Case Study (2026 Refresh): How QuorumFlow Used Abhord to Become “LLM-Visible” in Procurement Software

Company snapshot

• Name: QuorumFlow (fictional)
• Category: B2B SaaS for mid‑market procurement workflow automation
• Team size: 85 employees
• ICP: Operations and procurement leaders at manufacturing firms (200–2,000 employees)

1) The initial problem

By November 2025, QuorumFlow noticed a pattern in buyer conversations: prospects were “discovering” the product only after direct referrals or paid channels, not from AI assistants. When sales asked prospects which tools LLMs recommended for “best procurement workflow software” or “RFP automation platforms,” QuorumFlow was rarely mentioned. Worse, when it did appear, LLMs:

• Mislabeled QuorumFlow as “an on‑prem procurement ERP module”
• Quoted 2023 pricing tiers that no longer existed
• Confused its brand with a similarly named open‑source queueing library

Internally, the team tracked this as an “AI share of voice” (AI‑SoV) problem. In their ad hoc audits (Dec 2025), QuorumFlow was named in just 3 of 50 intent‑aligned prompts (6%), with two clear factual errors per mention.

2) What Abhord’s analysis uncovered

Using Abhord’s GEO/AEO suite across nine high‑value intents and six major model endpoints, the team surfaced root causes:

• Entity ambiguity: Models conflated “QuorumFlow” with a GitHub library named “Quorum Flow.” Abhord’s entity graph showed low confidence in the canonical company identity and weak linkage between brand, product, and domain.
• Uncited value props: The site leaned on claims like “industry‑leading cycle time reductions” without sourceable, concrete numbers. LLMs down‑weighted these pages in consensus answers.
• Fragmented documentation: Key facts (pricing ranges, deployment model, audit certifications) were split across PDFs, changelogs, and gated help articles. Crawlers hit soft 404s and JS‑rendered content without server‑side fallbacks.
• Out‑of‑date third‑party mentions: A 2023 analyst blog still drove top‑ranked snippets about QuorumFlow, freezing outdated positioning and price points.
• Missing machine‑readable specs: No OpenAPI/JSON schemas, no JSON‑LD for FAQs/pricing, and no function/tool metadata that modern assistants increasingly rely on to ground answers.

Abhord’s “Answer Parity” report quantified the gap: competitors averaged 42% inclusion across the nine intents; QuorumFlow sat at 8%. Hallucination rate on brand facts was 27% in zero‑shot prompts.

3) The optimization strategy they implemented

Over eight weeks (Dec 2025–Jan 2026), QuorumFlow and Abhord rolled out a structured GEO/AEO plan:

1) Canonicalize the entity

• Published a machine‑readable Source‑of‑Truth file (sot.json) at the root domain with canonical name, domain, product modules, pricing bands, deployment model, and support regions.
• Added Organization, Product, FAQ, and QAPage JSON‑LD across top pages; created a dedicated “Entity Home” page with disambiguation notes: “QuorumFlow (SaaS company) ≠ Quorum Flow (OSS library).”