Find your needle
in a haystack of documents
Alphamoon is your AI assistant in improving the skip tracing process. Classify large document folders automatically and find data in a snap.
Search faster, process more cases
A large volume of documents coming in can be overwhelming. That’s also a source of costly errors, data management issues and frustration.
With AI’s assistance, you’ll find information faster, no matter the size of your document stack piling up.
The increased accuracy of identifying information fuels your processes with structured data. With Alphamoon, you’re on your way to seeing KPI charts go up and to the right.
Get started with document automation
Explore the state-of-the-art technology
The image-to-text technology works on various file types and languages. Trained on the hardest scans and outdated docs to tackle the toughest jobs.
The core feature of our technology is the powerful data extraction component – finds personal contact data across many types of documents.
A feature needed by every skip tracing agent – the automated document classification, with user supervision mode and editable tags.
Use Zapier or API integrations to create an end-to-end flow of information – from your documents to any business system.
Have questions about the product? Read the most common questions or ghead over to our complete FAQ.
Blank - do not use
How is skip tracing automated through IDP?
If you buy debt, the number of random documents can be excruciating to sort through. That’s where Alphamoon’s solution comes in handy. Skip tracing automation enables you to automate the workflow of documents in your liability management cases. Classification feature tags documents for easier navigation, while data extraction allows you to find far more means of contact with the potential client. For your ease of use, this pipeline can be integrated with your existing systems through API.
What is your pricing?
If you are interested in upgrading your skip tracing to the next level, talk to our sales. Use this form and we will get back to you ASAP.
How much time does it take to set up the platform?
The answer to this question is largely dependent on the complexity of your use case. Provide us with all the details about your use case to make sure we get back to you with the most accurate estimation.
Supported document files
Explore the world of IDP
At Alphamoon, everyone has room for growth. And it's not...
When your goal is to optimize business processes through automation for others, the last thing...
Alphamoon is developing an AI-based platform to automate document processing. It helps companies...
Stay on top of AI & ML news with Automated by Alphamoon
Recognizing the power of automated doc search
The purpose of automated search in documents is to quickly locate relevant information that would otherwise be time-consuming or impossible to find manually. It is a valuable tool for information management, data mining, e-discovery, legal research, customer service, competitive analysis, and other applications where large volumes of documents need to be searched for specific information.
Automated search in documents is often performed using search engines, indexing tools, and natural language processing (NLP) techniques. These tools can recognize and interpret various types of data such as text, images, audio, and video and extract useful information from them. The results of automated searches can be presented in various formats, such as lists, summaries, reports, and visualizations, depending on the needs of the user.
Automated search for a needle in a haystack
Searching for information in documents can take a lot of time for several reasons, including:
Volume: Documents can be very lengthy, and the amount of information contained within them can be overwhelming. It can take a long time to manually search through all the text, images, and other data in a document to find the specific information you need.
Complexity: Documents can contain complex and technical language that requires specialized knowledge to understand. This can make it difficult to accurately identify relevant information without spending a lot of time reading and analyzing the content.
Inconsistency: Documents can be created by different authors with varying styles and formats, making it challenging to find information that has been written in different ways.