# Tender Intake Evidence Extractor (`signal-foundry/tender-intake`) Actor

Extract project, issuer, site, submission-date text, and required documents from supplied English tender text. Preserve document/page/quote evidence and flag missing or conflicting values for human review. Text-only, bounded, and not legal advice.

- **URL**: https://apify.com/signal-foundry/tender-intake.md
- **Developed by:** [Signal Foundry](https://apify.com/signal-foundry) (community)
- **Categories:** Automation, Developer tools
- **Stats:** 1 total users, 0 monthly users, 0.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

Pay per usage

This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have.

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

## 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

## Tender Intake Evidence Extractor

Use this Actor for tender document extraction from supplied English text into a bounded intake row
with source evidence. It extracts project, issuer, site, submission-date text,
and required documents, while retaining document IDs, page references, and
source quotes.

Missing values stay missing. Conflicting values remain flagged for human
review; the Actor does not select a deadline or provide legal advice.

### Quick start

1. Supply one to five English text documents.
2. Include an `id` and `text` for each document.
3. Add `page_count`, `page_number`, and `source_url` when available.
4. Run the Actor and review the extracted values, evidence, and diagnostics.

```json
{
  "documents": [
    {
      "id": "invitation",
      "text": "Project: Riverside Library\nIssuer: Example Council\nSite: 1 Main Street\nReturn by 12 September 2026 at noon.\nRequired documents: tender form, safety plan",
      "page_count": 1,
      "page_number": 1
    }
  ]
}
```

### What it returns

The output contains an intake row with extracted fields and evidence for each
value: document ID, page number, and source quote. It also reports missing
fields, conflicting values, and input diagnostics so a reviewer can check the
source material before using the result.

### Limits

- Accepts supplied English text; it does not fetch source files or perform PDF
  parsing or OCR.
- Each package is limited to 5 documents and 100 declared pages.
- This release is limited to synthetic or public non-confidential text until a
  separate data-handling decision is made for customer documents.
- It does not accept credentials, inbox or CRM connections, drawings, or
  quantities.
- It provides no legal, bid, compliance, or contract advice.

### Responsible use

Keep a human reviewer in the loop. Check every important extracted value and
its source quote against the original tender material before acting on it.

### Trial and support

Start with the synthetic invitation above. Expect `fields.project.value` to be
`Riverside Library` and `needs_review` to include `timezone_not_stated`. Each
field has an extraction status and source evidence. Extraction uses supported
text labels and date phrases; other layouts can leave fields missing. It does
not infer arbitrary tender requirements. `page_number` is a reference supplied
by you, not a page detected by a PDF reader.
Check the Pricing tab and run cost estimate before starting; platform usage
may cost money. Report unexpected results through the Issues tab using a
synthetic or public non-confidential example.

# Actor input Schema

## `documents` (type: `array`):

documents

## Actor input object example

```json
{
  "documents": [
    {
      "id": "invitation",
      "text": "Project: Riverside Library\nIssuer: Example Council\nSite: 1 Main Street\nReturn by 12 September 2026 at noon.\nRequired documents: tender form, safety plan",
      "page_count": 1,
      "page_number": 1
    }
  ]
}
```

# Actor output Schema

## `items` (type: `string`):

items

## `diagnostics` (type: `string`):

diagnostics

# 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 = {
    "documents": [
        {
            "id": "invitation",
            "text": "Project: Riverside Library\nIssuer: Example Council\nSite: 1 Main Street\nReturn by 12 September 2026 at noon.\nRequired documents: tender form, safety plan",
            "page_count": 1,
            "page_number": 1
        }
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("signal-foundry/tender-intake").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 = { "documents": [{
            "id": "invitation",
            "text": """Project: Riverside Library
Issuer: Example Council
Site: 1 Main Street
Return by 12 September 2026 at noon.
Required documents: tender form, safety plan""",
            "page_count": 1,
            "page_number": 1,
        }] }

# Run the Actor and wait for it to finish
run = client.actor("signal-foundry/tender-intake").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 '{
  "documents": [
    {
      "id": "invitation",
      "text": "Project: Riverside Library\\nIssuer: Example Council\\nSite: 1 Main Street\\nReturn by 12 September 2026 at noon.\\nRequired documents: tender form, safety plan",
      "page_count": 1,
      "page_number": 1
    }
  ]
}' |
apify call signal-foundry/tender-intake --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,signal-foundry/tender-intake"
        }
    }
}

```

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/fci1yu3oIRZqTxBjv/builds/sCiqayrplPsIacoz5/openapi.json