The era of artificial intelligence is no longer on the horizon; it's here, and it's transforming industries. For enterprise leaders, the question is no longer if you should implement AI, but how and where your AI workloads should run to maximize impact.
To help you navigate this choice, we've developed a comprehensive decision framework, now available as an interactive assessment that takes the guesswork out of your AI deployment strategy. More importantly, we've built the complete ecosystem to support whatever approach your assessment reveals as optimal. The reality is that most enterprises don't face an either/or decision. Instead, they need a framework that helps them understand which workloads belong where, and then the technology stack to implement that vision seamlessly.
Inside the Assessment: The Six Critical Factors
Our interactive assessment is built on six weighted factors, distilled from years of customer deployments, that determine the optimal placement for your AI workloads.
1. Latency Sensitivity (25% weight)
The Question: How critical is response time for your use case?
Real-time applications like autonomous systems, industrial automation, and AR/VR experiences simply cannot tolerate cloud round-trip delays. When milliseconds matter, edge processing isn't optional – it's mandatory.
SECO's Edge Solution: Our Titan 300 TGL-UP3 AI delivers the computational power needed for complex AI workloads that must run locally. It's engineered to handle everything from computer vision to natural language processing with minimal latency.
2. Data Privacy Requirements (20% weight)
The Question: How sensitive is the data you're processing?
Healthcare PHI, financial PII, and proprietary business data often cannot leave the premises – legally or strategically. In these scenarios, edge processing isn't just a technical choice; it's a compliance requirement.
SECO's Privacy-First Approach: By keeping sensitive data processing local with our edge computing solutions, you maintain complete control over your data lifecycle while meeting the strictest regulatory requirements like GDPR and HIPAA.
3. Connectivity Reliability (15% weight)
The Question: How reliable is your network connectivity?
Manufacturing floors, retail stores, transportation hubs, and remote agricultural sites can't depend on consistent cloud connectivity. When network outages mean business disruption, edge AI provides the resilience and operational continuity you need.
4. Model Complexity Requirements (20% weight)
The Question: How complex are your AI models?
This is where SECO's diverse hardware portfolio shines, offering tailored performance for every type of model.
For Complex AI Workloads: The SOM-COMe-BT6-RK3588 coupled with Axelera AI’s Metis AIPU delivers exceptional inference performance for demanding neural networks and multi-modal AI applications.
For Efficient Small AI Loads: The SOM-SMARC-MX95 with its integrated 2 TOPS NPU provides the perfect balance of power efficiency and AI capability for lighter workloads that still benefit from the responsiveness of edge processing.
5. Scale and Volume (10% weight)
The Question: What scale are you operating at?
From a single-device prototype to an enterprise-wide deployment, different scenarios require different approaches. The cloud excels at massive, fluctuating scale, while the edge provides predictable performance and cost control for distributed fleets.
6. Resource Availability (10% weight)
The Question: What resources do you have available?
Not every organization has unlimited cloud budgets or dedicated AI infrastructure teams. SECO's solutions are designed to be deployed and managed efficiently, minimizing operational overhead while maximizing your AI capabilities.
The Power of Hybrid: SECO's Clea Framework
Here's where SECO truly differentiates itself: we don't just help you choose between edge and cloud – we enable you to leverage both optimally through our Clea Framework.
Clea represents a paradigm shift in AI orchestration. Rather than forcing a binary choice, Clea allows enterprises to build a sophisticated, unified hybrid strategy.
Intelligent Workload Distribution: Clea allows you to orchestrate AI workloads dynamically. Critical, latency-sensitive processing happens at the edge using our specialized hardware, while complex model training and batch analytics can leverage the immense resources of the cloud.
Seamless Edge-Cloud Integration: With Clea, data flows seamlessly between your edge devices and cloud services. You can perform real-time inference locally, while securely sending aggregated, anonymized data to the cloud for deeper analysis and retraining.
Unified Management: Clea provides centralized fleet management for all your distributed AI deployments. Whether you're managing ten devices or ten thousand, you get consistent visibility, control, and the ability to deploy updates across your entire AI infrastructure from a single pane of glass.
Find Your Optimal AI Strategy
The question is not "Edge or Cloud?" but "What is my optimal AI strategy?". To help you answer that question, we've turned this decision framework into an interactive assessment.
In just a few minutes, you can evaluate your project's specific needs against these six critical factors and receive a tailored recommendation for an edge, cloud, or hybrid approach —- powered by SECO’s technology stack. Stop guessing and start building with a clear, data-driven strategy.
Ready to find out where your AI workloads belong?
Take the Interactive AI Strategy Assessment Now!