How Zaillor helped an India-based B2B SaaS provider become more visible in AI-generated software recommendations

Result snapshot

About the business

An India-based B2B SaaS provider whose buyers compare use-case fit, features, integrations, implementation effort, security and support before deciding which software to evaluate.

Client identity has been withheld for confidentiality. Results are based on Zaillor's recorded monitoring of the same fixed prompts across ChatGPT, Claude and Gemini during the stated engagement period.

What AI SEO meant in this engagement

For this engagement, AI SEO meant making the company's category, solutions, customer use cases and locations clear enough for answer engines to connect them with real B2B software questions. Traditional SEO helps pages appear in link-based search. AI SEO adds the work of making a business understandable in answer-based search. The two work together.

The challenge

Software discovery is increasingly shaped by questions about fit, implementation and risk. A SaaS provider can have a capable product and still be absent from, inaccurately described in or weakly sourced by AI-generated recommendations. The practical question was whether a prospective buyer asking an AI system for software in a relevant category would find the company with the right use-case description, evidence and source. At baseline, engagement week 0, the company appeared in 6 of 20 fixed prompts (30.0%), while 14 of 60 engine responses (23.3%) returned a mention. The practical goal was to make the company easier to understand across the different situations it serves, not to chase one keyword.

The AI SEO approach

Start with real questions

We mapped 20 commercially relevant B2B software questions covering software category discovery, use-case and workflow fit, integrations and implementation, security and buyer questions, and software alternatives, then used the same fixed prompts for baseline and follow-up measurement.

Make the business easier to understand

Technical work covered full-site crawlability, robots.txt, XML sitemap and llms.txt review, plus page-level content and schema improvements across priority solution, use-case and integration pages. Relevant Organization, WebSite, WebPage, BreadcrumbList, SoftwareApplication and Service markup was strengthened where applicable, with the company's solution architecture kept in view.

Keep learning from the answers

We re-ran the same prompts across ChatGPT, Claude and Gemini through engagement week 12, applying the same binary mention rule. Monitoring covered category, competitor and multi-region queries. Citation work included an audit, cleanup of inconsistent listings and submissions to agreed software and industry directories. Zaillor also prepared AI-optimised authority content around software categories, workflows, integrations, implementation and security, reported weekly and supported paid PR placements through ANI and other major Indian media channels. PR was treated as authority support, not as proof of ranking or guaranteed citation.

What changed by engagement week 12

Weekly diagnostic view for India, 15 Jun – 31 Aug 2026. Each point shows the percentage of monitored AI responses that mention the business; it complements the fixed-prompt summary below.

We treated monitoring as a recall-style test: the same 20 fixed prompts were asked across the same three AI engines, producing 60 engine responses in each window. A positive result means the company was named somewhere in the generated answer. The measurement does not assess ranking position, sentiment, citation quality or conversion impact.

Example prompts from the latest monitoring window

Examples shown from the 31 August 2026 India monitoring window. They illustrate individual engine responses; the headline results use the full fixed prompt set.

Why this matters to a business

An AI answer is often a decision shortcut. If a business is missing when a relevant question is asked, it may never reach the customer's shortlist. More complete and consistent information gives the business a better chance of being considered for the moments it actually serves. That is the role of Zaillor's AI SEO implementation: connect what a company does to the questions people ask, strengthen the information answer engines rely on and measure whether that connection is improving. For this B2B software business, that means being easier to find when someone asks about business buyers comparing software categories, use cases, integrations, implementation and security.

The next iteration can prioritise more specific integration, procurement, security and implementation prompts, where software buyers need deeper evidence before moving to evaluation.

Improve how your business appears in AI search

Zaillor helps teams measure, improve and monitor how their businesses are represented in AI-generated answers.