Profound is making Singapore its Asia Pacific headquarters, adding a regional base for a business focused on how brands appear in answers from AI search and conversational platforms. The expansion gives the company a local presence as marketers work out how product discovery changes when customers ask ChatGPT or Gemini for recommendations rather than starting with a conventional search result.
The company outlined the expansion in an announcement, saying Singapore will house regional leadership, customer and go-to-market teams supporting Southeast Asia, Japan, Australia and New Zealand. The more important question for brands is not whether AI search has arrived, but how to measure visibility in a channel where the answer can be the destination.
Table of contents
Jump to each section:
- Why Profound is building an APAC base in Singapore
- AI shopping research creates a different visibility problem
- From AI-search analytics to marketing operations
- What marketers should know about AI discovery in Asia Pacific
Why Profound is building an APAC base in Singapore
Profound plans to open a Singapore office in the central business district during the fourth quarter of 2026. Its local hiring plans span regional management, sales, engagement and account management, while some New York staff are expected to relocate for a year to help establish operations.
More than 15 local roles are planned over the next 12 months, according to Profound’s November 2 announcement.
James Cadwallader, Profound’s co-founder and CEO, described AI as “the new front door to every business” in the announcement. His point is also a commercial argument for setting up a regional team. The product sits at the intersection of brand strategy, search analytics and increasingly complex marketing execution, areas where customer context and local market knowledge matter.
A Singapore headquarters does not by itself establish that businesses across Asia Pacific have adopted GEO at scale. It does show where Profound has chosen to invest in local customer support and distribution. For marketing teams evaluating a new category, that distinction matters: an office opening is evidence of a vendor’s expansion, not independent proof of the market’s maturity.
AI shopping research creates a different visibility problem
Profound supplied a potentially useful signal from its analysis of anonymized conversations with AI systems in Singapore. Its figures suggest a rising share of interactions are linked to product and service research, but the data measures conversations rather than purchases.
23% increase in the share of conversations involving researching, comparing or buying products and services from January to September 2026, based on 1.8 million anonymized Singapore ChatGPT and Gemini conversations, according to Profound.
That is a relative increase in the share of commerce-related conversations, not a 23-percentage-point jump, and it is not a conversion-rate result. Profound did not disclose sufficient detail in the announcement for an independent assessment of the sample, intent classification or representativeness.
The usual search-marketing assumption is that a brand wins by moving a page higher in a ranked list. In an AI answer, the brand may instead be named, compared, paraphrased or omitted inside one generated response. A marketer therefore needs to distinguish visibility, the quality of the recommendation and the downstream commercial result.
Visibility can become a reporting metric before it becomes a proven revenue metric. That makes it worth monitoring, but it also argues against treating AI citations as interchangeable with leads or sales.
From AI-search analytics to marketing operations
Profound began as a system for tracking AI-search visibility and has expanded into an agent-supported marketing workbench. Its September product update describes AI Marketer as a tool for identifying opportunities and coordinating activities such as competitive analysis, content updates and paid campaign work. The company also describes a Context Manager intended to bring brand and team information into those workflows.
This broadening matters because knowing that an AI answer does not mention a product is different from deciding which product page, review or third-party source deserves attention. Measurement points to a potential gap. Fixing that gap may involve SEO, communications, customer content and advertising teams that do not normally share one operating dashboard.
Profound is not alone in offering AI-answer monitoring. The category contains services with overlapping measurement capabilities, although their product scope and workflows differ.
| Platform | Documented AI visibility focus |
|---|---|
| Profound | AI answer monitoring linked to an AI marketing agent workbench and campaign tools |
| Semrush | AI brand visibility tracking alongside established search-marketing tools |
| Peec AI | AI brand mentions, prompt tracking, competitor benchmarks and cited-source analysis |
Profound’s October partnership with Bazaarvoice offers a practical example. The companies connected AI visibility analysis with product reviews and other user-generated content, creating a path between finding an answer-engine content gap and improving the information AI systems may encounter.
The strategic issue is coordination rather than a dashboard race. The more work a marketing agent can propose or perform, the more important it becomes to know which team owns the decision, which evidence supports it and whether the change improved something beyond the visibility score.
What marketers should know about AI discovery in Asia Pacific
The Singapore expansion is a reminder that AI-search marketing now touches more than organic search specialists. Brand positioning, product data, public relations and paid media can all affect what information a buyer encounters before reaching a website.
Separate exposure from business impact. Track brand mentions and recommendations as discovery signals, but evaluate lead quality and commercial outcomes independently. Profound’s conversation analysis should not be read as evidence that more AI shopping questions automatically produce more purchases.
Audit the source material behind answers. Product detail pages, reviews and external coverage can shape how AI systems describe a brand. The Profound-Bazaarvoice tie-up illustrates why monitoring alone may not be enough.
Give AI workflows brand context. Profound’s Context Manager is designed to provide brand knowledge to its agents. That raises a broader question for any vendor evaluation: how accurately can a system use the company’s approved claims, product information and tone of voice?
Make accountability part of the tool decision. A vendor that can move from insight to action warrants questions about access, approval, measurement and rollback. The November announcement did not establish specific human approval controls for Profound’s workflows, so marketers should validate those directly.
The deeper change is organizational. Search visibility once sat largely within a specialist function; AI-mediated discovery increasingly asks several teams to agree on what a brand should be known for, and how to verify that the message is reaching customers.
Singapore’s role in this story is a regional service base, not a guarantee of results. As more AI marketing platforms establish local operations, the stronger test will be whether marketers can connect answer visibility to accurate content, accountable workflows and measurable customer decisions.
The enduring advantage may not belong to the team with the most AI mentions. It may belong to the one that can explain which mentions matter, why they happened and what to do next.
