Quepasa-AI
API for RAG retrieval and document management.
Pricing
Free tier
Flat rate
Adoption
↘CoolingLicense
Open Source
Data freshness
Aging · Jun 8, 2026Overview
What is Quepasa-AI?
Quepasa-AI provides an API for Retrieval-Augmented Generation (RAG) retrieval, managing documents and files efficiently. It is designed to help developers integrate advanced data infrastructure into their applications.
Key differentiator
“Quepasa-AI stands out with its efficient RAG retrieval capabilities and document management features, offering developers a robust tool for integrating advanced data infrastructure into their applications.”
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
Lack of native connectors for popular databases and storage systems
Documentation lacks step-by-step guides for different deployment scenarios
Fit analysis
Who is it for?
✓ Best for
Teams building RAG apps who need efficient document management
Projects requiring self-hosted solutions for data retrieval and indexing
✕ Not a fit for
Applications needing real-time streaming capabilities (batch-only architecture)
Budget-constrained projects that cannot afford the setup costs of a self-hosted solution
Cost structure
Pricing
Free Tier
Available
Open source — free to use
Starts at
$0
Model
Flat rate
Enterprise
None
Performance benchmarks
How Fast Is It?
Ecosystem
Relationships
Next step
Get Started with Quepasa-AI
Step-by-step setup guide with code examples and common gotchas.