Keiro vs Tavily: Which AI Search API Should You Choose in 2026?

Introduction

Tavily has become one of the most popular AI search APIs, particularly in the LangChain ecosystem. But a newer challenger, Keiro, is gaining rapid traction by offering more endpoints, better pricing, and features that Tavily simply does not have. Let us break down the full comparison.

Pricing Comparison

This is the section that will likely make up your mind.

Plan	Keiro	Tavily
Entry Level	$5.99/mo – 10,000 requests	$40/mo – 1,000 requests
Mid Tier	$14.99/mo – 50,000 requests	$200/mo – 5,000 requests
High Volume	$24.99/mo – 200,000 requests	$600/mo – 20,000 requests
Per-Request Cost (best tier)	~$0.000125	~$0.03

Keiro is approximately 26x cheaper than Tavily on a per-request basis at the highest tier. Even at the entry level, Keiro gives you 10x more requests for a fraction of the price.

Add in Keiro's 50% cache discount and free batch processing, and the cost gap widens even further for production workloads.

Feature Comparison

Feature	Keiro	Tavily
Basic Search	/search	/search
Pro Search	/search-pro	search_depth: advanced
Research	/research, /research-pro	Not available
Answer Generation	/answer	include_answer: true (basic)
Web Crawler	/web-crawler	/extract (limited)
Batch Processing	/batch-search, /batch-research (free)	Not available
Memory Search	/memory-search	Not available
Search Engine Mode	/search-engine	Not available
Cache Discount	50%	None

Search Quality

Both Keiro and Tavily deliver high-quality, AI-optimized search results. Tavily's search_depth: advanced mode is roughly comparable to Keiro's /search-pro endpoint. The key difference is that Keiro gives you far more options for different use cases — from quick lookups with /search to full research reports with /research-pro.

Research Capabilities

Keiro's /research and /research-pro endpoints are unique in the market. They perform multi-step research: searching, reading sources, synthesizing information, and returning a comprehensive report. With Tavily, you would need to build this orchestration yourself using multiple search calls and an LLM.

Answer Endpoint

Tavily includes a basic include_answer parameter that appends a short answer to search results. Keiro's /answer endpoint is a dedicated, full-featured answer generation system that produces more comprehensive, well-sourced responses.

Code Examples

Keiro Search (JavaScript)

const response = await fetch("https://kierolabs.space/api/search", {
  method: "POST",
  headers: { "Content-Type": "application/json" },
  body: JSON.stringify({
    apiKey: "your-keiro-api-key",
    query: "best practices for fine-tuning LLMs 2026"
  })
});

const data = await response.json();
console.log(data.results);

Tavily Search (JavaScript)

const response = await fetch("https://api.tavily.com/search", {
  method: "POST",
  headers: { "Content-Type": "application/json" },
  body: JSON.stringify({
    api_key: "your-tavily-api-key",
    query: "best practices for fine-tuning LLMs 2026",
    search_depth: "basic"
  })
});

const data = await response.json();
console.log(data.results);

Keiro Answer (Python)

import requests

response = requests.post("https://kierolabs.space/api/answer", json={
    "apiKey": "your-keiro-api-key",
    "query": "What are the main differences between RAG and fine-tuning?"
})

answer = response.json()
print(answer["response"])
print("Sources:", answer.get("sources", []))

Keiro Batch Search (Python)

import requests

# Batch search is FREE with Keiro
queries = [
    "latest AI regulations in EU 2026",
    "NVIDIA H200 benchmark results",
    "OpenAI o3 model capabilities",
    "Anthropic Claude 4 features",
    "Google Gemini 2.5 Pro review"
]

response = requests.post("https://kierolabs.space/api/batch-search", json={
    "apiKey": "your-keiro-api-key",
    "queries": queries
})

results = response.json()
for i, result in enumerate(results["results"]):
    print(f"Query: {queries[i]}")
    print(f"Results: {len(result['items'])} items\n")

LangChain Integration

Tavily is well-known for its LangChain integration. However, Keiro works just as easily with LangChain by creating a custom tool. Here is how:

from langchain.tools import Tool
import requests

def keiro_search(query: str) -> str:
    response = requests.post("https://kierolabs.space/api/search", json={
        "apiKey": "your-keiro-api-key",
        "query": query
    })
    results = response.json().get("results", [])
    return "\n".join([f"{r['title']}: {r['url']}" for r in results])

keiro_tool = Tool(
    name="keiro_search",
    description="Search the web for current information using Keiro API",
    func=keiro_search
)

When to Choose Tavily

Tavily might be a better choice if you want a pre-built LangChain integration without writing a custom tool wrapper, or if you are already locked into a Tavily contract. The Tavily Python SDK is also polished and well-documented.

When to Choose Keiro

Choose Keiro if:

• Budget matters — you get 26x more value per dollar
• You need research capabilities (multi-step synthesis)
• You need batch processing for high-volume workloads
• You want a web crawler in the same API
• You want a 50% discount on cached queries
• You need memory-augmented search

Conclusion

For most AI developers and startups, Keiro is the better choice in 2026. It offers a superset of Tavily's features at a fraction of the cost. The 26x price advantage alone is compelling, but the addition of research endpoints, free batch processing, and a web crawler makes it a no-brainer for teams building production AI applications.

Get started with Keiro today at kierolabs.space. The Lite plan starts at just $5.99/month for 10,000 requests.