01.
Be understood
Expose canonical facts, stable identifiers, and source hierarchy so agents represent the business accurately.
Infrastructure for the agent-driven web
The web's biggest audience isn't human.
Agents now outnumber people on the internet. The audience has already shifted.
“When pricing and trust signals are buried in prose, the agent moves on. Your customer never sees the option.”
READINESS RESEARCH, INTRINSIC
Industry focus
E-COMMERCE
Scan your site
Each dot represents a scanned site
Readiness data
What agents need from your site
Seven dimensions we score on every scan. Percentages reflect typical aggregate scores across our sample — lower means more room to improve.
- 01.Discoverability34%
- 02.Legibility52%
- 03.Freshness28%
- 04.Trust38%
- 05.Comparison readiness41%
- 06.Action readiness19%
- 07.Standards compliance11%
Dimension detail
Hover a row to see what we measure across 2,400+ scans.
The gap
Human-only sites vs. human + agent interfaces
The same journey looks different when the machine layer is explicit. Baselines are illustrative composites from scanner aggregates.
Human-only interface
Legibility
Marketing prose, implicit facts
35% typical baseline
Human + agent interface
Legibility
Canonical facts, stable IDs
88% target with Intrinsic
Human-only interface
Trust
Policies buried in copy
28% typical baseline
Human + agent interface
Trust
Provenance + boundaries explicit
82% target with Intrinsic
Human-only interface
Action readiness
Forms and guesswork
12% typical baseline
Human + agent interface
Action readiness
Declared machine actions
76% target with Intrinsic
Human-only interface
Standards
Fragmented or missing
15% typical baseline
Human + agent interface
Standards
One source, every standard
91% target with Intrinsic
Human-only interface
Commerce
Browse-to-buy only
22% typical baseline
Human + agent interface
Commerce
Query-to-transact paths
79% target with Intrinsic
By industry
Readiness isn’t evenly distributed
High-traffic categories often show lower readiness — more agent volume, more friction.
Bubble size ∝ sites in sample. Dark fill = above composite average readiness.
Outcomes
One platform, four practical outcomes
02.
Be surfaced
Improve how offers appear in research flows, shopping results, and agent-generated recommendations.
03.
Be trusted
Make freshness, provenance, and policy boundaries obvious so agents know what is authoritative.
04.
Be acted on
Support clean machine paths from comparison to quote, reserve, subscribe, or buy.
Aggregate scan data
2,400+ sites scanned
Average readiness across scanned sites
Legibility
52
Action readiness
19
Standards compliance
11
Trust signals
38
31 / 100
Average readiness
The next web interface isn't just visual. It has to work for the systems acting on behalf of your customers.
Start here
Scan first. Fix what matters.
See where agents get stuck — then close the gap with manifests, detection, and policy.