SpiderFly
Sign inGet API key
Production web data infrastructure

Web data infra for AI agents

Fetch, render, extract, and crawl the public web through one API. Get normalized outputs with the audit evidence production systems need.

Get API key Explore the API
Light to browser waterfallPublic-safe controlsAudit-ready results
POST /v1/fetch
// Request
{
  "url": "https://example.com/docs"
}

// Response
{
  "status": "completed",
  "content": {
    "markdown": "# Example Docs"
  },
  "audit": {
    "engine_winner": "light",
    "quality_score": 0.92
  }
}
200 completed · 842 ms
One deliberate data path

Use the least expensive engine that works.

SpiderFly keeps routing, quality decisions, identity, and browser capacity behind one consistent API boundary.

01

Fetch fast

Start with a lightweight request path for pages that do not need a browser.

Read the guide
02

Render when needed

Escalate to managed browser rendering only when page behavior requires it.

Read the guide
03

Extract usable data

Return normalized content, structured items, metadata, and explainable audit fields.

Read the guide
Abstract editorial view of web documents becoming structured data
From page to usable data

Keep content and execution evidence together.

Every accepted result can carry normalized content, artifacts, usage, quality, and fallback information. Your agent gets data it can use and your team gets a path it can explain.

Normalized
Markdown, HTML, metadata, and links
Structured
Typed extraction for repeated page shapes
Explainable
Engine attempts, fallback reasons, and quality
See the platform
Built for production workflows

One API surface from single pages to recurring collection.

01

AI research

Ground agents with current public web context and traceable source output.

02

Site monitoring

Observe pages, feeds, channels, and source-specific updates through durable jobs.

03

Data extraction

Turn repeated page structures into validated JSON without rebuilding browser infrastructure.

04

Web crawling

Plan bounded crawls and inspect asynchronous status, results, usage, and diagnostics.

From the journal

Patterns for dependable web data

Short, practical notes for teams building collection and agent workflows.

Browse the journal
Guides

When a web data request needs a browser

A practical way to choose between direct fetch and browser rendering without paying browser cost for every page.

7 min read
Guides

Designing bounded crawls for production

Define scope, depth, and result ownership before a crawl starts so asynchronous collection stays predictable.

8 min read
Guides

From HTML to structured data for agents

Separate acquisition from extraction, then validate a typed result before it becomes agent context.

6 min read
Start building

Give your agents a dependable web data layer.

Start with Fetch, add browser rendering when a target needs it, and keep the same result contract as your workload grows.

Get API key API reference