# Case Study Claim Evidence Extractor (`junipr/case-study-claim-evidence-extractor`) Actor

Extract case-study claims, metrics, outcomes, client names, industries, timelines, before and after language, and evidence context from public case-study pages

- **URL**: https://apify.com/junipr/case-study-claim-evidence-extractor.md
- **Developed by:** [junipr](https://apify.com/junipr) (community)
- **Categories:** Developer tools
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $11.50 / 1,000 case study page analyzeds

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.
Actors are written with capital "A".

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.
The best way to integrate Actors is as follows.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).

# README

## Case Study Claim Evidence Extractor

Extract case-study claims, metrics, outcomes, client names, industries, timelines, before/after language, and evidence context from public case-study pages.

### What it does

Extracts case-study claims, metrics, units, timeframes, client/industry context, before/after signals, and risky unsupported wording.

Every row is source-backed and schema-complete. Missing, blocked, or unmatched evidence produces diagnostics instead of invented values.

### Uses

- Extract case study claims
- Build proof point inventory
- Find vague marketing claims
- Export metrics from case studies
- Review case studies for sales enablement

### Input

Use authorized public HTTP(S) URLs or deterministic `htmlInputs`. Private-network targets are rejected and `allowedDomains` can narrow fetching.

- `startUrls`
- `sitemapUrls`
- `htmlInputs`
- `allowedDomains`
- `maxPages`
- `maxDepth`
- `includeEvidence`
- `includeRawSnapshots`
- `requestDelayMs`
- `timeoutMs`
- `userAgentMode`
- `caseStudyUrls`
- `claimPatterns`
- `metricPatterns`
- `extractClientInfo`
- `includeScreenshots`
- `redFlagTerms`
- `maxCaseStudyPages`
- `maxClaims`
- `maxEvidenceRecords`
- `maxChargeUsd`
- `includeReport`

Limits in `maxCaseStudyPages, maxClaims, maxEvidenceRecords, timeoutMs` and `maxChargeUsd` are enforced. Zero is a hard zero charge budget.

### Dataset

- `sourceUrl`
- `sourceType`
- `pageTitle`
- `recordType`
- `recordName`
- `issueCode`
- `severity`
- `evidenceSnippet`
- `recommendation`
- `canonicalUrl`
- `httpStatus`
- `scannedAt`
- `caseStudyUrl`
- `clientName`
- `industry`
- `claimText`
- `metricValue`
- `metricUnit`
- `timeframe`
- `beforeAfterSignal`
- `evidenceContext`
- `redFlag`
- `claimType`

Reports:

- `case-study-claim-evidence-extractor-summary-report.md`
- `case-study-claim-evidence-extractor-records.csv`
- `case-study-claim-evidence-extractor-issues.json`
- `case-study-claim-evidence-extractor-evidence-samples.json`
- `case-study-claim-evidence-extractor-run-metadata.json`

### PPE pricing

Platform-usage pass-through is off.

| Event | Price |
| --- | ---: |
| `actor-start` | $0.035 |
| `case-study-page-analyzed` | $0.0115 |
| `claim-record-extracted` | $0.0065 |
| `evidence-gap-detected` | $0.0115 |
| `executive-report-generated` | $0.4 |

The actor-start event is accepted before fetching. Source, record, signal, gap, and blocker events are deduplicated and charged before their paid output. Partial charges, event limits, and local caps stop later output. Reports are written only after the report event is accepted.

### Safety and limitations

- Public evidence only; no login, CAPTCHA bypass, or access-control evasion.
- Output reflects source content at scan time.
- Attribution, claim permission, pricing interpretation, partner status, and launch decisions require human ownership.
- Store discounts, tasks, categories, icons, publication, and scheduling are separate gated live configuration.

### Local verification

```bash
pnpm --filter @junipr/case-study-claim-evidence-extractor build
pnpm --filter @junipr/case-study-claim-evidence-extractor test
pnpm --filter @junipr/case-study-claim-evidence-extractor smoke
```

# Actor input Schema

## `startUrls` (type: `array`):

startUrls for Case Study Claim Evidence Extractor.

## `sitemapUrls` (type: `array`):

sitemapUrls for Case Study Claim Evidence Extractor.

## `htmlInputs` (type: `array`):

htmlInputs for Case Study Claim Evidence Extractor.

## `allowedDomains` (type: `array`):

allowedDomains for Case Study Claim Evidence Extractor.

## `maxPages` (type: `integer`):

maxPages for Case Study Claim Evidence Extractor.

## `maxDepth` (type: `integer`):

maxDepth for Case Study Claim Evidence Extractor.

## `includeEvidence` (type: `boolean`):

includeEvidence for Case Study Claim Evidence Extractor.

## `includeRawSnapshots` (type: `boolean`):

includeRawSnapshots for Case Study Claim Evidence Extractor.

## `requestDelayMs` (type: `integer`):

requestDelayMs for Case Study Claim Evidence Extractor.

## `timeoutMs` (type: `integer`):

timeoutMs for Case Study Claim Evidence Extractor.

## `userAgentMode` (type: `string`):

userAgentMode for Case Study Claim Evidence Extractor.

## `caseStudyUrls` (type: `array`):

caseStudyUrls for Case Study Claim Evidence Extractor.

## `claimPatterns` (type: `array`):

claimPatterns for Case Study Claim Evidence Extractor.

## `metricPatterns` (type: `array`):

metricPatterns for Case Study Claim Evidence Extractor.

## `extractClientInfo` (type: `boolean`):

extractClientInfo for Case Study Claim Evidence Extractor.

## `includeScreenshots` (type: `boolean`):

includeScreenshots for Case Study Claim Evidence Extractor.

## `redFlagTerms` (type: `array`):

redFlagTerms for Case Study Claim Evidence Extractor.

## `maxCaseStudyPages` (type: `integer`):

maxCaseStudyPages for Case Study Claim Evidence Extractor.

## `maxClaims` (type: `integer`):

maxClaims for Case Study Claim Evidence Extractor.

## `maxEvidenceRecords` (type: `integer`):

maxEvidenceRecords for Case Study Claim Evidence Extractor.

## `maxChargeUsd` (type: `number`):

maxChargeUsd for Case Study Claim Evidence Extractor.

## `includeReport` (type: `boolean`):

includeReport for Case Study Claim Evidence Extractor.

## Actor input object example

```json
{
  "startUrls": [],
  "sitemapUrls": [],
  "htmlInputs": [
    {
      "sourceUrl": "https://example.com/case-study",
      "html": "<title>Case Study</title><article data-client='Northstar' data-industry='SaaS'><h1>Northstar results</h1><p>Revenue increased 41% within 6 months after launch.</p></article>"
    }
  ],
  "allowedDomains": [],
  "maxPages": 5,
  "maxDepth": 5,
  "includeEvidence": false,
  "includeRawSnapshots": false,
  "requestDelayMs": 5,
  "timeoutMs": 5,
  "userAgentMode": "",
  "caseStudyUrls": [],
  "claimPatterns": [],
  "metricPatterns": [],
  "extractClientInfo": true,
  "includeScreenshots": false,
  "redFlagTerms": [
    "guaranteed"
  ],
  "maxCaseStudyPages": 5,
  "maxClaims": 20,
  "maxEvidenceRecords": 50,
  "maxChargeUsd": 75,
  "includeReport": true
}
```

# Actor output Schema

## `results` (type: `string`):

No description

## `report` (type: `string`):

No description

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {};

// Run the Actor and wait for it to finish
const run = await client.actor("junipr/case-study-claim-evidence-extractor").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {}

# Run the Actor and wait for it to finish
run = client.actor("junipr/case-study-claim-evidence-extractor").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{}' |
apify call junipr/case-study-claim-evidence-extractor --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,junipr/case-study-claim-evidence-extractor"
        }
    }
}

```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/BvwsJPJzXhv4S5SAd/builds/2ABCY96bWFZu998Ur/openapi.json