Proposal: Aimlux.ai MSP - AEA - SmartFabric IBM Aspera Faspex and Equitus.us KGNN (Knowledge Graph Neural Network) work together effectively, primarily because both are deeply integrated into the IBM Power ecosystem (specifically Power10 and Power11).
While serving different functions, they are often paired in high-security, high-performance "data pipelines" where huge volumes of sensitive information need to be moved and then instantly analyzed.
How They Complement Each Other
In a typical deployment, the two products fulfill a "Transport and Transform" workflow:
| Feature | IBM Aspera Faspex | Equitus KGNN |
|---|---|---|
| Primary Role | Transport: Moves large data sets at maximum speed over any distance. | Analysis: Automatically builds knowledge graphs from raw data. |
| Technology | Uses the FASP protocol to bypass TCP bottlenecks. | Uses a native graph database engine built for IBM Power MMA. |
| Data Handling | Handles the "Ingest" phase (getting files into the system). | Handles the "Intelligence" phase (connecting dots between files). |
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Common Use Cases
* Secure Intelligence & Defense: Aspera Faspex securely transfers massive, unstructured sensor or intelligence data from the edge to a central hub. Once it arrives, Equitus KGNN automatically ingests that data to identify patterns, threats, or entities without manual data entry.
* GPU-Free AI at the Edge: Since Equitus KGNN runs natively on IBM Power (using the Matrix Math Accelerator) and doesn't require GPUs, and Aspera is optimized for low-bandwidth/high-latency links, they are frequently used together in remote environments where cloud connectivity is restricted.
* Automated ETL Pipelines: Organizations use Faspex to "drop" data into a watched directory. Equitus KGNN then monitors that directory to perform automated semantic mapping and entity resolution in real-time.
Technical Synergy
* Infrastructure: Both are optimized for IBM Power10/11 hardware.
* Storage: They both frequently sit on top of IBM Storage (FlashSystem), allowing for high-speed read/writes during the transfer and analysis phases.
* No Cloud Dependency: Both can be deployed entirely on-premises (Air-Gapped), which is the primary reason many Equitus customers choose this specific stack.
Would you like more technical details on how to set up an automated "Watch Folder" in Faspex to feed directly into the KGNN ingestion engine?
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