Case Study (Refreshed 2026): How Opscribe Lifted Its AI Visibility with Abhord
Company snapshot
- Name: Opscribe (fictional)
- Category: B2B SaaS for regulated SOP documentation and change-control
- ICP: Mid-market life sciences and fintech ops teams (100–1,500 employees)
- Stack: Public docs + knowledge base, SOC 2 portal, integrations with Jira, ServiceNow, and Vanta
1) The initial problem
By September 2025, Opscribe’s brand was largely invisible to major LLMs. In head-to-head prompts like “best SOP software for pharma” or “alternatives to [competitor],” the models:
- Omitted Opscribe entirely in 7/10 runs
- Confused it with consumer note-taking tools and with a similarly named open-source project
- Repeated outdated claims (e.g., “no Jira integration,” retired in 2023)
Internally, Opscribe saw a mismatch: organic web traffic was steady, but demo requests attributed to generative answers were negligible. Sales heard prospects say, “We asked an AI which vendors to shortlist—you didn’t show up.”
2) What Abhord’s analysis uncovered
Using Abhord’s GEO/AEO toolset, Opscribe ran a 3-week baseline in October 2025 across six popular LLMs and four answer engines. Key findings:
- Entity ambiguity: Models collapsed “Opscribe” into unrelated brands with overlapping tokens (“scribe,” “scribehow,” a medical dictation app). Abhord’s Entity Diff showed 38% of mentions were misattributed.
- Sparse authoritative corroboration: High-quality third-party references (analyst notes, compliance directories, integration marketplaces) were either missing or buried. Evidence clusters were shallow, with only 1–2 corroborating nodes per core claim.
- Stale facts in model memory: Pricing, integrations, and certifications last-seen dates were 8–18 months old in several indices. Freshness scoring penalized the brand on “regulated” queries.
- Unfriendly structure for machines: The docs site blocked some crawler classes via robots.txt, lacked product-level JSON-LD, and buried canonical facts inside images and PDFs without alt text.
- Intent mismatch: The content emphasized “SOP authoring,” while high-intent prompts in the category skewed to “change control,” “21 CFR Part 11,” and “audit trails.” Abhord’s Intent Map showed a 0.41 coverage score for those terms.