About RANKARA
When clients ask ChatGPT or Perplexity to find a financial advisor, physician, or attorney, they get a list of specific people — not a page of blue links. RANKARA exists to make sure the right people are on that list.
The mission
For decades, professional services organizations invested in websites, SEO, and advertising to help clients find their people. Those investments worked because search engines returned lists — and being ranked highly in a list meant being found.
AI platforms changed that. When someone asks ChatGPT “who is the best retirement planning advisor near me,” they do not get a list of links. They get a name. They get a recommendation. They get told to call a specific person.
That shift created a problem no existing marketing tool was built to solve — especially for enterprises with dozens or hundreds of individual practitioners, compliance requirements, and the need for centralized oversight of every piece of content that goes out under their brand.
RANKARA was built to solve that problem. A managed platform that checks citations, generates practitioner-level content, routes it through industry-specific compliance review, builds entity authority across the right directories, and gets smarter from every edit and every citation win — month after month.
Why existing tools fall short
AI citation is not a brand awareness problem. It is a practitioner-level entity problem. AI platforms do not cite firms — they cite specific people. A physician, an attorney, a financial advisor. By name, credentials, city, and specialty.
Citation monitoring tells you whether your practitioners appear. RANKARA tells you — and then generates the content, routes it through compliance, builds the entity authority, and measures the improvement.
Financial advisors, physicians, and attorneys cannot publish content without compliance review. A content agency hands off content. RANKARA routes every piece through an industry-specific review workflow with pre-screening, inline editing, and audit trail.
Manually tracking AI citations for 50 advisors across 4 platforms, generating personalized content for each one, and routing it through review is not a workflow — it is a full team. RANKARA automates the entire cycle.
AI platforms cite specific, locally-grounded content about individual people — their credentials, their specialty, their city, their clients. Firm-level marketing copy does not produce practitioner-level citations.
The approach
AI citation is not a problem you solve once. It is a presence you build and maintain — because AI platforms are constantly updating what they know, competitors are publishing content, and your practitioners are always expanding into new markets and specializations. RANKARA runs a complete intelligence and content cycle every month.
Citation checking across 4 platforms, 25+ scenarios, sentiment scoring, share of voice by category, competitor tracking, hallucination monitoring, directory verification, and NAP consistency — all computed and stored for instant dashboard viewing.
Articles, FAQ entries, GBP posts, and LinkedIn variations — generated in each practitioner’s own voice, targeting their highest-priority citation gaps, and built specifically to be extracted and cited by AI platforms. Answer-first structure, credential attribution, entity co-citation, 6 engineered citable passages per article.
Industry-specific pre-screen, reviewer feedback with AI-assisted revision, version tracking, diff view, and copy-to-clipboard on the finalized version. Every action logged. Review edits feed the learning loop automatically.
Schema markup, directory submissions, NAP consistency, review monitoring and response drafts — the signals that give AI platforms confidence in a practitioner’s identity before citing them.
Every auto-fix, compliance edit, reviewer feedback note, and citation win is recorded. Patterns flow back into next month’s generation — per practitioner, across the roster, and across the industry. The platform builds proprietary intelligence that compounds month over month.
Principles
RANKARA was designed for regulated industries from day one. Every feature accounts for the reality that content cannot publish without structured review, documentation, and audit trail.
Not vanity metrics. Citation count, weighted score, share of voice by category, sentiment trend, directory coverage — the numbers that reflect real-world AI platform behavior.
Every edit, every fix, every citation win is a learning opportunity. RANKARA is built to compound intelligence — so month 12 is meaningfully better than month 1.
AI platforms cite people. RANKARA is built around individual practitioners — their voice, their credentials, their city, their clients — not generic firm content.
Every enterprise client’s data is completely isolated. Compliance teams, marketing teams, and practitioners only see their own organization’s information. No exceptions.
Run frequency, content volume, compliance workflow, industry module, content types — all configurable per client. RANKARA adapts to how each organization works, not the other way around.
Request a demo and we will show you exactly where your practitioners stand across ChatGPT, Perplexity, and Google AI — and what it takes to close the gap.