Enquire AI is an early example of an agentic workflow applied to a high-value, high-complexity vertical: professional research. It moves beyond simple chat interfaces by employing agents to coordinate between human experts and structured data synthesis. By positioning itself as an 'agentic research platform,' Enquire demonstrates how agents can act as moderators and synthesizers for proprietary, non-public information—a crucial use case for the enterprise agent stack.
For the broader ecosystem, Enquire highlights the value of 'human-in-the-loop' agentic systems. Rather than trying to replace human experts, the platform uses AI to reduce the friction of finding, interviewing, and summarizing their views. This makes it relevant to developers building agentic tools for finance and policy, where the authority and verifiability of a source are more important than the speed of the model response.
Enquire AI operates at the intersection of traditional expert networks and modern generative search. Founded in 2018 as GlobalWonks before rebranding in 2021, the company addresses a specific failure of standard large language models: the lack of verifiable, real-time human perspective. While a standard LLM might synthesize public data or outdated training sets, Enquire attempts to ground its outputs in the judgment of experienced operators and specialists.
The platform is structured around three primary components. First is the expert perspective, which consists of direct input from a network of specialists. Second is a layer of structured AI research designed to synthesize these signals and identify gaps in the available data. Third is a focus on institutional memory, ensuring that research builds on prior context rather than starting from zero with every query. This combination is intended to serve institutional teams—such as those in capital markets, management consulting, and policy—who make decisions in environments where the cost of being wrong is high.
The transition from GlobalWonks to Enquire AI signaled a shift from a manual marketplace for experts to a more integrated software experience. The leadership team, led by CEO Barry Hurewitz and CFO Fatih Orhan, has built a platform that treats research as a continuous process. Rather than a one-off transaction where a user pays for a single call with an expert, the platform creates a Research Center. This workspace allows teams to build and refine their understanding as conditions change.
This approach differentiates Enquire from both traditional expert networks like GLG or AlphaSights and standalone AI tools like Perplexity or ChatGPT. Traditional networks are slow and expensive, often requiring days to schedule a consultation. Standalone AI tools are fast but prone to hallucinations and lack insights that are not yet documented online. Enquire positions itself as the middle ground, using agents to moderate interviews and synthesize proprietary data into professional insights.
One of the more distinct aspects of the platform is how it handles knowledge retention. In most consulting and investment environments, research is ephemeral. A team might spend weeks investigating a regulatory shift, only for that knowledge to disappear when the project ends or the analyst leaves. Enquire builds a repository where every inquiry adds to a growing knowledge base. This allows teams to pressure-test assumptions against previous findings and observe how views are forming over time.
The company is based in Washington, D.C. and New York City, drawing heavily on advisors from firms like Citi, EY, and UBS. This institutional DNA is reflected in the product’s focus on compliance and professional judgment. The platform includes features for AI-moderated interviews and rapid-response pulses, which are micro-surveys sent to their expert network. By automating the coordination and synthesis of these human inputs, Enquire allows a small team to perform research that would typically require a much larger headcount.
An agentic research platform that combines expert perspective with structured AI synthesis.