Equitus KGNN key for TD Synnex IBM Power 11 enterprise customers is to align KGNN's strengths directly with the existing pain points and strategic value propositions of the IBM Power ecosystem.
IBM Power 11 clients are already focused on high availability, on-prem control, core performance for licensing/TCO, and accelerating AI workloads. KGNN is a native fit that multiplies those benefits.
Here is a targeted marketing strategy structured around KGNN's three strengths, connecting them to the IBM Power 11 value chain:
Targeted Marketing Strategy: Equitus KGNN on IBM Power 11
1. Data-to-AI Acceleration: The "Data-to-AI" Bottleneck Killer
Customer Pain Point: Enterprise data is siloed, complex (structured/unstructured), and requires massive, manual effort (ETL/Data Prep) to make it AI-ready. This is the single biggest bottleneck to operationalizing AI.
KGNN's Unique Value Proposition on Power 11:
| Strength | Core Messaging | IBM Power 11 Connection | Call to Action/Proof Point |
| Data-to-AI Acceleration | Automate the Path to Enterprise AI. KGNN is a self-constructing Knowledge Graph platform that takes raw, disparate data (logs, PDFs, databases, documents) and automatically unifies, cleans, and transforms it into AI-ready, vectorized data for RAG, LLMs, and analytics. | Leverage Power's AI-Readiness: The Power11 chip has built-in Matrix Math Accelerator (MMA) units for fast inference. KGNN is Power-native and is the perfect front-end to feed the high-quality, vectorized data that Power's MMAs are designed to process, ensuring your AI is fast and accurate. | Benchmark Data: Show the speed difference: "Reduce your manual data mapping time from 85 hours to just 35 minutes (KGNN vs. Manual Mapping)." (See Search Result 1.1) |
| Key Differentiator | No-Code Data Unification: Eliminate the massive time and talent drain of manual ETL/data engineering for AI projects. KGNN's Auto-ETL and semantic mapping dramatically reduce the time-to-insight. | AI Talent Shortage Solution: IBM clients are struggling with talent shortages in AI/Data Analytics (Search Result 2.1). KGNN's automation frees up scarce, high-value data science talent from data preparation, allowing them to focus on model creation and business value. | Focus on RAG/LLM: Position KGNN as the critical component to build a secure, on-premise, enterprise-grade RAG foundation that works with watsonx and other LLM platforms. |
2. Compute Optimization & Efficiency: Maximizing Power Core Value
Customer Pain Point: IBM Power clients pay a premium for per-core licensing (e.g., databases, other software). They need applications that maximize the utilization and performance of every Power core to drive down software TCO. They also want to avoid the cost and complexity of external GPU infrastructure.
KGNN's Unique Value Proposition on Power 11:
| Strength | Core Messaging | IBM Power 11 Connection | Call to Action/Proof Point |
| Compute Optimization & Efficiency | No-GPU AI: Full Power Core Utilization. KGNN is engineered to run complex knowledge graph and AI inference workloads using the native Power architecture, specifically leveraging the on-chip MMA (Matrix Math Accelerator). | Maximize Investment & Lower TCO: By being fully Power-native, KGNN ensures your mission-critical data and AI workloads maximize the efficiency of your Power11 cores. This leads to better consolidation ratios and a much lower effective per-core software licensing cost for the overall solution. | Energy & Space Savings: "Achieve high-performance AI inference without the need for expensive, energy-hungry GPU cards." This directly appeals to the Power 11 messaging of "twice the performance per watt" vs. x86 (Search Result 4.4, 3.4). |
| Key Differentiator | Engineered for Resilience: Built to run on the platform known for | Resilience and Continuity: Position KGNN as an integral part of the client's cyber resiliency strategy. By unifying data in a single, secure, on-prem graph, it enhances the security and data integrity that IBM Power Cyber Vault and Quantum-safe Cryptography are designed to protect. | Solution Integration: Promote KGNN as an extension of the IBM value stack (e.g., works with Red Hat OpenShift, is Power-native) that the TD Synnex/IBM sales team is already incentivized to sell. |
3. Modernization & TCO Reduction: De-risking and Simplifying IT
Customer Pain Point: Modernizing core IBM systems (like IBM i or AIX applications) while maintaining mission-critical stability is a complex, high-risk, and costly undertaking. The manual work of connecting legacy data to new AI systems is driving up operational costs (OpEx).
KGNN's Unique Value Proposition on Power 11:
| Strength | Core Messaging | IBM Power 11 Connection | Call to Action/Proof Point |
| Modernization & TCO Reduction | Simplify Modernization with a Semantic Layer. KGNN provides an intelligent data fabric that sits on top of existing data sources, making decades of legacy enterprise data instantly usable for modern AI/analytics without risky, expensive, and time-consuming migrations. | Non-Disruptive Modernization: IBM Power clients need to modernize alongside existing applications (Search Result 4.1). KGNN is the ideal way to "modernize in place," giving new life to legacy data on the new, powerful Power11 platform. | OpEx Reduction: Quantify the savings by highlighting the elimination of manual ETL pipelines and simplified, autonomous operation. Frame it as "reducing the 5,000 hours per year spent on manual data management" that plagues IT teams (Similar to the pain point of patching in Search Result 2.2). |
| Key Differentiator | On-Premise Control for Regulated Industries: KGNN's commitment to being a fully on-premise solution (no mandatory cloud dependencies) resonates deeply with the core IBM Power client base in highly regulated industries (finance, government, healthcare) who need strict data sovereignty. | The Trust Factor: Aligns with IBM's long-standing reputation for trust, availability, and on-prem security. KGNN is the final piece of the secure, reliable, full-stack AI platform that IBM Power 11 promises. | Assessment Offer: Use IBM/TD Synnex's existing assessment funding programs (Search Result 1.2) to offer a "KGNN Readiness Assessment" or "AI Data Unification Assessment" to show the TCO reduction potential. |
Overall Pitch Summary (The Elevator Pitch)
"Equitus KGNN is the Power-Native Knowledge Graph platform that unlocks the full AI potential of your IBM Power 11 investment.
Instead of spending months and millions manually prepping data, KGNN automatically unifies your complex data into a vectorized, AI-ready fabric in minutes. It runs lean on your Power cores—not expensive, external GPUs—maximizing your server efficiency and dramatically lowering the total cost of ownership for your enterprise AI initiatives."
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