PR firms work with us in two modes. First, as a specialist partner: when a client needs Wikipedia work, source-layer Google work, or AI reputation work that sits outside the firm’s core practice, we deliver it under the firm’s umbrella or directly to the client at the firm’s recommendation. We have done this with the major global PR firms, public affairs shops, and law-firm communications groups for two decades. Second, as a technology supplier: agencies subscribe to AIQ on the agency plan to run AI reputation audits as pitch material, add AI intelligence to existing retainers, benchmark client brands against peers, and produce white-label reports. The two modes are independent – many firms use AIQ without ever engaging us on advisory work, and vice versa.

AIQ is organized around topics, and each topic exposes several views. The Responses view shows the full text of what every engine said this period and historically. The Sources view shows which domains, articles, and Wikipedia sections are being cited and how that distribution is shifting. The Themes view tags the narrative themes appearing across responses and shows their movement. The Sentiment view scores positive, neutral, and negative framing per engine and over time. The Peers view runs the same prompts and analysis against named peers so the brand can be compared directly. Export is available on every view as screenshot, CSV, or JSON.

A topic is the unit of analysis inside AIQ. When a user sets up a topic, they define the subject (a brand, executive, product, or theme), a set of prompts that AI engines will be asked about that subject, a peer set for comparison, and any tags they want to attach for filtering. The same prompts and peers run against all eight AI engines daily, so the resulting data is directly comparable across models. Most clients run between three and ten topics per brand, with separate topics for the corporate brand, key executives, key products, and any active issue.

WikiAlerts subscribes to Wikipedia’s live edit feed for every page on a user’s watch list. The moment a watched page is edited, an email notification goes out with a diff view showing exactly what was added, removed, or changed and by which editor account. If the change is clear vandalism, a one-click revert button rolls the edit back through the same mechanism a Wikipedia editor would use. This works because Wikipedia exposes its edit stream as a public feed – the engineering challenge is in the scale (millions of edits a day across all watched pages worldwide), the diff rendering, the email throughput, and not flooding users with notifications for trivial changes like reference reformatting.

An AIQ Snapshot is a single point-in-time view rather than a tracking program: three AI engines, four questions, one brand or one person, captured and packaged for immediate use. PR firms use Snapshots in new-business pitches to show prospects how AI is currently describing them and their peers. In-house teams use them to brief a CEO before a meeting or to spot-check a sensitive moment. They sit alongside the full AIQ™ subscription rather than replacing it: the Snapshot is the photograph; the subscription is the time-lapse.

Self-serve starts at $99 per month and is suitable for an in-house comms team tracking its own brand and competitors. The agency tier adds multi-client management, white-label reporting, and seat scaling for PR firms managing several client brands. The enterprise tier is custom-scoped and is typically combined with our advisory services so the platform output flows directly into a Five Blocks engagement. Full plan details and a trial are at aiq.fiveblocks.com.

Polling runs daily for each engine on each topic, and the full response is stored along with cited sources, sentiment, and theme tags. For a newly created topic, the first results appear within 15-20 minutes – the initial round runs immediately on save and then the daily cadence picks up. The daily cadence is deliberate: AI engine responses change frequently enough that less frequent polling misses important shifts, and frequently enough that more frequent polling rarely changes the picture meaningfully.

IMPACT™ tracks every URL appearing on Google’s results pages for a client’s defined keyword set, across 500 cities, 69 countries, and 23 languages. Each ranking URL is classified by ownership (client-owned, earned media, third-party, hostile), by SERP feature (organic, AI Overview, People Also Ask, knowledge panel, image, video, news), and by topic. The platform records peer rankings against named competitors and stores the full time series. The output is roughly 100 million data points per day across the active client base.

Yes – the data is yours. Every view inside AIQ can be exported as a screenshot, every dataset as CSV or JSON, and we are adding MCP server support that will let leading AI models query the platform directly. The export options matter because most users put AIQ output into other deliverables: monthly client reports, board decks, crisis briefings. The platform is designed to feed those downstream uses rather than trap the data inside its own interface.

The day-to-day use cases inside a PR firm are concrete. New-business pitches now routinely include an AIQ audit of the prospect’s current AI exposure alongside its named peers, which a firm without AIQ cannot match. Active retainers use AIQ for ongoing narrative tracking, with the platform output flowing into monthly client reports under the firm’s own brand. Crisis work uses topics that spin up in minutes for the specific narrative threads the team is fighting. And competitive intelligence work uses peer comparison views to show clients exactly how they stack against named competitors across each engine.