interface between Wallaroo.ai and Equitus.us KGNn

 

An interface between Wallaroo.ai and Equitus.us KGNn could be established by using Wallaroo.ai's workload orchestration features to process data from KGNn.

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Wallaroo.ai uses YAML (.yml) files for configuration and installation, and ZIP files containing instructions, requirements, and artifacts for its workload orchestrations. Equitus.us's KGNn platform automatically ingests, unifies, and contextualizes data into an "AI-ready knowledge graph."

A possible workflow for integration would be as follows:

1. Data Ingestion and Contextualization: Equitus.us's KGNn would ingest and process disparate data, structuring it into a knowledge graph.

2. Wallaroo.ai Workload Orchestration: A Wallaroo.ai workload orchestration, defined by a ZIP file, could contain a Python script that connects to the Equitus.us KGNn API. This script would fetch the "AI-ready" data for a specific inference task.

3. Inference Execution: The Wallaroo.ai inference engine would then execute the model on the data retrieved from KGNn.

4. Result Handling: The orchestration could be configured to send the inference results back to Equitus.us to be integrated into the knowledge graph, or to another specified destination.

Wallaroo.ai's API and SDK offer a lightweight way to make these connections, allowing for custom data sources like Equitus.us KGNn to be integrated into Wallaroo.ai's automated and scheduled ML workflows.

IBM ISVs Equitus.us and Wallyroo.ai on IBM Power 11

 

A combination of IBM ISVs Equitus.us and Wallyroo.ai on IBM Power 11 can significantly improve AI deployment and add value for multinational enterprises by addressing key challenges related to data management, AI operationalization, and infrastructure optimization. This synergy creates a powerful end-to-end solution for AI.

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⚙️ How the Combination Adds Value

The combined solution provides a comprehensive platform that handles the entire AI lifecycle, from data preparation to model deployment and management.

Data Management & Preparation with Equitus.us

Equitus.us specializes in knowledge graph neural networks (KGNNs).¹ For multinational enterprises, this capability is invaluable for several reasons:

• Data Unification: Multinational corporations often have vast, disparate data silos across different regions and business units. Equitus.us's KGNN automatically ingests and unifies structured and unstructured data, creating a single, contextualized source of truth.² This eliminates the manual, time-consuming process of data cleaning and preparation, which is a major bottleneck in AI projects.³

• Traceability and Explainability: The knowledge graph provides full data provenance, allowing businesses to trace where data came from and how it was used in an AI model.⁴ This is crucial for compliance with data privacy regulations (like GDPR) and for providing explainable AI (XAI), which builds trust in AI-driven decisions.

• Contextual Intelligence: By linking data points and discovering hidden patterns, the knowledge graph provides rich context to AI models.⁵ This enhances the accuracy and relevance of AI applications, especially for complex tasks like fraud detection, supply chain optimization, and market analysis across different global markets.

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AI Operationalization & Performance with Wallyroo.ai

Wallyroo.ai focuses on the "last mile" of the AI journey, which is the deployment and management of models in a production environment.⁶

• Simplified Deployment: Wallyroo.ai's platform provides a turnkey solution for deploying AI models, regardless of the model type or hardware.⁷ It automates model packaging and deployment, significantly reducing the engineering time and complexity typically associated with getting AI from a prototype to a live application.⁸

• High-Performance Inference: The platform's high-performance inference engine, optimized for IBM Power 11, can deliver a significant boost in performance, with up to 2x faster inference latency and throughput. This is essential for applications requiring real-time decision-making, such as fraud detection, real-time analytics, and customer service chatbots.

• Centralized Governance: With Wallaroo's centralized management and monitoring capabilities, multinational enterprises can manage all their deployed models from a single console.⁹ This includes real-time monitoring, drift detection, and automated alerts, ensuring models remain accurate and performing optimally across all operational regions.

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Leveraging the IBM Power 11 Infrastructure

Running these ISV solutions on IBM Power 11 provides the underlying computational power and security necessary for large-scale, mission-critical AI workloads.¹⁰

• AI-Optimized Architecture: The IBM Power 11 is designed from the ground up to handle demanding AI workloads.¹¹ It includes a built-in AI accelerator (the Spyre Accelerator) and is optimized for AI inference, allowing for faster and more efficient processing of AI tasks.¹²

• Resilience and Security: With features like a guaranteed 99.9999% uptime and the IBM Power Cyber Vault for rapid ransomware detection, Power 11 provides the enterprise-grade reliability and security that multinational corporations demand for their sensitive data and mission-critical applications.¹³

• Hybrid Cloud Flexibility: Power 11 allows for flexible deployment in both on-premises and hybrid cloud environments.¹⁴ This is particularly beneficial for multinational enterprises that need to comply with data sovereignty laws by keeping sensitive data within specific geographical boundaries while still leveraging cloud-based services.