Concepts
Entities
An Entity is any important "thing" we want to track. This could be a brand (Nike), a product (iPhone 16), a person (Satya Nadella), a publication (Runner's World), an idea (Carbon Plate Technology)
This is our master list of all the players on the map. We treat these as global, shared items, so there's only one "Nike" entity in our whole system.
Content
Content is a specific piece of customer or third party content (from cited sources)—blog post, YouTube video, landing page, press release, etc.
This is the link that connects customer actions to AI responses. By bringing content in, we create a powerful feedback loop that takes our platform from a passive monitoring tool and turns it into an active, strategic content creation and content optimization suite.
We continuously monitor, automate, and optimize customer content while directly answering questions like:
Source Attribution: "Is our blog post about 'Carbon Plate Technology' being used as a source by ChatGPT?"
Gap Analysis: "The AI thinks our competitors own the 'sustainability' narrative. Our platform shows we've never written a single article about it. That's our gap."
Narrative Alignment: "How well do the AI's perceptions of our brand match the key messages in our pillar content?"
Prompts
A Tracked Prompt is a specific question or topic that our customer strategically wants to monitor and win in AI engines. Examples: "Best running shoes 2025," "alternatives to Slack," or "is Red Bull healthy?"
Responses
An Response is a single, raw response from an AI engine like ChatGPT. We save the prompt we used ("Best running shoes?") and the exact answer the AI gave us.
This is our raw evidence, we never change it, it’s what the AI said at a specific moment in time.
Mentions
Our system reads through every Response and identifies every time an Entity is mentioned. Each one of these is a Mention record.
A Mention is where the magic starts. It’s not just that Nike was mentioned, but how. Was it a top recommendation? A citation in an article? A comparison to a competitor? Each Mention captures this specific context.
Observations
An Observation is the raw evidence of a connection between two Entities found within a Response. It's the most granular record of a relationship. While a Mention tells us "Nike was found here," an Observation tells us "We observed that Nike COMPETES_WITH Adidas in this specific sentence." We create a new Observation every time we find one of these connections. This immutable log is the ultimate source of truth from which the summary Relationship scores are calculated.
Relationships
A Relationship is the connection between two Entities. These connections are built from the evidence we find in the Mentions and Observations
This turns our list of nouns into a true map. We can now say Nike (Entity) COMPETES_WITH Adidas (Entity). Or Runner's World (Entity) VALIDATES the Nike Pegasus 41 (Entity). We score the strength of these relationships over time.
Tags
Tags are private labels our customers create to organize things in a way that makes sense to them (e.g., Q4 Holiday Campaign, High Priority).
This makes the platform flexible. It allows each customer to impose their own business logic and structure on top of our global map, without affecting any other customer.