Reference table
Agency vs in-house vs AI platform: 8 factors
An eight-factor matrix for deciding who runs your UX research: an agency, an in-house team or an AI-native platform. It compares cost at low and high study volumes, speed to first insight, product context, independence, methodological specialization, knowledge retention and confidentiality. Most teams end up with a mix. Koji covers the platform column for repeatable interview work.
Where this appears
What's in this reference table
| Factor | Agency | In-house | AI platform |
|---|---|---|---|
| Cost at low volume (under 3 studies a year) | Best | Worst | Good |
| Cost at high volume (over 8 studies a year) | Worst | Good | Best |
| Speed to first insight | Slow | Medium | Fastest |
| Product context depth | Low | Highest | Medium, improves with a repository |
| Independence and political neutrality | Highest | Low | Medium |
| Methodological specialization | Highest | Varies | Standardized, framework-driven |
| Knowledge retention | Low by default | Highest | High, stays in your workspace |
| Confidentiality of unreleased work | Managed by NDA | Highest | Depends on vendor security |
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<a href="https://www.koji.so/visuals/agency-vs-in-house-vs-ai-platform-decision-matrix"><img src="https://www.koji.so/visuals/agency-vs-in-house-vs-ai-platform-decision-matrix/agency-vs-in-house-vs-ai-platform-decision-matrix.png" alt="Table rating a research agency, an in-house team and an AI platform on eight factors, from cost by volume to knowledge retention." width="1200" height="957" /></a>
<p>Source: <a href="https://www.koji.so/visuals/agency-vs-in-house-vs-ai-platform-decision-matrix">Agency vs in-house vs AI platform: 8 factors</a>, Koji</p>
