Network EYE - Equitus.ai and CyberSpatial on AWS

 

Equitus.ai and CyberSpatial on AWS: Intelligent Ingestion Technology

AIMLUX.ai Solutions Proposes - Network EYE - the deployment of Equitus.ai (KGNN & Graphixa) and Cyberspatial Teleseer are both deployed on Amazon Web Services (AWS), they form a "Cognitive Network Defense" and "Governance Factory" stack.

The AIMLUX integration solves the most difficult problem in AWS migrations: The gap between what you think is in your cloud and what is actually happening on the wire.

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1. The Integrated AWS Architecture: 

Improving the cyber security for cloud based networks Network Eye, Commercial Teleseer AMI provides the "Ground Truth" (Sensory Layer), while Equitus KGNN and Graphixa provide the "Semantic Intelligence" (Cognitive Layer).

Component	AWS Resource	Role
Observation	AWS VPC Traffic Mirroring	Replicates raw packets from production ENIs and sends them to the Teleseer sensor.
Extraction	Teleseer (AWS AMI)	Analyzes traffic passively to build a real-time Digital Twin of the network topology.
Governance	Graphixa.ai (AWS)	Ingests the Teleseer topology and applies Triple Logic to create a deterministic audit trail of data movement.
Inference	Equitus KGNN (AWS)	Powers the knowledge graph to detect Mission Relevant Terrain (MRT) and hidden risks (Shadow IT).

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2. How the Integration Works (Technical Handshake)

The integration moves data through three distinct "states of truth":

State 1: Network Truth (Teleseer)

Teleseer captures the raw VPC traffic and identifies every host and protocol.

• Example: It sees a legacy Oracle instance (10.0.1.50) sending 5GB of data to an S3 Endpoint.

State 2: Semantic Truth (Graphixa)

Graphixa ingests this network data and converts the "connection" into a Semantic Triple. It applies the enterprise ontology to give the connection a business purpose.

• Triple: Payroll_Database --->  performs_Backup ---> S3_Migration_Bucket.

State 3: Mission Truth (Equitus Fusion (KGNN))

The Fusion (KGNN) analyzes the triples to ensure they align with the mission. If it sees a triple like Payroll_Database ---> connects_to ---> Unknown_External_IP, it flags it as an Inconsistency. Because it's a Neural Network, it can infer that the external IP is likely a "Shadow IT" reporting tool that was never authorized.

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3. Key Benefits for Enterprise Migrations

• Zero-Blindness Migration: Before moving an Oracle database to SAP RISE or IBM DB2, Teleseer identifies all hidden dependencies (the "spaghetti" of old APIs). Graphixa then creates a "Migration Road Map" based on these triples.

• 100% Deterministic Audit: For every record landed in the new AWS environment, Graphixa provides a "Proof of Transit." This is an immutable audit receipt linking the database record back to the exact packet hash captured by Teleseer on the AWS wire.

• Explainable AI (XAI): When a security alert is triggered, the KGNN doesn't just say "Danger." It provides the Semantic Lineage, explaining why the connection is risky based on its relationship to your Mission Relevant Terrain.

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4. Deployment Workflow on AWS

1. Sensor Deployment: Launch the Teleseer AMI in a dedicated Security VPC.

2. Traffic Mirroring: Enable AWS VPC Traffic Mirroring on your mission-critical Application ENIs, setting the Teleseer instance as the destination.

3. Intelligence Ingestion: Use a Python-based Lambda or direct API hook to push Teleseer's JSON-LD topology updates into the Graphixa/Equitus ingestion endpoint.

4. Ontology Mapping: Define your "Clean Core" or "Zero-Trust" rules within the Equitus KGNN to begin automated monitoring.

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Graphixa Solves the Trust and Credibility Gap

Graphixa Solves the Trust and Credibility Gap

AIMLUX.ai and its distribution through Global Systems Integrators (GSIs) like TD SYNNEX, Sycomp, and VLCM, Graphixa serves as a bridge between the "raw" power of open-source AI and the "rigorous" requirements of enterprise-scale production.

While the open-source version allows for experimentation, the AIMLUX Service SKU addresses the specific "Day 2" operational headaches that enterprises face when trying to move AI from a developer's laptop to a global data center.

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1. The "Open Source to Enterprise" Chasm

Open-source software is great for building, but notoriously difficult to support. GSIs use the Graphixa SKU to solve the Trust and Reliability Gap:

• The Problem: Enterprises cannot run mission-critical apps on "best effort" community support.

• The Solution: The Service SKU provides SLA-backed support, indemnification, and curated updates. This allows GSIs to sell a "validated" solution that won't leave the customer stranded if a bug crashes their production pipeline.

2. Infrastructure Complexity (The "GPU Bottleneck")

Graphixa is often positioned at the intersection of AI Graph Computing and GPU Optimization.

• The Problem: Managing heterogeneous GPU clusters (NVIDIA, AMD, etc.) and optimizing data flow between them is incredibly complex.

• The Solution: Graphixa simplifies resource orchestration. It solves the problem of "under-utilized silicon," ensuring that expensive GPU resources are maximized rather than sitting idle due to poor workload scheduling.

3. Data Lineage and Governance

For highly regulated industries (Finance, Healthcare), "black box" AI is a non-starter.

• The Problem: Difficulty in tracking how data moves through a graph-based AI model, leading to compliance risks.

• The Source: Graphixa provides enhanced visibility and auditability. It allows GSIs to build "Explainable AI" frameworks where every node and edge in the data relationship is logged and traceable.

4. Integration Fatigue

GSIs like Sycomp and VLCM specialize in making different systems talk to each other.

• The Problem: "Shadow AI"—disparate teams using different open-source tools that don't integrate with the core IT stack (ERP, CRM, etc.).

• The Solution: The AIMLUX SKU includes pre-built connectors and APIs that allow Graphixa to snap into existing enterprise environments, reducing deployment time from months to weeks.

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Comparison: Open-Source vs. AIMLUX Service SKU

Feature	Open-Source Graphixa	AIMLUX Service SKU (via GSIs)
Support	Community-driven / Forums	24/7 Enterprise SLAs
Security	Manual patches	Hardened images & proactive patching
Scalability	DIY orchestration	Automated cluster management
Compliance	User-responsible	Audit logs & Governance frameworks

Governance and Traceability

 

Now Offered as an Open-Source Software Solution, Graphixa.ai is part of the Equitus.ai suite of intelligent ingestion services. Graphixa.ai promises to help organize and improve the enterprise data migration efforts with end-end service.

Graphixa.ai acts as the Governance and Traceability Layer in an Oracle-to-SAP/IBM RISE migration. Within the Equitus.ai family, it utilizes the Triple Store Ontology to ensure that data does not just move from point A to point B, but maintains its semantic integrity and auditability throughout the journey.

Graphixa.ai assists in the migration to SAP or IBM DB2 RISE platforms: By adding semantic verification and utilizing the triple store architecture Manual Integration is greatly reduced. Adding a layer of augmentation, automation and authorization to reduce costs and risks in system migrations.

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1. Zero-Blindness Dependency Mapping

Before the migration begins, Graphixa.ai works with Network Eye (Teleseer) to map the "Data-in-Motion."

• The Problem: Oracle databases often have "Shadow IT" or undocumented APIs that rely on them. Moving the database blindly breaks these connections.

• The Graphixa Solution: It ingests PCAP (Packet Capture) data and converts it into Semantic Triples (e.g., App_A ---> queries ---> Oracle_Table_X). This creates a "Live Topology" that identifies exactly what must be refactored or reconnected in the new SAP/IBM environment.

2. Semantic Data Harmonization (Triple Logic)

Migrating from Oracle to SAP/DB2 is not a 1-to-1 mapping; it requires a structural transformation.

• Ontology-First Migration: Instead of simple ETL (Extract, Transform, Load), Graphixa uses Equitus KGNN logic to map data based on meaning. It identifies that "Customer_ID" in Oracle is semantically identical to "BusinessPartner_ID" in SAP.

• Automatic Schema Alignment: By using a Triple Store, Graphixa handles the "looseness" of legacy data, allowing for the ingestion of unstructured notes or legacy comments into the structured fields of the new platform without losing context.

3. "Clean Core" Verification for SAP RISE

SAP's "Clean Core" principle requires getting rid of legacy customizations and keeping the ERP standard.

• Custom Code Analysis: Graphixa identifies which Oracle-specific SQL features (like certain stored procedures) are actually being used by the business.

• Targeted Refactoring: It flags unused "dead code" in the legacy system so you only migrate what is necessary, ensuring your SAP S/4HANA or IBM RISE environment starts "clean."

4. 100% Deterministic Proof of Transit

This is the most critical feature for highly regulated industries (USSF, NIWC, Finance).

• The Audit Chain: For every record landed in IBM DB2 or SAP, Graphixa generates an immutable triple-store receipt:

  • Fact A: Target_Record_001 was generated from Source_Packet_999.

  • Fact B: Source_Packet_999 was verified by Network_Eye at 10:01 AM.

• Traceability: If an auditor questions a data value in the new system, Graphixa can trace it back through the Semantic Lineage to the raw network packet that left the original Oracle database.

5. Deployment on IBM Power10/11 - Equitus.ai KGNN runs natively on Power10/11 

For organizations using IBM RISE or seeking Sovereign AI capabilities:

• Native Optimization: Graphixa and Equitus are optimized for IBM Power10 servers. They use the Matrix Math Accelerator (MMA) to process these complex triple stores and graph neural networks without needing expensive, high-heat GPUs.

• Air-Gapped Security: This allows the migration governance to run entirely on-premise or in a "disconnected" cloud enclave, ensuring sensitive Oracle data never leaves the organization's control during the transition.

Summary of Value

Migration Phase	Traditional Method	Graphixa.ai Method
Discovery	Manual spreadsheets & API checks	Automated Triple Store Mapping
Mapping	Heuristic (Guessing)	Semantic (Deterministic Logic)
Validation	Sample-based testing	100% Packet-to-Record Audit
Governance	Disconnected logs	Unified Semantic Lineage

"Graphixa.ai: Open Source Governance. Semantic Certainty."

"Graphixa.ai: Open Source Governance. Semantic Certainty."

AIMLUX Solutions - Graphixa.ai as an open-source product within the equitus.ai ecosystem delivers a strategic balance between "community-driven accessibility" and "enterprise-grade rigor."

Because it utilizes triple stores (Subject-Predicate-Object) and ontologies, your marketing should move beyond "data moving" to "semantic integrity." Here is a framework for marketing Graphixa.ai:

1. The Core Value Proposition: "Data Migration with a Memory"

Traditional migration tools are "stateless"—once the data moves, the context is often lost. Graphixa’s use of triple stores allows it to maintain the semantic lineage of data.

• Messaging: "Don't just move your data; migrate its meaning."

• The "Triple" Benefit: Explain that by using triple stores, Graphixa doesn't just copy rows; it understands the relationships between data points, making the migration "self-documenting" and 100% traceable.

[Summary of Value]

Migration Phase	Traditional Method	Graphixa.ai Method
Discovery	Manual spreadsheets & API checks	Automated Triple Store Mapping
Mapping	Heuristic (Guessing)	Semantic (Deterministic Logic)
Validation	Sample-based testing	100% Packet-to-Record Audit
Governance	Disconnected logs	Unified Semantic Lineage

2. Marketing the "Open Source" Advantage

In governance and security, "Open Source" is a mark of trust, not just a price tag.

• Transparency as a Feature: Market the code’s openness as a security benefit. For mission-critical users (like USSF or NIWC), being able to audit the migration logic is essential.

• The "Anti-Lock-In" Strategy: Highlight that unlike proprietary migration suites, Graphixa uses W3C standards (RDF/SPARQL). This ensures that the data remains accessible and the migration logic isn't trapped in a "black box."

3. Positioning within the Equitus.ai Family

Leverage the "Halo Effect" of the KGNN (Knowledge Graph Neural Network).

• The "Intelligence Intake": Position Graphixa as the ingestion engine for Equitus.AI.

• Concept: "Graphixa builds the foundation; Equitus provides the brain." Use this to target enterprises that want to move to an AI-ready state. Graphixa prepares the "Clean Core" by structuring data into the semantic triples that the KGNN needs to function.

4. Target Market Segments & "Hook" Narratives

Segment	The "Pain Point"	The Graphixa.ai "Hook"
Federal/Defense	Compliance & Audit Trails	Deterministic Lineage: Every migrated record has a triple-store audit trail back to its source.
Enterprise IT	Broken App Dependencies	Ontology-Based Mapping: Automatically identify which apps will break by visualizing the "semantic web" of dependencies.
Data Scientists	Poor Data Quality post-migration	Semantic Validation: If the triple logic doesn't match the ontology, the migration stops—ensuring only "clean" data moves.

5. The Commercialization Path (The "Aimlux.ai Consulting" Model)

Since the software is open source, the revenue and marketing efforts should focus on Services and Sovereignty:

• The "Sovereign AI" Package: Market a bundled service where Aimlux.ai deploys Graphixa on IBM Power10 for air-gapped environments.

• Certification & Governance: Offer "Certified Migration Frameworks" for specific industries (e.g., "Graphixa for HIPAA" or "Graphixa for FedRAMP").

• Support SKUs: Sell enterprise support tiers that guarantee 24/7 uptime for mission-critical migration windows.

6. Content Strategy: "From Packet to Policy"

• Technical Whitepapers: "Why Property Graphs Fail where Triple Stores Succeed in Migration Governance."

• Interactive Demos: Host a "Migration Sandbox" where users can upload a small PCAP file and see Graphixa convert it into a semantic triple map in real-time.

• Community Webinars: Focus on "Ontology-First Engineering"—teaching architects how to build migrations that are resilient to schema changes.

Strategic Marketing Slogan Idea:

"Graphixa.ai: Open Source Governance. Semantic Certainty."