I Built an AI That Remembers What Competitors Did Months Ago

The author developed an AI tool called Competitive Memory, which is designed to remember competitor actions from months ago and use that historical data to understand current competitor activities. The project aimed to address the challenge of retaining historical context in competitive intelligence, as traditional summaries often miss important connections between past and present events.

The core idea behind Competitive Memory is that the AI retains relevant competitive information and recalls it later, enabling it to compare current events with historical data. For instance, if the system has seen a competitor change pricing in January, March, May, and July, asking the AI "Have we seen this before?" provides context for the July event.

A standout feature of Competitive Memory is "We've Seen This Before," which allows users to investigate if a new competitor event resembles previous ones, and compare how the situation unfolded in the past. This feature goes beyond simply describing the present, enabling users to trace connections between events and gain deeper insights.

Another key aspect of the project is the "Competitive Timeline," which presents events as a sequence rather than isolated occurrences. Sequences can reveal patterns and trends that individual events might not expose. For example, a sequence of enterprise-focused messaging, enterprise features, enterprise hiring, enterprise pricing, and enterprise partnerships could suggest a pattern of strategy shift.

The system also includes capabilities for detecting possible changes in competitor strategy and identifying the earliest signs of these changes. By analyzing historical data, Competitive Memory can help analysts uncover patterns and shifts that may not be immediately apparent from the latest announcements alone.