Yes – and several do. Private equity firms, holding companies, family offices, and investor relations teams use AIQ to track AI narratives across an entire portfolio from a single account, with each portfolio company set up as its own topic with its own prompts, peers, and tags. The use case is straightforward: a portfolio of fifteen or twenty companies generates more AI mentions in a week than any analyst can manually monitor across eight engines, and the early-warning value of catching a shift inside one portfolio company before it shows up in the press is high enough to justify the platform on its own.

IMPACT™ runs continuous Google queries against defined keyword sets for each client, executed from the correct geographic and language context for each one. Every ranking URL is classified along several dimensions: ownership (client-owned, earned, third-party, hostile), SERP feature (organic, AI Overview, People Also Ask, image, video, news, knowledge panel), and topic. Movement, share-of-voice, and competitive position are tracked over time, so a one-position drop on a critical keyword last Tuesday is visible alongside the broader trend over the prior twelve months. Account teams use this data daily to spot threats, prioritize interventions, and produce the monthly client reporting that demonstrates progress against the program’s stated goals.

Generic monitoring tools – the Google Alert variety, basic mention trackers – can flag that a Wikipedia page changed, but the value is in the detail and the speed. WikiAlerts™ ingests Wikipedia’s live edit stream rather than polling on a schedule, so the alert hits within minutes of an edit. The email contains the full diff, so a comms team can see exactly which sentence was changed and by which account, not just that the page was touched. The one-click revert button rolls back clear vandalism through the same mechanism a Wikipedia editor would use. For corporate pages, executive biographies, and any article where small wording changes have outsize narrative consequences, that combination – speed, detail, ability to act – is the difference between knowing and being able to respond.

Yes – this is one of the highest-value use cases. A new topic can be configured in under five minutes, and the first round of AI responses comes back within 15-20 minutes. During an active situation, a comms team can stand up topics for the specific narrative threads they are tracking (a contested claim, an emerging frame, an executive name appearing in stories), watch daily as the AI engines absorb or reject each narrative, and identify which sources are driving the picture. Once the situation stabilizes, topics can be paused or removed and the subscription scaled back. We use this internally on every crisis engagement we run.

A pure technology vendor sells data dashboards and leaves the interpretation and action to the client. A pure services firm runs on intuition and quarterly audits. Five Blocks is built around the integration of the two. IMPACT and AIQ generate the diagnostic data continuously – every ranking shift, every AI source change, every Wikipedia edit – and the senior account team interprets it, builds the strategy, and executes the actual interventions: the Wikipedia edit requests, the structured data deployment, the source-layer content work, the coordination with the client’s PR firm. The data without the execution is just a dashboard. The execution without the data is just guesswork. The integration is what produces results that survive contact with the engines.

AI engines do not preserve a queryable history of what they said yesterday, so neither does AIQ. The platform begins collecting data the moment a topic is created. This is one of the practical reasons we recommend setting up topics for a brand and its key executives before a crisis arrives rather than after, and one of the reasons we set up exploratory topics for clients during onboarding even before strategy is finalized – the baseline data starts accumulating immediately.

The competitive edge is in the diagnostic depth. Off-the-shelf SEO platforms sample a few keywords a few times a week and report aggregate rankings. IMPACT™ tracks every URL on every result page for every defined keyword across 500 cities, 69 countries, and 23 languages, at daily cadence. Off-the-shelf AI tools measure visibility on one or two engines. AIQ™ tracks the full response, source attribution, and sentiment across eight engines daily. Generic Wikipedia monitors flag that a page changed; WikiAlerts™ flags the diff in real time with one-click revert. The result for clients is that we know what is actually happening across search and AI before anyone else in the room does, and the strategy reflects current state rather than last quarter’s snapshot.

Yes. AIQ is sold as a self-serve product and the majority of subscribers run it without any advisory engagement on the Five Blocks side. The typical pattern: an in-house comms team or agency starts a trial, sets up topics, and uses the data inside their own reporting workflow. Some of those subscribers later engage us when the data points to source-layer work they need help executing on. Others run AIQ on its own indefinitely. Both are valid uses of the platform.

GEO tools, in the current market, treat AI like SEO: count the mentions, optimize for more of them. That is a marketing measurement. AIQ measures reputation: the full content of what AI engines say about a brand, the sources they cite, the sentiment, the themes, the differences across engines, and the trajectory over time. The distinction matters in practice. A brand can be mentioned in every AI response for its category and still be losing the narrative if the response describes it badly or attributes the wrong story to it. GEO would call that a win. AIQ would call it a problem. For comms and corporate affairs teams, the comms framing is the one that matches the actual job.

They are designed to work together but they are separate products. AIQ™ is a SaaS platform – it monitors AI engine responses, identifies sources, and tracks narrative change. Five Blocks’ AI Reputation Management is the advisory service in which our analysts interpret AIQ data and our account team executes against it: improving the source layer, working at the Wikipedia and Knowledge Graph entity layer, coordinating with the client’s PR firm on placements that AI engines actually weight. Many clients start with AIQ alone, see what the data shows, and then bring us in for the source-layer work that the data points to. Others engage the full service from day one with AIQ embedded inside it.