Sycomp, an SAP HANA → Snowflake migration is the ultimate "high-stakes" play. Using Equitus.ai ARCXA alongside this migration transforms a risky technical move into a high-value AI Governance project.
The combination of Triple Store Architecture and Neural Network Exchange (NNX) allows Sycomp to provide "Smart Provenance"—proving not just that the data moved, but what it means and who changed it.
1. The Value of Triple Store (Subject-Predicate-Object)
Traditional SAP migrations lose "context" when data is flattened into Snowflake tables. ARCXA preserves this context by converting every data point into a Triple:
Subject:
SAP_Invoice_1001Predicate:
is_billed_toObject:
Customer_Global_ID_55Benefit: In Snowflake, this looks like two IDs in a row. In ARCXA’s Triple Store, it is a permanent, searchable relationship. If a user queries Snowflake and gets a weird result, they can use ARCXA to see the Predicate (the logic) that connected those two entities in the first place.
2. NNX (Neural Network Exchange): Lineage & Provenance
NNX is the "DNA tracker" of your data. It provides a level of lineage that tools like Informatica or Fivetran simply cannot reach.
Automated Lineage: NNX automatically generates a "Map of Truth" as data flows from HANA to Snowflake. It captures metadata at the point of ingestion, ensuring that every record in Snowflake has a "Birth Certificate" from SAP.
Provenance: It tracks the influence. If an AI model in Snowflake uses this data, NNX records which SAP user originally entered the data and which transformation script touched it. This is "Explainable AI" at the data layer.
3. Adding Value with Human-in-the-Loop (HITL)
Migrations are never 100% clean—SAP data is notoriously "messy." This is where HITL turns a technical hurdle into a consulting opportunity for Sycomp:
Semantic Conflict Resolution: When ARCXA’s Intelligent Ingestion System (IIS) finds two conflicting definitions of a "Customer" between SAP and Snowflake, it doesn't just fail. It triggers a HITL workflow.
Expert Validation: A Sycomp data steward or the customer’s business owner is presented with the conflict. Their decision (e.g., "Use SAP definition as the Master") is then fed back into the Knowledge Graph as a new triple.
Continuous Learning: The system learns from the human decision. The next time a similar conflict occurs, ARCXA suggests the fix based on previous human input, accelerating the migration and cleaning the "SQL Jungle" in real-time.
AIMLUX core positioning thesis
Sycomp wins the infrastructure contract — the lift-and-shift, the SAP Basis work, the IBM Power migration. What they historically leave on the table is the data intelligence layer: proving that what landed in Snowflake or Databricks is semantically equivalent to what left SAP HANA, and being able to show the regulator, the data governance team, or the business owner exactly how every field got there. That gap is precisely where Equitus.ai lives.
What each ARCXA layer does in the deal
ARCXA's connector registry is the opening wedge. SAP HANA, DB2, Oracle, Snowflake, and Databricks are all in the registry — meaning Sycomp's standard source/target combinations are natively supported on day one. No custom connector build, no scoping risk. ARCXA profiles the SAP schema automatically: it identifies MARA, EKKO, VBAK tables, infers semantic types, detects domain patterns like material numbers and cost centers, and produces a structured asset inventory before a single row moves.
NNX lineage captures the transformation graph at field resolution. Every derivation — a calculated column, a type cast, a unit conversion from SAP's internal format — becomes a node in the lineage graph. This is the artifact that makes Sycomp's delivery defensible: when the CFO asks "where does this revenue figure come from," the answer is a traversable graph, not a PDF written by the SI team.
The triple store is what makes this different from every other lineage tool. Instead of a proprietary lineage database, every relationship is expressed as a subject-predicate-object assertion — VBRP.NETWR → aggregated_by → DIM_REVENUE.NET_AMOUNT — stored as a queryable knowledge graph. This means lineage is composable with governance policies, business glossaries, and regulatory frameworks. It can be queried with SPARQL, federated across systems, and extended without touching the ingestion code.
Where HITL creates disproportionate value
This is the real differentiator in the Sycomp pitch. SAP schemas are notoriously ambiguous. The same field name appears in 40 tables with different semantics. Business rules are encoded in ABAP custom code, not in the schema. When ARCXA's semantic mapping encounters a conflict — two candidate target columns for the same source field, an ambiguous unit of measure, a business rule that has no structural equivalent in Snowflake — it surfaces that decision to a human reviewer rather than silently picking one.
Critically, the HITL decision doesn't disappear into a ticket system. It writes back into the triple store as a provenance assertion: MARA.MEINS → unit_normalized_by → [data steward: Jane Kim, 2025-11-03, rationale: "SAP internal UOM code mapped to ISO standard per Finance governance policy"]. That assertion is now part of the permanent lineage record. The migration is not just complete — it is explained, auditable, and defensible to any future auditor or data governance review.
For Sycomp, this turns a migration delivery into a managed data governance engagement. The HITL layer is the mechanism by which the customer's SAP subject matter experts contribute institutional knowledge that no AI can infer from metadata alone, and that knowledge becomes a permanent asset in the triple store rather than tribal memory.
The flagship deal structure
The SAP HANA → Snowflake migration with full lineage and semantic mapping is not just a technical win — it is a three-phase commercial motion. Phase one is the ARCXA ingestion and profiling engagement alongside Sycomp's infrastructure work. Phase two is the NNX lineage and triple store build, where every transformation is captured and the semantic map is validated through HITL review sessions with the customer's data stewards. Phase three is the governance layer handoff: a populated data catalog, a queryable provenance graph, and audit-ready lineage documentation that the customer owns and can extend.
Sycomp brings the SAP relationship and the infrastructure credibility. Equitus.ai brings the data intelligence layer that makes the migration defensible, extensible, and valuable long after the cutover. That is a joint go-to-market story, not just a tool handoff.
