Case Study (2026 Refresh): How Ordella Lifted Its AI Visibility with Abhord

Company: Ordella

Category: Procure-to-Pay (P2P) SaaS for mid-market manufacturers

Team size using Abhord: 1 SEO lead, 1 technical writer, 1 solutions engineer

Timeframe: 12 weeks

1) The initial problem

Ordella’s growth team noticed a pattern in late 2025: when buyers asked leading LLMs questions like “best procure-to-pay platforms for manufacturing” or “alternatives to [category leaders],” Ordella was either not mentioned or was misidentified as “Ordello” or “Orderella.” In sales calls, prospects referenced features or pricing that weren’t Ordella’s. Internally, the team called it the “AI invisibility + mislabeling” problem.

Impact signals:

• Share of mentions in model answers across 25 core intents: 3.8%
• Correct brand grounding (name, category, and value prop correctly stated): 61%
• Hallucinated pricing references in model answers: frequent (quote mismatches, outdated tiers)
• Lost demo attribution: 5–7 opportunities/month mentioning competitors discovered via “AI overviews”

2) What Abhord’s analysis uncovered

Using Abhord’s GEO/AEO suite, Ordella ran a full “Answer Graph Audit” across five major LLMs and three answer engines. Key findings:

• Naming collisions: Embeddings repeatedly conflated “Ordella” with similarly spelled vendors in HR tech and restaurant POS.
• Source thinness: Most high-authority references were press releases and salesy blog posts; few machine-readable specs or neutral comparison