Company
Making AI search visibility measurable, manageable, and improvable for everyone.
Geoptiq.ai is a platform that measures, analyzes, and optimizes brand visibility across AI-powered search engines — ChatGPT, Gemini, Perplexity, Claude, Grok, and Copilot. Our mission is simple: show businesses exactly where they stand in the AI search landscape and give them concrete, data-driven recommendations on how to move forward.
Classic SEO was the marketer's primary tool for two decades. Since 2024, however, a growing share of users now ask "what's the best CRM?" not in Google, but directly in ChatGPT or Perplexity. The answer is no longer ten blue links; it's a single paragraph of advice. If your brand appears in that paragraph, you win; if not, your very existence is up for debate. Geoptiq.ai exists to close that gap.
Geoptiq.ai was founded in London in 2025 by a group of engineers and marketing operators with backgrounds in technology and SaaS. The founding team started from a concrete customer-side pain: great products failing to show up in AI chatbot recommendations. Organic traffic was quietly leaking to conversational interfaces, and marketing teams had no way to observe or attribute that shift with traditional analytics tools.
For the first six months, we worked on one question: "How do you measure a brand's AI search visibility in a consistent, repeatable way?" We built our methodology on top of prompt replays, variation testing, position normalisation, multi-model cross-checks, and disambiguated competitor tracking. When we opened the platform in early 2026, our goal was not just a dashboard — it was a measurement system that product and marketing teams could use to make weekly decisions.
Today, Geoptiq.ai is used by teams ranging from early-stage SaaS companies to international marketing agencies to track their position in AI search and feed their content strategy with hard data. The product expands every week with new models and new metrics.
AI search engines differ from classic search in three fundamental ways: (1) the result is delivered as a single answer, not a list; (2) that answer blends training data with live web retrieval; (3) the same prompt can return different answers across days and across models. These three properties make classic SEO tooling largely unusable for AI search.
As a result, marketing teams had been unable to answer three big questions:
- Are we visible? In which model, at what position, does our brand appear for our target category queries?
- How are we perceived? When we're mentioned, is the framing positive, neutral, or negative?
- What are competitors doing? Who's outperforming us, and why?
Geoptiq.ai reduces those three questions to a single measurement system. Every run dispatches dozens of prompt variations against every supported model, structures the outputs, and converts them into five core metrics. Marketing teams then make weekly calls not on instinct but on verifiable numbers.
Our measurement model rests on five core metrics, built by blending industry research, customer feedback, and our own internal experiments:
- Visibility: a normalised score of how often your brand is mentioned across the full prompt set.
- Sentiment: three-way sentiment classification of each mention — positive, neutral, negative.
- Position: the rank at which your brand appears in a model's answer — first place and fifth place are very different outcomes.
- Share of Voice (SOV): the percentage of total mentions you own relative to your competitors.
- Citations: which sources the model cites when producing answers — your own site, industry publications, or competitor content.
Each metric is tracked over time, compared against competitors, and broken down by model. That is how practical observations such as "we're strong on ChatGPT but losing ground on Gemini" become minutes-long, not weeks-long, exercises.
The platform has four main modules, all sharing the same measurement stack:
- Analysis: one-shot deep analyses. Give it a keyword, a brand, and a competitor list, and it returns a full visibility report in minutes.
- Tracker: runs your chosen prompt sets on a weekly or monthly schedule; ships with trend charts, regression alerts, and email reports.
- GEO Audit: evaluates how "readable" your website is for AI — schema.org markup, content structure, E-E-A-T signals, and a citeability score.
- Scheduled Reports: delivers weekly summary emails to stakeholders, enabling teams to manage multiple brands in parallel.
Under the hood, every module talks to the same PostgreSQL database, Cloud Tasks queue, and a Vertex AI + OpenAI model pool. When an analysis starts, the job runs on a separate worker Cloud Run service and streams to the user via polling — so even large analyses complete reliably, tab open or not.
We deliver measurable, data-backed outcomes. Every report carries concrete numbers and actionable recommendations. We don't hide how we arrive at those numbers — our methodology doc is public.
AI search moves fast, and so do we. We ship at least one new model, metric, or integration every month.
Every business has different needs. We tailor solutions to company size and industry, and our support team aims to respond within 24 hours.
Customer data, analysis outputs, and tracker lists belong to you. We never use your data to train models, and we never share it with third parties. Storage is GDPR, KVKK, and UK DPA 2018 compliant.
If numbers are decision tools, those numbers must be trustworthy. We compute statistical confidence intervals for every metric and minimise noise with prompt variation.
CEO & Founder
Chief Legal Officer
Head of Marketing
AI search will become the primary mode of information discovery over the next five years. Geoptiq.ai's goal is to be the measurement and optimisation infrastructure for every brand navigating that world. Just as Ahrefs, SEMrush, and Search Console became industry standards for classic SEO, a similar standard is emerging for AI search — and we are here to build it.
Our roadmap includes multi-language support, locale-specific analysis, a content generation assistant, integrated A/B testing infrastructure, and a third-party verification protocol. Every release ships alongside an updated methodology doc.