Infracouch is building a verified, manufacturer-direct product data layer that AI agents can trust - preventing the compounding pollution of scraped and AI-generated product information across the web.
Direct from manufacturers. Standardized across industries. Ready for reasoning.
Your products recommended by AI agents. Your specifications, verified and distributed.
Clean data that improves reasoning. Legal compliance built in. Single API across industries.
Beta Program
No cost during beta. Lock in pricing. Limited spots per vertical.
AI models generate product descriptions. That content gets indexed. Next generation models train on AI-generated text. The feedback loop compounds errors. Product data degrades exponentially as AI-generated content floods search results and training datasets.
"Bad money drives out good money." Bad data drives out good data. SEO-optimized content is cheaper to produce and performs better in search. Accurate product specifications are expensive to maintain and get buried. The economic incentive favors misinformation. Truth becomes economically unviable.
Your specifications get rewritten. Your descriptions get modified. By the time AI agents find your products, the information is wrong. You have no direct channel to AI platforms.
AI companies scrape retailers. Retailers scrape manufacturers. No provenance chain. No consent mechanism. No standardization across industries. When copyright lawsuits arrive, everyone is exposed.
The result:
AI agents recommend products based on corrupted data. Manufacturers can't control their product representation. AI companies face legal exposure. The information commons collapses. Someone needs to build verified infrastructure before this becomes irreversible.
Same product. Two data sources. Different outcomes.
AI agent scrapes retail websites
Agent cannot determine:
• Which titles are actual model names
• If these are the same product at different prices
• What the real specifications are
• Which geometry fits the user
AI agent queries verified API
Agent reasoning:
Based on your query for endurance riding, the Canyon Ultimate CF SLX has ideal geometry (higher stack for comfort) and vibration-damped layup. At $3,299, it's within your high-end budget. The endurance geometry (stack: 563mm, reach: 398mm for size M) provides a more upright position suitable for long-distance comfort.
Agent: "Would you like me to find where you can purchase this frame?"
This is a real example from cycling. The same pattern repeats across every vertical.
Clean data produces better recommendations. Manufacturers control their representation. AI platforms avoid legal exposure.
What developers receive when querying the Infracouch API:
{
"product": {
"icid": "CANYON-ULTIMATE-CF-SLX-DISC-56",
"manufacturer": {
"name": "Canyon Bicycles GmbH",
"verified": true,
"updated": "2024-11-15T10:23:00Z"
},
"basic": {
"name": "Ultimate CF SLX Disc Frame",
"model_year": 2024,
"category": "bike-frames",
"use_case": ["endurance", "racing", "all-road"]
},
"specifications": {
"material": "Toray T1100 carbon fiber",
"layup": "endurance-optimized, vibration-damped",
"weight": {
"value": 850,
"unit": "grams",
"size": "M",
"measurement_type": "claimed"
},
"geometry": {
"size": "M",
"stack": 563,
"reach": 398,
"head_tube_angle": 72.5,
"seat_tube_angle": 73.5,
"unit": "mm"
}
},
"pricing": {
"msrp": 3299,
"currency": "USD",
"region": "US"
},
"provenance": {
"source": "manufacturer_direct",
"last_verified": "2024-11-15T10:23:00Z",
"data_version": "1.2"
}
}
}
Every field traces to manufacturer source. Every timestamp shows data freshness. Every product has provenance.
How manufacturers see their products in the system:
Available to Beta Manufacturers
Review ingested products. Approve changes. Monitor AI platform queries. Track data freshness.
How AI agents use the API to make recommendations:
User asks:
Agent queries Infracouch:
Agent receives verified data and reasons:
Based on your height (5'10"), a medium frame with stack of 560-570mm and reach of 390-400mm would fit well. The Canyon Ultimate CF SLX has endurance geometry (stack: 563mm, reach: 398mm), vibration-damped layup for comfort, and is within budget at $3,299 MSRP.
Reasoning based on actual specifications. Not marketing copy. Not guesswork.
Product schemas evolve. New attributes emerge. Industries have specific requirements. We maintain backward compatibility while allowing forward progress.
Universal fields across all products: ICID, manufacturer, basic info, pricing, provenance. Versioned independently. Breaking changes require major version increment.
Industry-specific attributes. Cycling has geometry. Cosmetics has ingredients. Electronics has technical specs. Each vertical maintains its own schema version.
Developers specify API version in requests. We maintain previous versions for 12 months after deprecation. Migration guides provided. No surprise breaking changes.
Beta manufacturers provide feedback on schema requirements. We implement changes that serve the majority use case while maintaining backward compatibility.
Be part of the verified catalog before AI platforms fully integrate
(We do not accept retailers)
When ChatGPT, Claude, or Perplexity need product data, they query our API. Your verified specifications reach AI agents without intermediaries modifying your information.
Limited spots per industry during beta. Early manufacturers establish presence before AI shopping becomes mainstream. Lock in positioning before competitors understand the opportunity.
Connect once. Your product data becomes available to any AI platform that integrates our API. Future-proof distribution as new AI agents emerge.
We pull from your existing feed. Shopify, CSV, or API. Automated updates. Review changes before they go live. Set it up once, maintain data accuracy automatically.
Web scraping gets you SEO spam and legal exposure. Our API provides manufacturer-direct data with consent and provenance. Reduce hallucinations. Improve recommendation quality.
Every product has consent documentation. Every specification traces to manufacturer source. When copyright lawsuits escalate, you have permission-based data with audit trails.
One API call instead of scraping multiple retailers. No data reconciliation needed. No conflict resolution between contradictory sources. Lower latency, lower inference cost, better results.
Same schema whether querying cosmetics, electronics, or sporting goods. Build once, query any vertical. Add new product categories without changing your integration.
Additional verticals added based on manufacturer demand
Shopify feed, CSV, or API. Any format accepted.
Automated enrichment with AI. Review and approve changes.
AI agents access your products through standardized API.
Submit application, receive credentials and documentation.
RESTful API with JSON. Query by category, brand, or attributes.
Improved recommendations, reduced errors, legal compliance.
Ready to Begin
Join manufacturers and AI developers building verified product infrastructure
Get your products into AI recommendations. No cost during beta.
Integrate verified product data into your AI agents and applications.
Yes. Consent plus provenance transform "nice-to-have data" into legally defensible, audit-trailed product truth that AI platforms can safely rely on.
Every product in Infracouch has documented manufacturer consent. Every field traces to its source. Every update has a timestamp and version. When copyright litigation escalates, AI platforms need proof of permission. When product liability questions arise, manufacturers need audit trails. This is legal infrastructure.
They won't manage tens of thousands of heterogeneous feeds, version policies, consent revocations, and schema drift. They want a single, versioned, cross-vertical interface.
Manufacturers don't publish machine-readable, schema-consistent, provenance-tracked feeds with uniform update semantics. Infracouch absorbs the combinatorial explosion; normalization, versioning, consent management, provenance tracking; and exposes a single API. Bypassing us means recreating our hardest work with worse reliability.
We detect changes automatically. Manufacturers review updates before they go live. AI platforms query the API for current data on demand. No stale data. No silent corruption. Complete update history maintained.
Core schema (ICID, manufacturer, provenance) is universal and backward-compatible. Vertical-specific schemas (cycling geometry, cosmetic ingredients) extend the core independently. API versioning guarantees no breaking changes without migration period. Developers specify version in requests. We maintain previous versions for 12 months post-deprecation.
Immediate removal from API. All cached data flagged for deletion. Audit trail maintained showing consent period. AI platforms notified via webhook. This is built into the consent architecture-not an afterthought.
You control what gets published. You see every change before it goes live. You can revoke consent instantly. You own your data-we're infrastructure, not a data broker. Our business model depends on your trust. If we violate that, we have no business.
Manufacturers: Per-product monthly fee ($0.05-0.50 depending on volume and vertical). API customers: Tiered pricing based on request volume. Beta participants lock in founder pricing permanently. No revenue sharing. No commission on sales. Infrastructure pricing.
No. We don't do aggregation or merge semantics. We preserve per-manufacturer truth, version it over time, and expose catalog-shaped views for consumption. Nothing gets homogenized.
Aggregators combine data from multiple sources and resolve conflicts by choosing or averaging. We don't. Each manufacturer's data remains distinct with its own provenance chain. When you query "bike frames," you get manufacturer-specific entries-not merged/averaged specifications. The truth stays attributable.
Not exactly. Think of Infracouch as data infrastructure that holds truth about manufacturer catalogs in layers-product data, versioning, provenance, audit trails. The API output is served in the form of a catalog, shaped to each request.
A catalog is a presentation layer. We're infrastructure that generates catalog views on demand. Query for "endurance bike frames under $3,500" and you get a catalog-shaped response. Query for "all products from Manufacturer X" and you get a different catalog view. Same underlying truth, different projections. The catalog is ephemeral-the versioned, provenance-tracked data layer is permanent.
Google Merchant Center optimizes for ads and shopping. We optimize for reasoning. GMC data is retailer-submitted and unverified. Infracouch data is manufacturer-direct with provenance. GMC is a walled garden. We're cross-platform infrastructure. Different purpose, different architecture, different outcome.
The verified catalog layer between manufacturers and AI agents.
Industry Verticals
Current Phase
Foundation
Beta participants get:
Questions
Infracouch
Verified product data infrastructure for AI agents