Arobis AI
Pricing
- Model
- Custom
Summary
Your SaaS brand ranks on page one of Google, but when a buyer asks ChatGPT 'what's the best tool for X,' a competitor gets named and you don't — because Google rankings and AI citations are built on entirely different signals. Arobis AI is a managed optimization service that targets exactly that gap.
Arobis AI runs structured audits against real buyer prompts across ChatGPT, Gemini, Claude, and Perplexity, then restructures your content and entity signals so AI engines cite you instead of skipping you. The workflow moves through three stages: audit what AI surfaces about you, restructure content for semantic clarity, and build authority signals that AI models use to decide who gets recommended. This is a done-for-you service, not a software platform — there is no dashboard to log into, no API to wire up, and no self-service configuration. Teams that need real-time competitive monitoring or want to run their own prompt tests are dependent on Arobis to surface that data. Because pricing is custom and the service model is agency-style, iteration speed is tied to the engagement cadence, not your sprint cycle.
Bottom line: Pick Arobis AI if you are a B2B SaaS company that has solid SEO but is invisible in AI-generated answers and needs a structured service to fix that — plan for friction if your team expects to own the tooling, pull live Share of Voice data on demand, or iterate on content signals without waiting on a service engagement.
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Pros
Sign in to edit- Audits run against actual buyer prompts across ChatGPT, Gemini, Claude, and Perplexity simultaneously, so you see your real AI Share of Voice instead of inferring it from proxy metrics.
- Content restructuring targets semantic clarity and entity signals — the specific signals AI engines use to decide who gets cited — which means optimization effort is not wasted on factors that move Google rankings but have no effect on generative answers.
- Authority Engineering builds citation signals across the web, so your brand accumulates the external trust footprint that AI models weight when selecting sources rather than relying solely on on-site content.
- The service model handles the diagnostic and execution work, so marketing teams without in-house GEO expertise can close the AI visibility gap without hiring or retraining before the category is locked in.
- The free AI Visibility Audit provides a concrete baseline of where your brand surfaces across AI platforms before any engagement begins, so the decision to proceed is grounded in actual data rather than vendor claims.
Cons
Sign in to edit- There is no self-service dashboard or software platform — competitive Share of Voice data, prompt test results, and optimization progress are delivered through the service engagement, not pulled on demand. Teams that need to monitor AI visibility weekly on their own schedule cannot do that here.
- The service model ties iteration speed to engagement cadence. When a product launch or category shift requires rapid content signal updates, waiting on a service cycle is a hard constraint — not a workflow preference. Teams running high-frequency content experiments move to in-house GEO tooling or software platforms that let them push changes and measure AI response without an external dependency.
- No API and no self-hosted option means the service cannot be wired into an existing marketing data stack or analytics pipeline. Reporting lives inside the engagement, not inside your BI tools.
- The vendor site went live in early 2025, which means the track record, case study depth, and long-term citation durability of the optimization work are unproven at the scale and time horizon that enterprise procurement requires. Teams with rigorous vendor evaluation criteria will have limited third-party validation to reference.
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About
- Platforms
- Web-based SaaS platform
- API Available
- No
- Self-Hosted
- No
- Last Updated
- 2026-06-09T12:12:28.962Z
Best For
Who it's for
- SaaS companies seeking visibility in AI-generated answers
- B2B technology vendors transitioning to AI search era
- Demand generation and growth marketing teams
- CMOs and revenue leaders focused on high-intent buyer discovery
- Startups and enterprise brands competing in AI recommendation spaces
What it does well
- Improving brand visibility in ChatGPT and other generative AI answer engines
- Optimizing for AI-powered recommendation engines and answer platforms
- Building entity authority and trust signals for AI model citation
- Monitoring AI Share of Voice against competitors across multiple platforms
- Developing content strategy for AI-driven search discovery
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Frequently Asked Questions
- Is Arobis AI free?
- Arobis AI is a paid tool. No permanent free tier is offered.
- Is Arobis AI open source?
- No — Arobis AI is a closed-source tool. Source code is not publicly available.
- What platforms does Arobis AI support?
- Arobis AI is available on: Web-based SaaS platform.
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Curated lists that include this category
Arobis AI is a managed service targeting a specific problem: SaaS brands that have invested in traditional SEO but are absent from AI-generated answers on platforms like ChatGPT, Gemini, Claude, and Perplexity. The vendor describes a three-step workflow — AI Visibility Audit, Answer Optimization, and Authority Engineering — that first measures where a brand appears (or doesn’t) when real buyer prompts are run, then restructures content so AI engines can clearly parse what the company does, who it serves, and when to recommend it, and finally builds the entity footprint and citation signals that generative models use to select sources.
The differentiating claim is focus: Arobis AI positions itself against traditional SEO firms that optimize for click-through and rankings, arguing those metrics are decoupled from AI recommendation logic. The vendor states the system is built specifically for Answer Engine Optimization (AEO) and Generative Engine Optimization (GEO) — a framing that prioritizes being selected in a generated answer over appearing in a ranked list. The approach centers on semantic relevance, entity authority, and structured content signals rather than keyword density or backlink volume.
This service fits B2B SaaS demand generation and growth marketing teams that have budget for managed optimization and want an external team to diagnose and close the AI visibility gap. It does not fit teams that need a self-service platform, real-time monitoring dashboards, or API access to pull competitive Share of Voice data into their own reporting stack. Because there is no software product — only a service engagement — teams that need to move fast between content experiments, or that want to internalize the optimization capability, will hit a ceiling on iteration speed that no configuration change can fix. A team that reaches that ceiling typically moves toward building in-house GEO processes or evaluating software-native platforms.