Zero-Dev Proxy Architecture

[STD-AEO-006] | Network Systems Architecture | Last Updated: January 2026

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1. Technical Objective

Most enterprise platforms (Shopify, Salesforce) are built for human browsers and possess "Rigid Schemas" that are difficult to update for the Agentic Web. The objective of the RankLabs Proxy is to mirror the store's content, harden the metadata at the network edge, and serve a "Hardened Node" to AI agents without requiring a single line of backend code from the client.

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2. The Mirror. Harden. Proxy. Lifecycle

Our architecture operates on a cyclical validation loop to ensure 100% data fidelity:

Mirror (Ingestion)

The proxy acts as a high-speed gateway, performing a real-time crawl of the storefront. It captures raw HTML, price strings, and inventory status.

Harden (Transformation)

The raw data is passed through our Semantic Enrichment Engine. Here, we strip away "Noisy HTML" and inject the 20+ specialized attributes defined in [STD-AEO-003], including global identifiers (GTIN13) and cryptographic check-sums.

Proxy (Delivery)

When an AI agent (DeepSeek, Grok, Gemini) requests a URL, the proxy detects the "User-Agent" and serves the Hardened JSON-LD Node directly. Humans continue to see the standard storefront, while machines receive a defense-grade data stream.

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3. Network Routing Logic

To maintain sub-millisecond latency and prevent "Stale Data Hallucinations," we implement specialized routing protocols:

Agent Detection Engine

We maintain an exhaustive database of frontier model crawlers. This allows the proxy to distinguish between a "passive scraper" and a "shopping agent" like Siri or Meta AI, delivering a custom-tailored data response for each.

Edge-Side Injection (ESI)

We use ESI to "stitch" the hardened metadata into the page header at the CDN level. This ensures that even if the primary server is slow, the "Truth Layer" is delivered instantly to the ingesting agent.

Asynchronous Verification

While the proxy serves the current node, it triggers an asynchronous check-sum match with the store API. If a price change is detected mid-ingestion, the proxy immediately invalidates the current cache and updates the priceValidUntil timestamp to prevent hallucinations.

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4. Security and Isolation Protocol

Following Zero-Trust principles, we implement strict isolation for enterprise clients:

Dedicated Proxy Instances

Every RankLabs client is assigned a dedicated proxy instance to prevent cross-brand data leakage.

Cryptographic Signing

Every packet served by the proxy is cryptographically signed at the edge. This allows AI agents that support verified data standards to confirm the "Chain of Custody" from our Palisades Park laboratory to their ingestion engine.

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Implementation Comparison

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Next Steps

Access the Specification: View Multi-Agent Citation Benchmarks (STD-AEO-007)

Deploy Pilot: View Pricing Tiers

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Systems Architecture by Sangmin Lee, ex-Peraton Labs. Engineered in Palisades Park, New Jersey.