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Web data your business and your agents can rely on.

Managed, monitored data feeds from public websites. Built by AI agents, checked by engineers, delivered by API, MCP or file, with the source on every row.

  • Feeds from $600/mo
  • Datasets from $1,500
  • Free sample in 2 days

Competitor prices

Updated today, 06:00 · 14 stores

Example feed
Product Store A Store B Store C
Trail runner 2 · black $129 $124.95 $131
Trail runner 2 · white $129 Out of stock $129
Rain shell pro · M $349 $339 $359
Day pack 24L $89 $84 $89

How the top 1,000 sites treat AI bots

From our AI Crawler Access Index, Nov 2026

21%

block OpenAI's GPTBot

30%

block at least one AI training crawler

14%

turn away a plain automated client

“Can't my AI agent just do this?”

For 50 rows, once: yes, and we'll tell you so. For data your team or product depends on every day, you need what an agent session doesn't give you: a fixed schema, monitoring when sites change, access that keeps working when bots get blocked, and a source for every value.

Your own AI agent

Great for a quick look. Fragile as a supply line.

Good for
20–500 rows, once, today
Cost
Roughly $0.02–0.50 per page-level task in model and browser time
When a site changes
Returns wrong or empty data, silently
Bot blocking
Increasingly blocked by default
Schema
Different every run
Traceability
“The model found it”
Where it lands
A chat transcript

A managed feed from us

Boring in the best way: it just keeps arriving.

Good for
10k to 10M rows, every day, for years
Cost
Fractions of a cent per page: agents build the pipeline, plain code runs it
When a site changes
Detected, alerted and fixed within the SLA
Bot blocking
A route that keeps working: official APIs, licensed or engineered access
Schema
A versioned contract; changes announced in advance
Traceability
Source URL, timestamp and method on every value
Where it lands
Your API, MCP server, warehouse, Sheets or CSV

Sources for the cost and reliability figures: browser agents vs. scrapers.

Agents do the building. A QA gate decides what ships.

Agents are good at figuring out a website and writing the code to read it. They are bad at running it ten thousand times without drifting. So we split the work.

The full process
  1. 1

    Scope

    We map the sources, the fields and the most reliable way to get each one, and send you a fixed quote.

  2. 2

    Agents build

    Coding agents write extractors against your schema and test them on live pages. A person reviews the change.

  3. 3

    QA gate

    Every run passes deterministic checks, then an independent model spot-checks a sample. Failures go back, not out.

  4. 4

    Run and monitor

    Plain code runs the feed on schedule. When a site changes we are alerted, an agent drafts the fix, we review it.

Proof, not testimonials: the same pipeline runs our own dataset.

Nomad Watch tracks 3,169 cities, 6,794 embassies and 3,625 tax treaties. Agents research it, a lint gate and a cross-model judge check it, and every run lands as one reviewable change. We publish the pass rates, including the batches that failed and went back for fixes.

Read the case study
agent runs in four weeks
7,068
research tasks completed
3,463
dated source citations
~39,600
embassy records, all sourced
6,794

What you get that a scraper script doesn't

Fix-time SLA

When a source breaks, the clock starts. Daily feeds carry a one-business-day fix target.

Versioned schema

Fields never change silently. New versions are announced and the old one keeps running.

Freshness on every row

Each value carries its retrieval time and source URL, so stale data is visible, not hidden.

Reviewed changes

Agents propose extractor fixes as reviewable changes. Nothing ships unreviewed.

No invented values

Language models never fill in data. Every field is observed on a page or marked as derived.

Monitoring you can see

Row counts, empty fields and layout drift are tracked on every run. You see what we see.

Public prices. Fixed quotes.

A monthly price per feed that covers running and repairing it. Setup is quoted after the free sample; normal access costs are included.

Full pricing

Single feed

$600

per source / month

One source, refreshed weekly. Daily refresh with an SLA from $1,000.

  • Setup from $1,000, quoted up front
  • Versioned schema and change log
  • Breakage monitoring and repair
  • CSV, JSON, Sheets or warehouse delivery
  • Source URL and timestamp on every row
Start with a sample

Team

Recommended

$3,000

per month

Up to 5 sources, daily refresh, monitoring included.

  • Everything in Single feed
  • Daily refresh, fix-time SLA
  • Web monitoring with AI change summaries
  • Hosted MCP server and API for your agents
  • Shared Slack or email channel
Scope a Team setup

Scale

$6,000+

per month

Many sources, high volume or hourly data. Quoted per project.

  • Everything in Team
  • Hourly or near-real-time feeds
  • Premium access routes passed through or included
  • Custom SLAs and data contracts
  • Quarterly source and schema review
Talk about Scale

Founding customers: the first five feed customers get 35% off for six months in exchange for a case study.

Details

Questions we get

Something else? Ask us directly.

Why not just ask ChatGPT, Claude or another browser agent to collect this?

For a one-off list of a few hundred rows, do that. It's cheaper. Agents get expensive and unreliable when the job repeats: on live-web benchmarks they finish roughly 30–60% of tasks, they cost real money per page, and they don't tell you when a site changed. We use agents to build and repair pipelines and plain code to run them.

What happens when a site blocks bots?

We pick the most reliable route per source: an official API or feed, open pages, licensed or paid access, or engineered collection through specialist infrastructure. If a source cannot be collected reliably, we say so before you pay.

How do you prevent hallucinated data?

Language models never generate values. Extractors read fields from pages, every value carries its source URL and timestamp, and each batch passes deterministic checks plus an independent model spot-check before delivery.

Can you deliver straight into our AI agents?

Yes. Any feed can be served as a hosted MCP server or REST API with narrow, documented tools, so ChatGPT, Claude, Cursor or your own agents can query it. It is included from the Team plan.

How fast can a feed go live?

The free sample takes 2 business days. Most single-source feeds go live within a week of approval; multi-source feeds in two to three weeks.

Who owns the data?

You do. You get the data, the schema and the source list. If you leave, we hand over the extractor documentation and a final export.

Get a free 100‑row sample

Tell us what you need to track. Within 2 business days you'll get a sample, the sources we'd use and a fixed price, or an honest note that an off-the-shelf tool will do.

  • Sample and fixed quote in 2 business days
  • Source URL and timestamp on every row
  • No commitment, no sales sequence

Prefer email? [email protected]

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