At four in the morning, the news has a particular personality. It is both too much and not enough. There are thousands of fresh stories, posts and clips, but perhaps six that a pharmaceutical executive really needs before breakfast. For one team at the global agency FINN Partners, finding those six meant a relay through offices in Israel, Britain and New York. The New Yorkers sometimes began at 4 a.m. The machinery worked. The people were getting tired.
This is the small, severe problem Fullintel was built to solve. The Cambridge-area company monitors online news, print, television, radio, podcasts and social media, then turns that torrent into daily briefs, dashboards, analysis and urgent alerts. Its customers are communications departments, PR agencies, public-affairs teams and government offices. They do not merely want to know where a name appeared. They need to know whether the mention matters, whether the tone is changing and whether somebody should wake the general counsel.
The obvious answer has long been software. Search everything, match the keywords, rank the results. Yet that answer created a second problem: the software returned so much junk that operating it became a job of its own. A company with a common name might get pages of unrelated hits. Paywalls hid important stories. Sarcasm confused sentiment scores. Fullintel’s founders, Gaugarin Oliver and Andrew Koeck, had seen this movie before. Each had already built a media-monitoring company and exited - Oliver’s MyMediaInfo to Thomson Reuters, Koeck’s dna13 to PR Newswire. In 2015 they started again, this time with an unfashionable idea. The machine needed readers.
The first thing that failed was relevance
Fullintel’s first product was not a futuristic chatbot. It was an executive news brief, launched for Canadian clients in 2015 and delivered early enough to shape the day. Media analysis followed in 2016. A production team opened in Nagercoil, India, staffed in part by veterans of Thomson Reuters and Nasdaq. The geography mattered: a team working ahead of North American clocks could read, sort and prepare while clients slept.
The company expanded to U.S. clients, then Britain and Australia. In 2018 it added competitive analysis and a 24-hour crisis service; headcount reached 100. The progression tells you what customers changed their minds about. They had bought automation for efficiency. They came back to human service because their actual bottleneck was confidence. A result that might be wrong is not a shortcut when the recipient is the CEO.
“There are certain things that require a level of nuance, or the understanding of what clients want to see and don’t want to see.”Jessica Lise · Partner, FINN Partners
The workflow is simple enough to sketch. Software captures and de-duplicates coverage. Models classify subjects, estimate sentiment and surface unusual movement. Analysts correct the search, remove false positives and attach the client’s context. The result becomes a dashboard, an alert, a custom report or a polished morning email. Fullintel calls the platform Hub. Its measurements include share of voice, key-message pull-through, prominence and a proprietary Media Impact Score that weighs the quality of a mention rather than treating every clip as equal.
Software with a newsroom attached
This puts Fullintel in an odd but useful part of the market. Cision, Meltwater, Onclusive, Muck Rack, Signal AI and Agility PR Solutions all compete for some of the same budget. A lightweight self-serve tool can be entirely sensible for a small brand tracking a few distinctive terms. Fullintel is aimed at the harder cases: many markets, regulated language, senior readers, a live reputation risk or a reporting framework complicated enough that “mentions went up” is not an insight.
Its newer AI products extend that logic. PredictiveAI scores stories for their likelihood of gaining momentum. MATT AI - short for Media Analysis, Trends & Tracking - lets a communications professional ask questions about coverage, themes, spokesperson performance or competitors. The interesting part is not the chat box. It is the claimed training ground: years of analyst-curated, client-specific media data. Human judgment becomes the material used to make the machine less generic.
The business model follows from the labor. Fullintel sells enterprise software wrapped in managed service: access to data and dashboards, plus people who tune searches, read coverage, build reports and answer at inconvenient hours. Commercial contracts are quoted privately. A public federal schedule from 2023 provides a rare window into the order of magnitude.
Annual range listed for weekday analyst-curated daily news reports. Government schedule rates were marked subject to change.
Those prices clarify the proposition. This is not a five-minute signup for someone curious about a hashtag. It competes with internal headcount, agency hours and the financial cost of missing something consequential. In FINN Partners’ case, Fullintel took on the heavy production work for a daily pharmaceutical brief distributed to roughly 1,600 people at 7:30 a.m. The agency reported spending about half as much internal time and saving more than 50 percent in cost. What changed its mind was not a feature checklist. It was the sustainability of making skilled employees wake before dawn to format the news.
The useful lesson is smaller than the platform
A communications team can copy Fullintel’s logic without buying Fullintel. Begin by separating collection from judgment. Let automation gather, deduplicate and label; make a named person responsible for relevance. Create a written definition of “important” for each executive audience. Review false positives weekly, not when somebody finally complains. Measure fewer things, but connect them to an actual goal - message adoption, audience influence, reputation movement or response time.
The approach has conditions. Human review adds cost and can add latency. It works when missed context is expensive, the audience is senior, the subject is messy or the coverage spans enough markets to overwhelm an internal team. It is harder to justify when the search is narrow, the stakes are low, the user enjoys working directly in a dashboard or the budget cannot support a managed service. Prediction also deserves caution: a score can focus attention, but it cannot promise that a story will travel. The newsroom remains an unruly organism.
Copy this
Use automation for collection and repetition. Assign humans to ambiguity, exceptions and the final call on what reaches leadership.
Skip this when
Your topic is simple, false positives are cheap and a small team can review the entire feed without sacrificing higher-value work.
Fullintel’s validation has arrived in the language its industry respects. It won seven AMEC communication-effectiveness awards in 2024 and a PRSA Anvil in 2025 for an AI-automation resource. Yet awards are not the most revealing proof. The better evidence is that its original promise has survived every fashionable technology cycle: a brief that arrives on time, contains what matters and does not force the reader to do the monitoring all over again.
There is a quiet joke in this. The media-intelligence industry spent years selling more information as the product. Fullintel sells the subtraction. It gathers everything so that a busy person can receive almost nothing - six useful items before breakfast, perhaps, and the confidence to ignore the rest.