Who we are

eGrabber is the leader in solutions for building custom B2B prospecting lists in-house.

eGrabber Overview

eGrabber is the leader in solutions to build custom B2B prospecting lists in-house.

We make tools that enable users to build B2B prospecting lists faster & more accurately than SDR Experts do.

Our tools are faster & more accurate because we automated 50+ List Building work-flows commonly performed by SDR Experts, by developing proprietary parsing & web-research algorithms and integrating best-in-class technologies.

The lists we build are uniquely high-converting to each customer because we leverage intelligence from customer’s in-house databases (past relationships - prospects, customers, users), their professional networks & web sources to build lists.

US Patents

Methods and systems for determining Business email addresses with name & company

Method and system to enable searching for lead & contact information on the web

Detecting near duplicate records like humans do (Bob/Robert ; HP/Hewlett Packard; ..)

Process of dynamically loading driver interface modules for exchanging data between disparate data hosts

Automatic transfer of address/schedule/program data between disparate data hosts

Methods and systems for determining Business email addresses with name & company

us 8,495,151

Abstract

Disclosed herein is a method and system for a user to find an email address using the Internet. The user inputs the information that he wants to be verified or completed. A seeking unit determines the missing fields in the input information. The seeking unit may determine the missing information in the email address from various sources on the Internet, using a set of rules. The rules may be specified by the user or present in the database. The obtained search results are ranked by a ranking unit, based on the relevance of the scores. The seeking unit may also display the found email information along with the ranks to the user. The user has the option to sort the email information. The user may then select the most accurate email information, according to him, which is then used to populate the field in the information.

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Method and system to enable searching for lead & contact information on the web

us 7,822,732

Abstract

A method and a computer system to enable domain specific search is disclosed. The present invention enables creation and sharing of domain specific search scripts, where search intelligence relating to domain and search engines is encapsulated in a parameterized domain specific search script. The system provides a customizable knowledge base to be used to configure the parameters specific to a chosen domain. Users can parameterized search scripts and configure search scripts according to their search needs. Users can use search scripts to perform complex domain specific searches by specifying input search string and without having to worry about refining results. The system uses the parameterized search scripts and configuration information along with user input search string to build search engine independent and search engine dependent queries from one or more search engines to provide relevant results to user.

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Detecting near duplicate records like humans do (Bob/Robert ; HP/Hewlett Packard; ..)

us 8,838,549

Abstract

A method for finding duplicates by matching group of fields in records is disclosed. The method comprises standardizing data using field specific knowledge base; extracting at least part of one or more related fields of records; applying a matching attribute function to generate keys on the "comparable" field part extracted data; generating record level keys using generated field level keys; clustering the records based on generated record level keys; identifying reference record for each cluster identified; and calculating matching percentage for each record in a cluster with respect to reference record of the cluster. Devices and systems are disclosed that enable the method for finding duplicates.

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Process of dynamically loading driver interface modules for exchanging data between disparate data hosts

us 6,711,624

Abstract

A data exchange process is implemented by a computer system coupled for communication with a remote index server via a network. The process provides for transfer of a data block from a source host having an internal source data format, to a destination host having an internal destination data format different from the source data format. The process includes the steps of: determining characteristics of the source data format by comparing the source data format to sets of data format characteristics stored in a memory storage space of the computer system to determine if a predetermined relationship exists between the characteristics of the source data format and a particular one of the sets, and if so, a source driver associated with the particular set is accessed from memory of the computer system, the source driver being capable of extracting a data block from the source host and converting the format of the data block to an intermediate data format. If no predetermined relationship exists, the process samples data from the source host, and transmits the sampled data to the index server which compares the sampled data to remote sets of data format characteristics stored in a memory of the index server to determine if a predetermined relationship exists. If a predetermined relationship exists, the server accesses an appropriate source driver, and transmits it to the client computer system.

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Automatic transfer of address/schedule/program data between disparate data hosts

us 6,339,795

Abstract

A data exchange process for transferring data representing a geographical address from a source host using a source data format to a destination host using a destination data format including the steps of: using a first driver to extract a data block from the source host and to convert the format of the data block from the source data format to an intermediate data format; and temporarily storing the data block in an intermediate memory storage location; determining if the data block includes plain text data which is not parsed and identified by corresponding tags. If the data block includes plain text data which is not parsed and identified by corresponding tags, the process provides for automatically parsing the data block into a plurality of data portions having corresponding tags associated therewith, each of the tags indicating a type of information represented by the corresponding data portion. A second driver is used to convert the format of the data block from the intermediate data format to the destination data format, and to insert the data block into the destination host. The step of automatically parsing the data block into a plurality of data portions includes the steps of: identifying a plurality of text strings of the plain text data; and comparing the text strings to a plurality of predefined patterns to determine pattern matches between the text strings and the predefined patterns.

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