About AITWIRE
The AI Answer Platform
AITWIRE helps brands measure how AI answers about them to their target audience, fix the gaps, and prove what changed — across the AI systems they don't control and the ones they do.
As AI systems increasingly mediate how people discover, compare, and choose businesses, brands need a measurement layer, an action layer, and an authority layer. AITWIRE brings those together.
Why AITWIRE exists
Traditional websites were built for people first and machines second. That worked when search engines mostly indexed pages and ranked links. It works less well in a world where AI systems summarize, synthesize, and cite information across many sources at once.
AITWIRE was created to solve that gap.
The goal is simple: help organizations measure how AI answers about them, identify what needs to change, and publish verified, current information in forms AI systems can crawl, cite, and train on.
AITWIRE turns ordinary website content and brand knowledge into analytics, recommendations, drafts, and machine-readable authority surfaces — then measures whether AI systems are using them.
Across the product, the work is simple: See It with AI Analytics, Fix It with AI Recommendations, and Publish It with AI Publishing.
Mission
Measure how AI answers about you. Calibrate the record. Prove what changed.
AITWIRE exists to solve a practical problem: brands do not know what AI says about them, what to fix, or how to give AI a trusted source of authoritative data. The mission is AI Answer Assurance — measure how AI systems answer, calibrate the sources they read with the facts you approve, and prove what changed, with evidence you can review and retain.
What AITWIRE is building
AI Publishing
Keep verified surfaces — entity.json, JSON-LD, feeds, RSS, sitemaps — synced for AI crawlers, and publish the fix to the destinations you choose (your own CMS, structured and social surfaces) with canonical pointing back to your site.
AI Analytics
Measure how AI systems describe, cite, and recommend a brand to its target audience, with confidence on the data.
AI Recommendations
Turn measured gaps and drift into prioritized recommendations and factual content drafts.
Proof and governance
Control crawler access, track changes, and measure whether published authority surfaces are influencing AI answers.
Founder
AITWIRE is being built by Matthew Herbert, working with AI as a force multiplier across product strategy, drafting, systems design, implementation support, and iteration.
Matthew Herbert
Founder
Matthew Herbert is building AITWIRE as an AI Answer Platform for AI-facing information. The work combines product strategy, technical architecture, legal and governance thinking, and AI-assisted execution to move from concept to deployable platform faster and more precisely.
AITWIRE reflects a model of modern software creation where a founder works directly with AI to accelerate research, product design, copy, workflows, and implementation.
Milestones
Problem identified
The initial concept emerged from the growing gap between how websites publish information and how AI systems consume it.
Authority publishing model defined
Core ideas around machine-readable authority surfaces, governed publishing, and AI parseability were shaped into a product direction.
Initial audit and publishing workflows
Early workspace, audit, and authority-management capabilities were developed into a usable product structure.
Governance and multi-tenant thinking added
AITWIRE evolved from a simple visibility concept into a broader AI Answer Platform spanning measurement, publishing, and monitoring.
Publishing destinations + measured lift
AITWIRE now turns measured gaps into publishing across owned, free, and social destinations (canonical → your site), runs course-of-action campaigns, and reports the measured lift each action produces.
Build a stronger AI answer layer
Start with a free AI Readiness Assessment, then grow into AI analytics, recommendations, and verified publishing for your target audience.