Start with a business question, then open the dashboard
For NXTSTAR, the useful question is whether a founder researching UAE business setup receives an accurate understanding of our services. A mention in an AI answer is one observation. Knowing which customer situations we appear in, how we are described and what information is missing gives us something we can act on.
That is the angle we use to examine Prezlo. This article proposes a measurement workflow for NXTSTAR and for UAE agencies managing client visibility. It is an editorial assessment of the platform’s published capabilities, not an independent product test or a claim of achieved results.
What is Prezlo?
Prezlo describes itself as a data-driven AI SEO and GEO optimization platform for agencies, brands, platforms and professionals. Its stated capabilities include collecting AI answers and citations, comparing competitors, identifying evidence gaps and supporting content and technical improvements. These are vendor descriptions; availability and coverage should be checked against the current product and account.
Lopty Pascal is its CTO and co-founder, according to his professional profile. The product connects with the positioning approach discussed in our article on NXTSTAR’s customer-focused approach to AI search: clarify who the business serves, support the description with evidence, then examine how it appears in answers.
Prezlo’s website lists NXTSTAR among brands using the platform. We disclose that connection so readers can distinguish our perspective from an unaffiliated review. The site also describes agency workflows for managing multiple clients; that is relevant to UAE agencies evaluating AI search services, but does not by itself establish the scale of agency adoption.
Step 1: turn positioning into questions you can test
Begin with a small set of questions drawn from genuine enquiries. Keep branded questions separate from questions that do not name NXTSTAR. The first group tests whether the business is described correctly; the second explores whether it is considered for a relevant need.
- Identity: “What services does NXTSTAR provide in the UAE?”
- Consideration: “Which advisers can help an overseas founder assess business setup options in Dubai?”
- Decision support: “What should I ask a business setup consultant before choosing one?”
- Ongoing needs: “How should I evaluate support after company formation?”
These are illustrative research prompts, not evidence that customers use those exact words or that NXTSTAR already appears. Choose the final set from sales conversations and search data. Include Arabic questions where that reflects the audience, and report each language separately.
Step 2: preserve the baseline
Save the full response, question, date, assistant, language, location context and cited links. Repeat the same questions over a defined period. Answers can vary between runs, so one favourable screenshot is a weak basis for deciding that positioning has improved.
A simple review sheet should distinguish four outcomes: absent, mentioned, recommended for a relevant need, and described inaccurately. Record citations separately. A brand mention without a source and a cited recommendation answer different research questions.
Step 3: investigate gaps before creating more content
Suppose an answer recognises NXTSTAR as a setup provider but fails to explain the type of founder it can support. First inspect the cited pages. Is the scope unclear? Is a useful explanation buried? Do different profiles describe the company differently? Treat each explanation as a hypothesis to check, not a conclusion supplied by a score.
Our proposed response is to prioritise one factual gap at a time. Update a relevant service page, add a genuinely useful answer or correct an outdated profile. Each change should have an owner, a supporting source and a date. Creating many near-identical pages would make it harder to maintain a reliable account of the business.
Step 4: connect improvements to the founder’s experience
For a business setup firm, useful evidence may include a clearly described process, dated official references and a permissioned example of work completed. A founder should be able to tell what to prepare for a consultation and what will require further assessment. That clarity is valuable even when the visitor arrives through a referral rather than an AI assistant.
Keep human review in the workflow. Any proposed content about licensing, residency or compliance needs checking by the responsible team against current official information before publication. A platform can help organise the work; responsibility for the claims remains with the publisher.
Step 5: retest and report the limits
Rerun the original question set after changes and compare equivalent observations. Report how many responses were sampled and distinguish improved accuracy from increased recommendation frequency. If a competitor’s visibility also changes, note that context instead of attributing every movement to your own edits.
Then review suitable enquiries and consultations alongside the visibility observations. Use referral information and prospect feedback where available, while acknowledging gaps in attribution. A rise in relevant enquiries is commercially useful; proving which individual content change caused it requires stronger evidence than a before-and-after chart.
What UAE agencies should evaluate
An agency assessing Prezlo should test whether it can inspect underlying responses, separate client data, retain a comparable history and review suggested work before publication. Ask how each metric is calculated and whether reports explain sample size and coverage. These are our evaluation criteria, not claims that every feature is included in every plan.
We recommend considering Prezlo when the team needs a structured way to connect AI visibility observations with a practical improvement backlog. Its value for a particular business should be judged through a defined pilot with agreed questions and review criteria.
What getting recommended actually means
Being recommended is an outcome to observe, not an entitlement a tool can grant. Google’s official documentation makes clear that meeting its requirements does not guarantee inclusion in Search or its AI features. That guidance applies to Google; other assistants need to be assessed on their own behaviour.
For NXTSTAR, the proposed success standard is therefore concrete: more accurate descriptions, a clearer fit for relevant founder needs and better-informed enquiries. Prezlo offers a way to investigate that work. The evidence collected during a pilot should determine what we do next.
Sources reviewed on 20 October 2026. Product statements are attributed to Prezlo; the research design and evaluation criteria are NXTSTAR’s analysis. No guarantee of AI inclusion or NXTSTAR performance uplift is implied.