Factget

About Factget

Deep Dive with Clara AI

Factget automates recurring data collection from external sources: websites, filings portals, registries, and long or scanned PDFs. Point it at a source and define the fields you need. Factget investigates the source once, then turns it into a fixed workflow that reruns on a schedule without a model in the loop, into your own schema. What you get is the whole harness, not just an extractor. Source investigation happens once. Deterministic extractors then rerun at no AI cost per run, across thousands of pages in bulk. Change detection watches both values and structure, and when a layout shifts Factget repairs the extractor automatically and logs the diff. Schema validation flags ambiguous rows rather than dropping or guessing them. OCR handles scans, and translation covers values or whole documents with structure preserved. Every value links back to the page it came from. Deployment is managed cloud, zero-retention, or inside your own VPC. There is no training on customer data, and a DPA is available on request. Typical uses: regulatory filings and corporate disclosures, sanctions list extraction and normalization, earnings data from 10-K/10-Q PDFs, pricing and rate monitoring across institutions, fund fact sheets (NAV, holdings, performance), and corporate registries and KYB sources. Note: Factget (factget.ai) is not FactSet.

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Pricing

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SW Score Breakdown The SW Score breakdown shows individual score for product features.Read more

Features The Feature Score % is calculated using the weighted average method, where core features hold more weight in the final calculation. Read more

100%
Reviews

60%
Momentum

60%
Popularity

60%

Platforms Supported

Browser Based (Cloud)

Organization Types Supported

Large Enterprises
Medium Business

API Support

Available

Modes of Support

Online

Factget Features

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Data Extraction Features

Features: The Feature Score % is calculated using the weighted average method, where core features hold more weight in the final calculation. Read more

100%

Data Validation

Flag missing or inconsistent values

ETL Pipeline

Transform and load into analytics and, BI tools

Data Normalization

Standardize formats (dates, currency, identifiers)

Document Parsing

Process DOCX, PDF, XLS, CSV, JSON, XML, etc

Unstructured Data Extraction

Pull data from text documents, PDFs, images, emails or databases

Export in Common Formats

Accepted file formats: TXT, DOCX, PDF, SRT, and VTT for captions.

Automated Scheduling

Helps to automate the scheduling processes to reduce paperwork, provide a comprehensive solution and ensure timely updates

Optical Character Recognition - OCR

Helps in converting scanned paper documents into editable files

Data Cleansing

Helps in verifying/correcting/modifying inaccurate or coarse data from database

Multi-language Support

Available in multiple languages to support global customers

Built-in Templates

It has bundle of predefined templates that can be used for creating a design

Cloud Storage

Provides an online storage space to store data

Factget Pricing

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Pricing Options

Premium Plans ( Subscription / Quotation Based )

Custom (Contact us) Custom

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Factget FAQs

What does Factget do?

Factget extracts structured data from websites, documents, PDFs, images and other difficult sources, then monitors those sources and keeps the data up to date. You describe the fields you want in plain language and Factget builds and maintains the extractor for you, so you don't write or babysit scraper code.

How is Factget different from a web scraper?

A scraper is code you write and then maintain every time a site changes. Factget investigates the source once, then runs deterministically at scale, so re-runs add no AI cost and stay predictable. It also detects when a source changes, validates results and repairs the extractor itself, which is the part that usually breaks in-house scrapers.

How do I get the data out of Factget?

Structured results can be delivered by API, webhook, scheduled file drops, or pushed directly into your database or warehouse. Scheduling and monitoring for recurring pulls are built in, so the dataset stays current without manual steps.

Which languages and source types are supported?

Factget works across 30+ languages, so non-English sources are handled the same way as English ones. Supported sources include websites, documents, PDFs and images, including pages that are awkward to parse or have no clean structured data behind them.

How is our data handled, and can Factget run in our own environment?

Factget can run managed in the cloud, in zero-retention mode, or entirely inside your own VPC. Customer material is never used as training data, and a DPA is available on request. Collection is limited to public, logged-out sources. Factget is not SOC 2 certified yet; Type I begins when a customer needs it.

Can I see Factget working before committing?

Yes. There is a live sanctions screening console you can try without a login at https://sanctions.factget.ai. Beyond that, Factget does not run a generic free trial: we run a live pilot on your own sources instead, so you judge it on the data you actually need rather than a sample.

What is Factget used for?

Factget is Data Extraction Software. Factget offers the following functionalities:

Data Validation
ETL Pipeline
Data Normalization
Document Parsing
Unstructured Data Extraction
Export in Common Formats
Automated Scheduling
Optical Character Recognition - OCR
Data Cleansing
Multi-language Support
Built-in Templates
Cloud Storage

Learn more about Factget features.

What are the top alternatives for Factget?

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Does Factget provide API?

Yes, Factget provides API.

Factget Contact

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