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G-Stacker Gets Google-Approved AI Application Status, Launches Beta Platform for Automated Business Entity Verification

Platform addresses growing “Entity Contamination” problem affecting small business visibility in AI-driven search results

Business owners should not need to be data architects to maintain their visibility in AI search”
— Ferdinand Mehlinger

SEATTLE, WA, UNITED STATES, February 24, 2026 /EINPresswire.com/ — G-Stacker, a newly developed digital infrastructure platform, has been designated as a Google-Approved AI Application and has entered a limited Beta release, the company announced today. The platform automates the verification and distribution of business entity data across Google’s Knowledge Graph and AI search infrastructure — a technical process that has become increasingly consequential for local businesses as AI-assisted search has expanded.

The Google-Approved AI Application designation indicates compliance with Google’s 2026 standards for data integrity and brand verification, a framework the search company introduced in response to concerns about AI-generated content accuracy across the web.

A Documented Shift in Local Search Visibility
The platform’s launch corresponds with a widely reported transition in how search engines process local business information. For approximately two decades, search ranking depended primarily on keyword optimization — the strategic placement of search terms across web properties. As AI has become central to the search experience, major platforms have shifted toward evaluating businesses as “entities,” defined as verified, machine-readable identities confirmed across multiple authoritative data sources.

Under this model, a business’s visibility in AI-generated recommendations depends on the consistency of its identity data — including name, address, phone number, business category, and associated identifiers — across the web. When inconsistencies exist across directories, review platforms, and listing services, search algorithms may classify the business as an unreliable data source and exclude it from AI-generated results.

Search industry practitioners have termed this problem “Entity Contamination.” The issue is considered particularly significant for small and mid-sized businesses, which typically accumulate inconsistent data across platforms over years of operation and lack the internal resources to audit and standardize that data at scale.

Platform Functionality
G-Stacker addresses this challenge through a process the company describes as Autonomous Entity Retrieval. A business enters its brand name and website URL. The platform then conducts an automated scan using an integration with Perplexity’s AI research engine, retrieving the business’s Google Business CID — a unique identifier Google uses to track physical locations — along with additional verified data points including team member information, brand categorization, and existing Knowledge Graph position.

The retrieved data is then distributed across a redundant multi-cloud network utilizing Amazon Web Services, Microsoft Azure, and Google Cloud simultaneously. The company has filed a patent application on this architecture, which it describes as a “Semantic Mesh” designed to ensure consistent entity data delivery regardless of the path through which a search engine accesses the information.

The automated retrieval approach is intended to eliminate manual data entry errors, which the company identifies as a primary cause of entity inconsistency. Rather than requiring users to input their own business information — a process that frequently introduces the formatting variations that degrade entity authority — the platform draws directly from verified existing sources.

“Business owners should not need to be data architects to maintain their visibility in AI search,” said Ferdinand Mehlinger, founder of G-Stacker. “The system retrieves what is already verified and builds a consistent record around it. That precision was previously only available to companies with dedicated technical teams.”

Access and Eligibility
G-Stacker Beta is currently available through a limited Beta program accessed via an application-based private community. Admission is manually reviewed. The company cites compliance with Google’s policies on Scaled Content Abuse as the basis for its screening process, excluding industries associated with low-quality content generation or unregulated sectors from participation.

Mehlinger noted that the vetting process is designed to protect the search authority of all participating businesses. “A platform’s standing with Google is influenced by the collective behavior of its users,” he said. “Keeping the participant base limited to verified, legitimate businesses protects the integrity of the system for everyone in it.”

About G-Stacker
G-Stacker is a Google-Approved AI application that automates the verification and distribution of business entity data for local brands. The platform is currently in limited Beta and is accepting applications from businesses across all service categories.

About Ferdinand Mehlinger
Ferdinand Mehlinger is a systems architect and former developer on the early team behind Backrub, the Stanford research project that became Google. He has worked across search infrastructure, SEO strategy, and AI application development for more than two decades.

Ferdinand Mehlinger
G-Stacker
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