - Standardized Data Mapping: Rapidly extracts data and maps it to ACORD standards or integrates with legacy systems. - Flexible Data Output: Provides extracted data in XML or JSON formats for seamless integration into existing workflows. Primary Value and Problem Solved: Chisel AI's Data Extraction solution addresses the inefficiencies and inaccuracies associated with manual data entry in the insurance industry. By automating the extraction process, it provides underwriters with immediate access to comprehensive data, enhancing risk assessment and pricing accuracy. Brokers benefit from expedited quote comparisons and policy checks, allowing them to dedicate more time to client relationships. Overall, the solution streamlines operations, reduces human error, and frees skilled professionals to focus on strategic tasks, thereby improving productivity and profitability within insurance organizations.
Cigati Email Address Extractor is an advanced utility built to extract email addresses from 90+ webmail accounts and email clients, including Gmail, Office 365, Yahoo Mail, Thunderbird, Apple Mail, and IMAP-supported platforms. The tool scans and collects email addresses from the To, From, CC, BCC, and Body fields with precision. Extracted data can be exported in CSV and TXT formats for easy use in marketing, contact management, audits, and lead generation. It supports both Single Mode and Batch Mode, allowing users to process multiple accounts simultaneously via a CSV credentials file. Key features include a date-range filter for targeted extraction, an advanced email filter to include or exclude specific addresses, duplicate email removal, and a preview panel to verify data before export. Folder hierarchy is preserved throughout the process, and users can skip previously extracted emails to avoid repetition. The tool features an intuitive, step-by-step interface suitable for both technical and non-technical users. Compatible with Windows and Mac operating systems. A free trial version is available, allowing extraction of the first 50 emails.
The world runs on data about people and organizations - but most of that data is wrong, old, or missing entirely by the time it reaches the systems that need it. Enrichment pipelines pull from caches that are weeks stale. Scrapers break silently when platforms update their structure. And stitching together signals from multiple sources means building and maintaining a normalization layer that never quite works. Clerix is the intelligence infrastructure layer built to fix that. We deliver real-time, structured data on entities - people, companies, networks - by extracting directly from the world's largest digital platforms. Not cached. Not crawled. Live, on demand, the moment your system needs it. The result is ground-truth telemetry your pipelines can actually trust. Every Clerix response is deterministic typed JSON - schema-stable ready to use without a transformation step. When platforms change their internal structure, we absorb it. Your integration stays intact. Your data quality stays consistent. Under the hood, Clerix fuses global OSINT signals with proprietary data streams and AI systems to achieve entity coverage that single-platform providers simply can't match. Whether you're resolving an identity across fragmented profiles, profiling an organization's digital footprint, or enriching a lead in real time before a sales call, Clerix returns the full picture - not a partial snapshot. We're built for enterprise teams where data quality is the product: AI pipeline engineers, sales intelligence platforms, digital risk and OSINT analysts, and agentic system builders who can't afford for enrichment to be the weak link. Our infrastructure runs at 99.99% uptime, monitored continuously, with a full observability stack. Clerix operates on custom enterprise contracts. We don't do self-serve - every deployment starts with an MNDA, a scoped quote, and defined success KPIs. It's a deliberate choice: the teams we work with have real requirements, and we'd rather get it right than ship fast and fix later. Real-time intelligence. Any platform. One API.
Automated, fast, and secure cloud browsers on demand.
Clura is an AI web scraper Chrome extension that extracts structured data from websites and exports it to Excel or CSV in minutes without coding.
Vahe Andonians founded Cognaize in 2020 to serve the financial industry by extracting actionable intelligence from unstructured documents enabling better decisions, new revenues and efficiency gains using Artificial Intelligence. Unstructured Documents are any written data that traditional software struggles to process. A financial institution is traditionally collecting, archiving and manually processing a huge number of such documents. For instance: Financial Reports, ESG Reports, Credit Agreements, Trustee Reports and Indentures of Structured Credit, Subscription Finance documents such as Borrowing Bases, Agreements such as ISDA or Credit Support Annexes. Actionable Intelligence is not just an extraction out of the document but an interpretation of the data using internal knowledge and definitions. For example: - What is the definition of Costs of Goods Sold? - Where do you put restricted cash? Under current assets or noncurrent assets? Each institution is answering those questions differently and this must be taken into account when processing documents. The value we deliver manifests in better decisions through consideration of more data points like deeper insights or entirely new data points. This is used by our clients to make better risk/reward decisions or to create new products. We are achieving this by combining traditional Deep Learning models for spatial understanding with cost efficient modern generative AI language models and knowledge graphs.
