Stravito and Koji are often shortlisted together by insights leaders, which is odd, because they solve opposite halves of the same problem. Stravito is an enterprise insights management platform: it centralizes the research your organization has already commissioned and makes it searchable across teams. Koji is an AI-native research platform: it runs moderated interviews with real people and produces findings that did not exist this morning.
The distinction is not marketing positioning. It is the difference between a retrieval problem and a generation problem, and confusing the two is how insights teams end up with an immaculate library and no answer to the question the CEO asked on Tuesday.
This comparison is written by the team behind Koji. Stravito is a strong product in its category - it was named a Visionary in the 2026 Gartner Magic Quadrant for Competitive and Market Intelligence Platforms - and we say clearly below where it is the better purchase.
Koji vs Stravito at a glance
| Stravito | Koji | |
|---|---|---|
| Core job | Find and reuse existing research | Generate new primary evidence |
| Input | Reports, decks, PDFs, agency deliverables you already paid for | Live AI-moderated interviews with real participants |
| Output | Search results, curated collections, summaries of prior work | Transcripts, themes, quotes and reports from this week |
| Time to a new answer | Bounded by whether someone studied it before | Hours |
| Typical buyer | Enterprise insights or knowledge management leader | Product, marketing, CX or founder-led teams |
| Question it answers | What do we already know? | What is true right now? |
| Integrations | Teams, SharePoint, PowerBI, Slack, Tableau, Google Drive | CRM, product analytics, support tools, MCP |
| Pricing | On request | Published, self-serve, from 10 free credits |
| Fails when | Nobody has studied the question yet | You need to reuse a 2019 agency study |
What Stravito does well
It solves a real and expensive problem. Large organizations genuinely lose research. A global brand can commission the same segmentation study twice in three years across two regions because neither team knew the other had done it. Stravito exists because that waste is measurable and embarrassing.
The productivity numbers behind it are serious. McKinsey Global Institute research put the share of the workweek that knowledge workers spend searching for and gathering information at roughly 19 percent - about a day a week. IDC has estimated information retrieval at around 2.5 hours per day, close to 30 percent of the workday. In an enterprise with a large research spend, cutting that materially is a defensible line item on its own.
The feature set matches the job. AI-powered search across an entire research corpus, multi-lingual translation, curated collections by topic, role-based permissions, and delivery into the tools people already use - Microsoft Teams, SharePoint, Slack, PowerBI, Tableau and Google Drive. If your insights function is drowning in agency PDFs, this is the right shape of solution, and our insight repository methodology guide describes the practice it supports.
Analyst validation. The 2026 Gartner Magic Quadrant Visionary placement is a genuine signal for enterprise procurement, and it is the category Stravito competes in: competitive and market intelligence, not primary fieldwork.
The retrieval ceiling
Here is the structural limit, and it applies to every repository including the excellent ones.
Search quality determines how fast you reach the edge of what your organization already knows. It cannot move that edge.
A perfect insights platform - instant, semantic, multilingual, zero false negatives - returns everything anyone has ever learned and then stops. And the questions that actually block decisions cluster disproportionately outside that boundary, because they tend to be new: a competitor repriced last month, a feature shipped in March, a regulation changes in Q3, a segment started churning in a way no 2024 study anticipated.
Insights teams feel this as a specific frustration. The repository works, adoption is up, search is fast - and the hard questions still get answered with "we do not have anything on that." That is not a failure of the tool. It is the tool working exactly as designed, and hitting its ceiling.
The half-life problem, which better search makes worse
There is a second-order effect that rarely comes up in procurement.
A repository treats a study as a durable asset. But findings decay. A 2023 study of switching drivers describes a market that has since absorbed a pricing war, a new entrant and a shift in how customers buy. The document has not changed; its truth value has.
Retrieval systems have no native concept of decay. They rank by relevance to the query, and a well-tagged, well-summarized 2023 study is highly relevant to a 2026 question about switching drivers - especially when nothing newer exists to compete with it. So the better your search gets, the more influence stale research exerts on current decisions, because it surfaces instantly, looks authoritative, and carries the institutional weight of having been expensive.
The fix is not worse search. It is a cheap way to generate a current answer, so the 2023 study becomes context rather than conclusion. That is the gap Koji is built for.
How Koji works
Koji is an AI-native customer research platform. You describe what you need to learn; Koji builds the interview; participants have a live AI-moderated conversation by voice or text; themes and quotes arrive with the transcripts.
Real conversations, not forms. The AI moderator hears each answer and generates unscripted follow-ups, so a participant who says pricing felt "unfair" gets asked which part and what they expected - the question a survey defers to a second study. See AI follow-up probing.
Quant and qual in one study. Six structured question types - open_ended, scale, single_choice, multiple_choice, ranking and yes_no - produce distributions alongside the reasoning that explains them, detailed in the structured questions guide.
Automatic thematic analysis. Themes are generated across the corpus with every quote traced back to a named interview, using the method described in our thematic analysis guide. No manual coding pass, no three-week synthesis.
A customizable AI consultant. You shape the moderator's persona and priorities, so it probes like your best researcher, at interview 40 as attentively as at interview 1, with no moderator bias nudging respondents toward a preferred answer.
No research expertise required. This is what makes Koji a democratization tool as well as a research tool - a PM can run a defensible study without a trained moderator, as covered in the research democratization playbook.
Pricing
Stravito prices on request. That is normal for enterprise insights management, where seat counts, corpus size and integration scope drive the quote, and it means a procurement cycle before you learn the number.
Koji publishes its rates. Insights is EUR 29 per month for 29 credits; Interviews is EUR 79 per month for 79 credits; annual plans include two months free. A text interview costs 1 credit, a voice interview 3 credits, a report refresh 5 credits, and extra credits are EUR 1.00 with volume discounts. Only conversations that pass a quality score consume credits, so abandoned sessions do not bill.
New accounts get 10 free credits without a subscription - enough to run a real study before any procurement conversation happens. If you are consolidating tooling, research tool consolidation covers how the stack usually collapses.
Which should you buy
Buy Stravito if your organization already spends heavily on research, most of your pain is that people cannot find or reuse it, your corpus is thousands of documents across regions and agencies, and your mandate is knowledge management. If you are also comparing repository-first tools, our best UX research repository tools roundup covers the wider field.
Buy Koji if your bottleneck is that the answer does not exist yet, you need evidence in days rather than a commissioned project, your team has no dedicated researcher, or your most important questions are about your own customers right now.
Buy both if you are a large enterprise. They are complements, not substitutes, and the honest framing for a budget conversation is a ratio: what share of your insights spend goes to organizing what you bought versus generating what you need. Most enterprises are heavily overweight the first, because organizing is a one-time capex-shaped purchase and generating has historically been slow and expensive per study. AI-moderated interviews are what changed the second half of that equation. The build vs buy framework is a useful companion for that decision.
A repository full of current, first-party research beats a repository full of well-indexed history. The point of making research findable is that it is worth finding.
Frequently Asked Questions
Is Koji a Stravito alternative?
Not directly - they solve different problems. Stravito makes existing research findable; Koji generates new research. Koji becomes an alternative when the reason you were buying a repository was that decisions kept stalling for lack of evidence, because in that case the constraint was research supply, not search.
Does Koji store and organize past research like Stravito?
Koji stores everything it generates - transcripts, recordings, themes, quotes and reports - searchable across studies. It is not an enterprise knowledge management system for third-party agency PDFs and decks spanning decades, which is Stravito core competency. See our research repository guide for how the two layers fit together.
How much does Stravito cost?
Stravito does not publish pricing; quotes come through sales and vary with seats, corpus size and integrations. Koji publishes rates starting at EUR 29 per month for 29 credits, with 10 free credits on signup and no subscription required to start.
What is insights management, and do we need it?
Insights management is the practice of centralizing, tagging and surfacing research so an organization can reuse what it already knows. It pays off when you have a large existing corpus and multiple teams duplicating work. It pays off far less when your corpus is small or your questions are mostly new, because there is little to retrieve.
Can we use Koji and Stravito together?
Yes, and for large enterprises that is the sensible configuration. Use Stravito as the durable memory of what the organization has learned, and Koji to generate current primary evidence when retrieval comes back empty or stale. Koji reports export cleanly into a repository workflow.
Why does old research keep influencing decisions even with good search?
Because retrieval ranks by relevance, not freshness, and a well-tagged old study is highly relevant to a current question when nothing newer exists. Better search surfaces stale findings faster and more authoritatively. The remedy is making new research cheap enough that recent evidence usually exists to outrank it.
Answer the question nobody has studied yet
If your team can already find every study your company has run and the answer still is not there, the constraint was never search. Koji gives you AI-moderated interviews that probe like a researcher, thematic analysis that arrives with the transcripts, and reports stakeholders can act on - from question to insight in hours, not weeks, with no research background required.
Start free with 10 credits - enough to run a real study and put something current in your repository.
