Service vertical — AIO/GEO · AI Search Visibility
Improve how Google AI Overviews, AI Mode, ChatGPT, Perplexity, Gemini, Claude, and Copilot discover, understand, verify, and recommend your company.
Built on search infrastructure, not GEO hacks. We improve the systems AI retrieval depends on: technical SEO, crawlability, entity clarity, expert content, structured evidence, internal linking, and conversion automation.
Why this matters now
Google AI features rely on core Search systems: indexed pages, crawlable architecture, snippet eligibility, and high-quality content. Other AI systems apply comparable trust and retrieval logic. We optimize the shared foundation first, then add AI-specific monitoring and operational controls so visibility is measurable and repeatable.
How we do it
Most GEO agencies sell content volume. That isn't enough. We run technical SEO, entity clarity, structured data, and evidence-oriented content as one workflow. Every engagement follows the same eight steps with a named owner and a shipped artifact at each stage.
STEP 01
Outcome
Definitive list of the 30–60 prompts that decide your category
We work backwards from the buyer. Which exact prompts do your prospects type into ChatGPT, Perplexity, Gemini, and Claude when they have the problem you solve? We map intent, decision stage, and language (English / Russian where it matters) so every later step optimizes against a real prompt, not a guessed keyword.
STEP 02
Outcome
Side-by-side scoreboard of who gets cited today, and why
We run every mapped prompt through the four major engines and record the cited sources, citation order, and the structural reason each one is winning. The output isn't a vibes report — it's a delta document showing exactly which schema, which author bios, and which crawler signals your cited competitors have that you don't.
STEP 03
Outcome
An entity graph the LLMs can actually traverse
Most sites have schema, but it's disconnected — an Article that doesn't link to a Person who doesn't link to an Organization. We rebuild the entity chain end-to-end so any article on your site is traceable to a credentialed author at a real firm with verified sameAs links into LinkedIn, Wikidata, and (where applicable) the bar registry or industry register.
STEP 04
Outcome
Article / FAQ / HowTo / Service schema across the content library
We deploy the right schema types at the right scale — Article + BlogPosting on every post, FAQPage on Q&A blocks, HowTo on tutorials, Service / LegalService / MedicalBusiness where the firm type warrants it. JSON-LD, server-rendered, validated against Schema.org and Google's Rich Results test before it ships.
STEP 05
Outcome
1–5 long-form pillars that anchor every citation
Comprehensive pages give search and AI systems more verifiable context, especially when claims are supported by clear sections, internal links, visible evidence, and structured data. We build authority pillar pages (4,000–10,000 words each) that comprehensively cover the highest-value queries in your category. Each pillar follows the direct-answer-first structure, lifts every claim into a citable paragraph, and is wired into the entity graph as the canonical source.
STEP 06
Outcome
Important pages are crawlable, indexable, and snippet-eligible
We verify crawlability, indexing eligibility, canonical consistency, internal linking, and snippet readiness on the pages that matter commercially. We review robots directives, sitemap quality, and crawler access for relevant systems. Optional AI-readable files can be added for non-Google systems, but they are treated as supporting assets, not as a Google ranking requirement.
STEP 07
Outcome
Monthly dashboard showing where you stand in every engine
Every month we re-run the full prompt set across all four engines, record citation rate, mention rate, average rank when cited, and competitor citation share. You see exactly which prompts moved, which engines responded fastest, and which content asset is driving the lift. No black-box reports.
STEP 08
Outcome
AI-driven traffic captured into a process, not a contact form
Citation alone is awareness — it has to convert. We wire the AI-driven traffic into the same process infrastructure we build for our automation clients: enriched lead intake, CRM routing, follow-up sequences. Visibility and automation, working as one engine instead of two disconnected projects.
Steps 1–6 form the foundation phase (typically weeks 1–8). Steps 7–8 are the recurring monthly operation. Every step has a shipped artifact you can verify — not a deck, an actual file in your repo or your CRM.
Compliance stance
We do not treat AI visibility as a hack layer. The work is built on technical SEO, crawlability, indexability, internal linking, structured data that matches visible content, and expert-led pages that can be verified and trusted.
Indexed and snippet-eligible pages for commercial intents
Crawlability and canonical consistency on key templates
Structured data aligned with visible on-page claims
Entity clarity across Organization, Person, Service, and Article
Evidence-led content architecture across services, case studies, and blog
Visibility connected to CRM automation and follow-up operations
Guardrails
No fake mentions or synthetic reputation schemes
No hidden or misleading schema
No mass AI spam pages
No keyword stuffing for long-tail permutations
No llms.txt-as-magic positioning
No generic blog farms without first-hand evidence
No mass pages for every query variation
We publish what can be defended with visible evidence. See related pages: Services, CRM Automation, Automated Reporting Systems, Lead Management Automation, Case Studies, Blog.
The differentiator
Most AI/GEO agencies stop at the citation. They leave visibility traffic to land in a contact form and call it a day. Because Profitec AI is wired into automation, the visibility we earn for clients is connected to the same operational infrastructure we build for our automation engagements — lead intake, enrichment, CRM routing, follow-up sequences, and monthly reporting.
Stage 01 · Visibility layer
ChatGPT, Perplexity, Gemini, Claude, Copilot, and Google AI Overviews recommend you for the prompts buyers actually use.
Stage 02 · Bridge layer
AI-driven traffic flows into enriched lead intake — not a generic contact form. Every prospect arrives with firmographic + behavioral context attached.
Stage 03 · Operations layer
CRM routing, automated follow-up sequences, dashboards. The visibility becomes pipeline, not vanity metrics.
See our core automation services for how the operations layer is built — the same engineering team that ships the AIO/GEO foundation builds the CRM, reporting, and follow-up automations.
Platforms monitored
Citation rate, mention rate, and competitor share recorded across each engine. Crawler access verified, fetch logs reviewed, factual-error flags fired when an engine describes you incorrectly.
ChatGPT
GPTBot
OpenAI search index + browse
Perplexity
PerplexityBot
Own crawler, fast re-index
Gemini
Google-Extended
Google's generative surface
Claude
ClaudeBot
Anthropic crawler, growing share
Copilot
Bingbot
Microsoft surface, Bing index
AI Overviews
Googlebot
Google AIO, fastest growth
See the live AI Visibility Dashboard for the operational view that ships with every engagement.
Deliverables
Engagement tiers
Single-language practice, focused query set
Larger content library, broader query set
Multilingual market, deep query coverage
Each engagement is scoped to your practice. We map the right tier on the discovery call — usually after a baseline audit so the recommendation is grounded in what your current visibility looks like, not in what we’d like to sell you.
Proof
Case Study / 03 — Fershteyn Law
Full teardown of the audit, schema deployment, E-E-A-T signaling, and the bilingual market insight that drove the strategy.
Timeline
Time to First Visibility
8 weeks
Full indexation and first AI citations begin appearing across ChatGPT, Perplexity, Gemini, and Claude.
Time to Sustained Growth
1–12 months
Compounding citation volume and ranking authority across queries — measured monthly with citation-rate, mention-rate, and competitor share.
Week-by-week breakdown
W 1
Discovery + scope
30-minute call. Practice areas, target queries, and engines confirmed.
W 2–3
Baseline audit
30 query patterns logged across 3 engines. Competitor structural gaps surfaced.
W 4–6
Schema + infrastructure
BlogPosting / Article schema deployed at scale. LegalService and Person entities wired.
W 7–8
Signaling + first pillar
E-E-A-T author bios, technical accessibility checks, and the first authority pillar page.
M 2+
Monthly monitoring
Re-audit cadence, citation-rate tracking, query expansion, competitor monitoring.
Common questions
For Google AI Overviews and AI Mode, foundational SEO remains the base: indexing eligibility, crawlability, snippet readiness, quality content, internal links, and strong page experience. What we add is an AI-visibility operating layer on top of that foundation: prompt-level monitoring, entity clarity improvements, structured evidence, and conversion integration into CRM workflows.
Usually the work supports organic performance because it improves technical quality, information architecture, and content clarity. We don't treat AI visibility as a replacement for SEO; we treat it as SEO-grade infrastructure extended to AI search surfaces.
We track citation rate, mention rate, and competitor citation share across a stable prompt set, then connect those visibility signals to lead flow, CRM routing, and follow-up outcomes. Visibility metrics are useful, but the commercial metric is whether visibility becomes qualified pipeline.
Yes — and the Fershteyn case study shows it's often where the biggest opportunity sits. Russian-language estate planning queries had ~80% less competition than English. We've seen the same asymmetry in Spanish and Portuguese markets. Bilingual authority pages are usually the highest-leverage move.
No. Google does not require llms.txt or special AI text files for AI Overviews/AI Mode visibility. We treat llms.txt as an optional supporting asset for non-Google systems and internal documentation, not as a Google ranking prerequisite.
Profitec AI is an AI automation company. AIO and GEO are one service vertical inside that broader automation and growth infrastructure model. We connect AI search visibility with CRM automation, lead handling, reporting, follow-up systems, and internal process automation so visibility and operations run as one engine.
Yes. We provide AI search visibility services for B2B companies in Israel, North America, Europe, and the UK. The work includes AI visibility audits, technical SEO and crawlability checks, schema deployment, entity optimization, structured content, citation tracking, and competitor monitoring across ChatGPT, Perplexity, Gemini, Claude, Copilot, and Google AI Overviews. Bilingual coverage (English + Russian) is available where it materially improves outcomes.
A 30-minute fit call. We discuss your practice, the queries that drive consultations, and where you currently stand. If we both want to move forward, the Lite tier is usually the right starting shape — fixed setup, fixed monthly, and the audit ships within the first three weeks.
We'll run a 30-query baseline audit on Gemini, Perplexity, and ChatGPT for your practice area, and report exactly what your cited competitors have that you don't. 15-minute fit call to scope it.