Keenious
Find research relevant to any text with AI-powered search.
Pricing
Free tier
Usage-based
Adoption
→StableLicense
Proprietary
Data freshness
UnverifiedOverview
What is Keenious?
Keenious uses advanced AI algorithms to help users find the most relevant research papers and articles based on their input text, streamlining the process of literature review for researchers and professionals.
Key differentiator
“Keenious stands out by offering an AI-driven approach to finding relevant research, providing users with highly accurate and contextually appropriate results.”
Capability profile
Capability Radar
Honest assessment
Strengths & Weaknesses
↑ Strengths
↓ Weaknesses
API requires Python-specific patterns, TypeScript SDK is community-maintained
v0.1 to v0.2 migration required rewriting chain definitions
Official SDK only available in Python, other languages rely on community support
Cost increases significantly with the number of queries and volume of data processed
Fit analysis
Who is it for?
✓ Best for
Academics needing to quickly find relevant literature for their research topics
Professionals who require up-to-date market analysis and industry reports
Content creators looking to curate articles based on specific themes or keywords
✕ Not a fit for
Users requiring real-time data updates (Keenious focuses on curated academic content)
Projects with extremely limited budgets as it operates on a usage-based pricing model
Cost structure
Pricing
Free Tier
Available
Top 10 search results, 5 AI responses per conversation, 10 conversations per day, 3 MB max file upload size
Starts at
$10/mo
Model
Usage-based
Enterprise
None
Performance benchmarks
How Fast Is It?
Ecosystem
Relationships
Integrations
Next step
Get Started with Keenious
Step-by-step setup guide with code examples and common gotchas.