Elicit
Kagi
| Feature | Elicit | Kagi |
|---|---|---|
| Pricing | Free / from $10/mo | From $5/mo |
| Free Plan | ✓ Yes | ✗ No |
| Rating | 4.5 / 5 | 4.6 / 5 |
| Best For | researchers, academics, phd-students, scientists, analysts | privacy-conscious-users, developers, researchers, power-users |
| Founded | 2021 | 2022 |
| Paper Search | ✓ | ✗ |
| Summarization | ✓ | ✗ |
| Data Extraction | ✓ | ✗ |
| Synthesis | ✓ | ✗ |
| Citation Export | ✓ | ✗ |
| Saved Searches | ✓ | ✗ |
| Tables | ✓ | ✗ |
| Ad Free Search | ✗ | ✓ |
| Ai Summaries | ✗ | ✓ |
| Personalization | ✗ | ✓ |
| Domain Blocking | ✗ | ✓ |
| Lenses | ✗ | ✓ |
| Privacy | ✗ | ✓ |
✓ Elicit Pros
- Searches 125M+ academic papers
- Extracts structured data from papers
- Summarizes findings across multiple studies
- Saves hours of literature review
✗ Elicit Cons
- Limited to academic/scientific papers
- Free tier has usage limits
- Can miss nuanced findings
✓ Kagi Pros
- No ads or tracking
- Customizable results
- AI-powered summaries
- Fast and accurate
✗ Kagi Cons
- No free plan
- Requires subscription
- Smaller index than Google
The Verdict
Elicit is built for researchers and academics, with a focus on paper-search and summarization. Kagi targets privacy conscious users and developers and leads with ad-free-search and ai-summaries.
On pricing, Kagi is the clear winner for budget-conscious users — starting at $5/mo compared to $10/mo for Elicit. That $5/mo difference adds up quickly for growing teams.
Elicit has a free plan, which gives it a meaningful edge for individuals and small teams exploring their options. Kagi requires a paid subscription from day one.
Feature-wise, Elicit offers broader built-in capabilities (7 features vs 6), while Kagi takes a more focused approach — which can mean a simpler, faster onboarding experience.
Both tools are a solid fit for researchers — in those cases, the decision often comes down to workflow style and how your team prefers to organize work.
This is a genuinely close comparison. If you can, sign up for both free trials (where available) and run a one-week test with your actual team tasks before deciding.