In broadcast media monitoring, not every mention is a meaningful mention.
For Signal AI, an AI-powered reputation management and enterprise risk intelligence platform, television advertising had long created a challenge inside broadcast monitoring workflows. Keyword-based monitoring could surface relevant editorial coverage, but it could also capture unrelated 30-second advertisements — creating false positives, cluttered feeds, and extra manual work for analysts.
As one of TVEyes’ premier global distribution partners, Signal AI provides broadcast and podcast monitoring to platform clients across the U.S., Canada, and the U.K. But without a reliable way to distinguish ads from editorial content, teams were forced to rely on known string matching, custom filtering rules, and ongoing manual tuning.
TVEyes helped solve this challenge with its Ad Aware API, designed to automatically identify and flag advertising content within broadcast streams. The integration took approximately three days of development and allowed Signal AI to reduce manual overhead while improving the clarity and accuracy of its monitoring feeds.
Today, Signal AI filters approximately 120,000 ad documents daily, helping remove irrelevant content at scale and giving clients a cleaner view of the true media landscape.
The result: broadcast monitoring with less noise, less manual cleanup, and stronger editorial signal.
Read the full case study to learn how TVEyes helped Signal AI improve broadcast monitoring clarity at scale.
