ArcXA intelligence engine

Designed to move partners from AI experimentation to production-ready execution by solving the "dirty data" and "fragmented systems" problems that typically stall AI projects.

ACS Proposes: E quitus.ai ArcXA Data Governance Management (DGM) - based on Triple Store Architecture =  Knowledge Graph Neural Network ( KGNN)  platform: which acts as a high-performance "intelligence engine" for TD SYNNEX Destination AI users. 

ArcXA specifically benefits TD SYNNEX users across the three pillars of migration, integration, and governance:

Start your free Migration Readiness Assessment, at AIMLUX.ai Consulting Services (ACS) 

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1. Accelerated Migration: From Legacy to AI-Ready

Migration is often the biggest bottleneck in AI adoption. ArcXA simplifies this by removing the need for massive, manual data overhauls.

Zero-ETL Approach: Unlike traditional migrations that require complex “Extract, Transform, Load” (ETL) pipelines, ArcXA automatically ingests and structures data from legacy systems.

• Mapping users to migrate the intelligence of their data without necessarily moving every raw byte into a new cloud silo.

• Rapid Deployment (IOC in 30 Days): Equitus guarantees an Initial Operational Capability (IOC) within 30 days.

• For TD SYNNEX partners, this significantly shortens the sales cycle and allows them to demonstrate ROI to end customers much faster than traditional 6-12 month AI implementations.

• Hardware Agnostic: ArcXA can run on-premises (optimized for IBM Power10 or Dell servers), in the cloud, or in hybrid environments, allowing users to migrate at their own pace without being "locked in" to a specific infrastructure.

2. Seamless Integration: Unifying the Data Fabric

TD SYNNEX Destination AI program focuses on "Outcome-Based" AI. ArcXA facilitates this by acting as the glue between disparate data sources.

• Automated Knowledge Graphs: ArcXA creates a Semantic Layer that connects siloed data sets (structured and unstructured).It automatically discovers relationships between individuals, entities, and events across different platforms.

• Interoperability: It is built on an open architecture that integrates with existing Active Directory, S3 buckets, databases, and application stacks.

• For a TD SYNNEX reseller, this means they can offer a solution that works "out of the box" with a customer's current IT ecosystem.

• Edge to Enterprise: It allows for the integration of real-time data—such as video feeds via Equitus Video Sentinel (EVS) —directly into the business intelligence workflow, providing a truly unified view of operations.

3. Robust Governance: Traceability and Trust

Governance is a core pillar of the Destination AI program.ArcXA addresses the "Black Box" problem of AI by providing a transparent framework.

Data Provenance: ArcXA maintains strict data lineage.

• Users can trace any AI-generated insight back to its original source, ensuring auditability—a critical requirement for government, defense, and highly regulated industries.

• Explainable AI (XAI): Because it uses Knowledge Graphs rather than just probabilistic models, the logic behind the AI's conclusions is explainable.

• This reduces the risk of "hallucinations" and increases executive confidence.

• On-Premises Sovereignty: For users with high security requirements, ArcXA can run entirely behind a firewall without a cloud connection. This ensures complete data sovereignty and compliance with strict governance standards like GDPR, CJIS, or HIPAA.

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Summary Table: ArcXA for Destination AI Users

Feature	User Benefit	Impact on AI Maturity
KGNN Automation	Eliminates manual data prep and ontology building.	Moves users from “Aware” to “Ready” faster.
Open Architecture	Connects to any existing database or S3 bucket.	Simplifies Integration of new AI tools.
Deterministic Logic	Provides clear provenance and explainability.	Enhances Governance and reduces risk.
COTS Deployment	Fully operational (FOC) in 60 days.	Accelerates Migration and time-to-value.

 Pro-Tip for Partners: When using the Destination AI Solution Grid , ArcXA should be positioned as the "Foundational Data Layer" for customers who have fragmented data or high security requirements that prevent them from using public cloud-only AI services.

How far along is your current AI practice—are you currently in the assessment phase, or are you ready to start mapping out specific vendor integrations?

Subject	Predicate	Object
Credit_Model_v2	usesFeatures	Income_Data
Income_Data	hasSource	HR_Database_Cloud
Income_Data	containsPII	True
Credit_Model_v2	approvedBy	Compliance Officer Bob

Migration Complexity

 

How complex is the current data architecture you're looking to migrate?

ACS Proposes: CloudLake Intelligent Integration Layer (IIL) Utilizing ArcXA Mapping functions as a semantic orchestration layer that bridges the gap between technical infrastructure and business logic. 

 ArcXA governance integration combines high-performance storage and compute platforms, ensures that data definitions, security protocols, and relationships remain consistent throughout the migration lifecycle.

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1. Enhancing Migration Mapping – Ingestion Layer (The “Multi-Cloud” Surface;

ArcXA streamlines the transition from legacy systems to modern cloud warehouses by providing a unified semantic framework.

• Semantic Alignment (Snowflake & BigQuery): Instead of simple schema copying, ArcXA identifies business-critical metrics and dimensions. This prevents “lost in translation” errors when moving from legacy SQL dialects to Snowflake’s Iceberg tables or BigQuery’s BigLake managed tables.

• Automated Logic Conversion (Databricks & Azure Synapse): ArcXA assists in mapping complex Databricks Spark data types or Azure Synapse T-SQL stored procedures to their target equivalents, ensuring precision—such as correctly mapping 64-bit LongTypeto the appropriate integer scale in a new environment.

• Federated Interoperability (Dremio & Starburst): For platforms like Dremio or Starburst that query across multiple sources, ArcXA provides a "single source of truth." This allows teams to map data from disparate silos without needing to physically consolidate it first, significantly accelerating the planning phase.

2. Post-Migration Issue Resolution (PMIR) Diagnostic Mapping

Post migration, ArcXA acts as a diagnostic tool to identify and resolve performance and integrity gaps.

• Deep-Link Disconnect Identification: Using its relationship-mapping capabilities, ArcXA can detect broken deep-links in a Knowledge Graph Neural Network ( KGNN ) structure. If a migration to Azure Synapse breaks a connection to a specific data mart, ArcXA flags the semantic "orphan".

• Performance Baseline Comparison: ArcXA tracks transactional core speeds and query response times. If Snowflake or Databricks performance fluctuates more than 5% compared to pre-migration baselines, ArcXA helps isolate whether the issue is a configuration error or a semantic logic break.

• Security & ICAM Synchronization: Post-migration, it verifies that Identity and Access Management (ICAM) levels—such as Azure AD roles—are correctly mapped to the new architecture, ensuring no "leakage" or unauthorized access occurs in hybrid or cloud environments.

3. Value-Add by Platform [  Snowflake, Databricks, BigQuery, Azure Synapse, Dremio / Starburst]

Platform	Primary Value of ArcXA Connection
Snowflake	Standardizes fragmented definitions via the Open Semantic Interchange (OSI).
Databricks	Converts complex Spark logic into governed business metrics for AI/BI Genie consumers.
BigQuery	Synchronizes manifest statistics for Iceberg tables to ensure read/write consistency.
Azure Synapse	Re-engineers physical distribution clauses eg, ROUND_ROBIN) into automated cloud storage.
Dremio / Starburst	Provides a virtualized semantic layer to query migrated and legacy data side-by-side during transition.