The twelve questions buying committees ask about firms like yours — and partners ask about AI-era visibility — each answered in a form worth quoting.
How do B2B buyers shortlist vendors in India now?
A committee longlists before any vendor is contacted — from prior experience, peer references, and increasingly from AI-assisted research. By the time an RFP or enquiry goes out, the field is largely set. Being present in that first AI-assembled answer decides whether your firm enters the evaluation at all.
Do procurement teams really use ChatGPT to find vendors?
Increasingly, yes — for longlists, background checks and comparison summaries, before the formal process begins. The RFP still runs traditionally; the names inside it are pre-shaped by what AI research surfaced. Firms visible at that early, invisible stage enter more evaluations than firms whose public evidence is thin.
How does AI decide which firms to name for "top consultants in India"?
From public evidence, weighed for confidence: a clearly stated specialisation, consistency between your website and every directory, independent corroboration from third-party sources, depth of published material, and recency. Firms strong on all five get named; firms weak on any get hedged or omitted. Scale alone does not decide it.
Why is my competitor named by AI and my firm is not?
Almost always: they are better documented, not better at the work. Published thinking, consistent profiles, third-party mentions and current pages give a system the material to name them confidently. The fix is not imitation — it is building your own record of evidence deliberately, where theirs grew by accident.
What should a consulting firm publish to become visible to AI?
Four things: a precise positioning statement used identically everywhere; service pages that answer real procurement questions rather than describing values; published thinking that demonstrates the expertise you sell; and corroborated capability facts — sectors, scale, methods — on independent platforms. Volume matters far less than consistency and specificity.
Our case studies are under NDA. Can we still build AI visibility?
Yes. What AI systems need is capability evidence, not client names: anonymised engagement patterns, sector experience, methodology, team credentials and scale indicators are all publishable without touching a confidentiality clause. Most B2B firms have years of this material sitting unwritten — the NDA was never the real obstacle.
How long does it take a B2B firm to see movement in AI answers?
Descriptive queries — "tell me about this firm" — usually improve within two to three months of published, corroborated evidence. Competitive shortlist queries take longer, because you are displacing incumbents. ProminAI baselines your questions at the start and re-runs them monthly, so movement is recorded and dated — never asserted.
Is this different from hiring a PR agency?
Different job. PR earns press coverage and relationships, typically at ₹75,000–₹3,00,000 a month. ProminAI builds the machine-readable evidence layer — positioning, published articles, verified mentions, entity consistency — and monitors what AI actually answers, with per-link proof. Some firms run both; only one is designed for AI answers.
What does AI visibility cost for a B2B services firm?
Momentum, the plan most B2B firms choose, is ₹39,999 + GST for three months — three authority articles, thirty-plus verified mentions, monthly monitoring of up to forty procurement questions and competitor tracking. Against engagement values of ₹1,00,000–₹25,00,000, entering one additional evaluation typically returns the fee several times over.
We sell in a narrow niche. Does AI visibility matter there?
Niches are where it works fastest. Fewer firms contest a specific query — "ERP partners for mid-size pharma manufacturers" — so a documented specialist can become the consistent answer in months. Broad categories take longer and favour incumbents. If your niche has a phrase buyers type, that phrase is winnable.
Do Clutch, GoodFirms and directory profiles help with AI answers?
They help as corroboration — independent sources agreeing with your own description — and they hurt when they contradict it: an old headcount, a dropped service line, a stale city list. ProminAI's audit finds every listing that describes your firm, and the fix-list brings them into word-for-word agreement.
How do we measure whether any of this works?
Three instruments: a baseline audit recording what AI answered on day one across your real procurement questions; monthly re-runs of the same questions with dated results; and the portal, where every article and mention is logged with a live link. You compare baseline to now — the evidence is checkable, not narrated.