The category, explained
A plain-English definition of on-demand expert networks — what they are, when to use one, and how AI is rewriting the playbook.
An on-demand expert network is a service that lets you ask a high-stakes professional question and receive a written, verified answer from practitioners who have done the specific thing before — typically within hours.
Think of it as the synchronous-call legacy expert network (GLG, AlphaSights, Guidepoint), reimagined for an async, AI-augmented buyer.
"Human intelligence as a service" (HIaaS) is the broader category: the subscription delivery of verified human expertise. Where AI handles synthesis, structure, and routing, humans supply the lived experience that isn't in any training set — operator playbooks, regulatory nuance, vendor reputations, and the institutional memory of an industry.
OpenIQ is an on-demand expert network built subscription-first. Compare OpenIQ to legacy networks, or see how experts are verified.
An on-demand expert network is a service that connects decision-makers with verified subject-matter practitioners and returns answers in hours rather than days. Unlike legacy networks built around scheduled calls, on-demand networks deliver written, AI-curated briefs synthesized from multiple expert inputs.
Human intelligence as a service (HIaaS) is the subscription delivery of verified human expertise — the qualitative, experiential knowledge that AI models cannot generate because it has never been written down. It complements AI rather than competing with it: AI handles synthesis and routing, humans supply lived experience.
Use an expert network when you need a focused answer from someone who has done the specific thing before — within hours, without scoping a project. Use a consultant when you need a multi-week workstream with deliverables, frameworks, and implementation support.
Use an AI model for known, well-documented domains. Use an expert network for tacit, recent, or proprietary knowledge — operator playbooks, regulatory nuances, vendor reputations, and anything where 'what's actually true on the ground today' matters more than 'what's in the training data.'
Reputable networks verify each practitioner against their LinkedIn profile, employment history, and topic-specific track record before accepting them. OpenIQ also requires reference checks.