The web is becoming an input to answers, not only a destination.
People increasingly ask AI systems to research, compare, summarize and recommend. That means a brand's information can influence a decision even when the user never lands on the brand's site or sees a traditional search result. At the same time, AI crawlers and software agents interact with digital properties as machine visitors.
SIGNAL was built to measure both sides of that transition: what happens inside AI answers and what happens when AI systems access, refer to and act on web information.
Demand side
What people ask, which intents are growing and where AI-mediated decisions are forming.
Answer side
How entities are represented, recommended, cited and compared.
Machine side
What crawlers and agents request or retrieve from first-party digital properties.
Business side
What AI referrals, campaigns and interventions mean for measurable outcomes.
Five modules, one measurement context.
| Module | Role |
|---|---|
| Intelligence | Measure AI demand and understand how AI represents brands, products, categories and competitors across answers. |
| Analytics | Measure AI crawlers, agents, retrieved content, AI referrals, conversions and business outcomes on connected properties. |
| Verify | Independently audit campaigns, GEO, agency claims, AI crawler access and policy behavior with methodology and evidence. |
| Ads | Plan, buy, measure and optimize paid media across supported AI advertising environments from a common control layer. |
| Distribution | Deliver authoritative, structured and attributable brand information across publisher and agent-ready Web, API, MCP, A2A, Mobile and TRUYN channels. |
The modules are connected deliberately. Intelligence identifies the market and answer problem; Analytics shows first-party machine and human outcomes; Verify tests claims; Ads and Distribution provide activation paths; measurement then continues after the intervention.
How SIGNAL is designed to operate
- Measure before optimizing.
Establish a baseline and a defined scope before claiming improvement. - Separate evidence classes.
Observed, modeled and independently verified values should remain distinguishable. - Keep measurement separate from the claim.
When possible, the party selling an intervention should not be the only party proving its impact. - Preserve provenance.
Important results should carry the source, methodology and evidence context needed to interpret them. - Connect to business outcomes.
AI visibility matters more when it can be connected to referrals, conversions, revenue or another defined organizational outcome.
SIGNAL is one part of InnMedia Group.
InnMedia Group builds infrastructure for the AI information economy across content creation, information operations, measurement, distribution, exchange and machine-readable data.
InnMedia SOLO
Consumer-facing AI content creation and publishing workflows.
InnMedia OS
B2B content operating infrastructure for organizations that need governed, repeatable content workflows.
InnMedia SIGNAL
Intelligence, analytics, verification, advertising and distribution for AI-mediated discovery.
InnMedia EXCHANGE
Infrastructure connecting information supply and demand in the broader InnMedia ecosystem.
InnMedia Data Graph
Structured information and data relationships supporting the group’s machine-readable information layer.
Truyn Network
Open distributed infrastructure work focused on resilient agent/network communication.
Built for organizations with something measurable at stake.
Brands
Understand AI demand, visibility, recommendation position, citations and competitive information gaps.
Advertisers
Plan around AI-native demand and connect paid activation to comparable outcomes.
Agencies
Add independent measurement and client-ready evidence to GEO, PR, media and content programs.
Enterprise
Govern AI measurement consistently across brands, markets, teams, vendors and internal data systems.
What we mean by the AI information economy
The old information economy centered on websites, search engines and human navigation. The emerging AI information economy increasingly includes AI assistants, answer engines and autonomous agents that retrieve, synthesize, compare and act on information for people and organizations.
In that environment, information needs more than publication. It needs discoverability, machine-readable structure, provenance, access policy, attribution, measurement and verification. SIGNAL focuses on the measurement and activation layer of that system.
See the AI information environment around your organization.
Start with demand and answer intelligence, connect first-party measurement, then decide what to verify, advertise or distribute.