SiftQ vs
Tavily.

SiftQ matches Tavily on agent ergonomics, adds structured output mode, and exposes a true multi-modal scope (image, video, podcast, scholar) under one API.

Try the SiftQ API playground Visit Tavily ↗

TL;DR

Tavily is great for plain RAG on webpages. SiftQ becomes the obvious pick the moment your agent crosses into multi-modal retrieval.

SiftQ

Why pick us

Your agent needs more than webpages — images, videos, papers, podcasts — and you want one auth scheme to cover all of them.

✓10 scopes vs 2
✓Structured output GA
✓Lower latency
✓Cheaper at scale

Tavily

Why pick them

You want the simplest "web search for my LangChain pipeline" with no surprises and zero scope complexity.

•Excellent LangChain ergonomics
•Tight RAG focus
•Simple mental model
•Reliable for general queries

Side by side

At a glance.

Preview · numbers below are illustrative pending audited benchmarks

SiftQTavily

p50 latency · ranked174ms280ms

Multi-modal scopes102

Structured output (schema)yesbeta

LangChain native integrationyesyes

Free tier (queries/mo)1,0001,000

PricingFree tier 1,000/mo, $0.003/query at scale.Free tier 1,000/mo, $0.008/query at scale.

Tavily's positioning

Tavily focuses tightly on the RAG / LangChain integration story with strong "search → context" ergonomics out of the box.

SiftQ's positioning

SiftQ matches Tavily on agent ergonomics, adds structured output mode, and exposes a true multi-modal scope (image, video, podcast, scholar) under one API.

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