IntelEdge™ Technology for Competitive Business Intelligence

Gathering competitive business intelligence forms an integral part of our services. Winning campaigns require sound preparation, decision-making, and operations based on timely and actionable intelligence. We provide clients with situational awareness and foresight, enabling informed decisions to seize opportunities.

Our IntelEdge™ technology combines our subject matter expertise, our unique, open source intelligence-gathering experience, and leading edge techniques to deliver high-stakes critical insights. 

Advanced search and analysis tools enhance collection and analysis of open source information, to uncover the necessary intelligence.

How Does it Compare?

IntelEdge™ Research Capabilities vs. Traditional Research

Traditional web searches – limited to 32 words or phrases in one language; find only what’s on Web 2.0 (current platforms); search for an image or video can only be done by name of person or object depicted.

 IE Keyword Signatures™ (KWS) dramatically surpass traditional search tools by querying, filtering, and targeting upwards of 10,000 keywords in up to 40 languages in a single search of open web, deep web, dark web, social media platforms (both Web 1.0 and 2.0) and news sources in over 180 countries.


 Visual Signatures™ (VS) leverage IE’s internal neural network to analyze and authenticate still and motion visual imagery. VS support a wide variety of image types and content, from people, weapons, vehicles, satellite imagery, graffiti, and medical imagery.

 Polling – expensive; skewed by universe of those willing to respond by phone or internet; efficacy affected by writing of questions; subject to manipulation by those who intentionally offer misleading responses; targeting of geographic or demographic groups relies on self-identify of respondents.

 IE Chatter Collection and Analysis Platform™ (CAP) allows us to overlay analytic criteria to unfiltered chatter in order to describe in a structured manner clusters of activity that point to indicators and warnings (I&W) of impending events. We use Natural Language processing to extract entities from big data sets, permitting the discovery of new insights, at a fraction of the cost of polling.


 Hyper-local Targeting (HLT) sharpens a geographic search by including local names of metropolitan areas, such as townships, villages, hamlets, county names, etc. When analysts research a geographic region, those with the most local knowledge have an advantage over those lacking it. A search for a metro area might actually query hundreds of different local place names, thereby improving the results to the analyst.


 Hyper-local Demographics™ (HLD) leverages Hyper-local Targeting and layers up to 400 variables of neighborhood-level demographic datasets, including age, race, gender, occupation, income and education data. This delivers uncommon insight of chatter and sentiment for micro-targeted research for pinpoint understanding your critical issues and micro-targeted messaging.