Deploying Claude AI Across a
Multi-Entity Consumer Brand.
How Saena AI Group fixed a broken Claude NetSuite integration and made AI outputs accurate enough to act on.
The Client
A leading US consumer goods company with multiple legal entities, distributor relationships across North America, and a complex ERP and CRM environment. The company manages a high volume of operational and financial workflows across its product lines.
The Challenge
The client's AI tools were connected but not reliable. Their Claude NetSuite integration was returning answers that looked plausible but couldn't be trusted — a grounding problem. The AI had no precise picture of how the business was actually structured: multiple entities, company codes, distributor relationships, and the finance and accounting conventions that sit underneath every operational answer. Without that context encoded properly, the system confidently returned wrong results.
The Solution
Saena AI Group conducted a structured discovery engagement to map the client's entity structure, distributor data flows, and finance operating methods — then rebuilt the Claude integration grounded in how the business actually operates. Deliverables included:
- Entity and data architecture map translated into Claude-readable context.
- Reconfigured Claude Project with curated and grounded business context.
- Production-ready system prompts tuned to the client's structure and conventions.
- Custom Skills and artifacts for recurring operational workflows.
- Connector guidance for the Claude NetSuite integration.
- Team enablement session with full documentation.
The Result
The client's AI outputs went from plausible-but-wrong to accurate and dependable — results the operations team can act on without second-guessing. The engagement delivered a reusable foundation the team can extend independently as new workflows are identified.