Alternative Data for Investment API - Web Data for Finance

Traditional Data Isn't Enough

Everyone has access to the same financial data feeds. To generate alpha, you need unique data sources - web-based signals that reveal market dynamics before they show up in traditional metrics.

Building and maintaining alternative data pipelines is expensive and complex. You need a reliable way to extract insights from the web at scale.

WebScraping.AI Solution

Flexible Data Collection: Extract any data from any public website
AI-Powered Analysis: Ask questions about pages and get intelligent insights
Scale Ready: Handle thousands of data points daily
Reliable Infrastructure: Enterprise-grade uptime and accuracy

Alternative Data Sources

Web data that drives investment insights

Company Signals

Track hiring, job postings, executive changes, and expansion indicators.

Consumer Data

Monitor pricing, inventory levels, and product launches.

Sentiment Data

Extract sentiment from reviews, forums, and news sources.

News & Events

Monitor press releases, news articles, and regulatory filings.

Code Examples

Extract alternative data signals

Track hiring signals from a careers page

curl -G "https://api.webscraping.ai/ai/fields" \
  --data-urlencode "api_key=YOUR_API_KEY" \
  --data-urlencode "url=https://target-company.com/careers" \
  --data-urlencode "fields[total_openings]=Total number of open positions" \
  --data-urlencode "fields[departments_hiring]=Which departments are hiring" \
  --data-urlencode "fields[engineering_roles]=Number of engineering positions" \
  --data-urlencode "fields[sales_roles]=Number of sales positions" \
  --data-urlencode "fields[locations]=Locations with open positions" \
  --data-urlencode "fields[recent_postings]=Jobs posted in the last 30 days"
# Response:
# {
#   "total_openings": 47,
#   "departments_hiring": ["Engineering", "Sales", "Marketing", "Operations"],
#   "engineering_roles": 23,
#   "sales_roles": 12,
#   "locations": ["San Francisco", "New York", "London", "Remote"],
#   "recent_postings": 15
# }

# pip install webscraping_ai
# https://pypi.org/project/webscraping-ai/
from webscraping_ai import Client

client = Client(api_key="YOUR_API_KEY")
result = client.fields(
    "https://target-company.com/careers",
    fields={
        "total_openings": "Total number of open positions",
        "departments_hiring": "Which departments are hiring",
        "engineering_roles": "Number of engineering positions",
        "sales_roles": "Number of sales positions",
        "locations": "Locations with open positions",
        "recent_postings": "Jobs posted in the last 30 days",
    },
)
print(result)
# Response:
# {
#   "total_openings": 47,
#   "departments_hiring": ["Engineering", "Sales", "Marketing", "Operations"],
#   "engineering_roles": 23,
#   "sales_roles": 12,
#   "locations": ["San Francisco", "New York", "London", "Remote"],
#   "recent_postings": 15
# }

// npm install webscraping-ai
// https://www.npmjs.com/package/webscraping-ai
import { WebScrapingAI } from 'webscraping-ai';

const client = new WebScrapingAI({ apiKey: 'YOUR_API_KEY' });
const result = await client.fields({
  url: 'https://target-company.com/careers',
  fields: {
    total_openings: 'Total number of open positions',
    departments_hiring: 'Which departments are hiring',
    engineering_roles: 'Number of engineering positions',
    sales_roles: 'Number of sales positions',
    locations: 'Locations with open positions',
    recent_postings: 'Jobs posted in the last 30 days',
  },
});
console.log(result);
// Response:
// {
//   "total_openings": 47,
//   "departments_hiring": ["Engineering", "Sales", "Marketing", "Operations"],
//   "engineering_roles": 23,
//   "sales_roles": 12,
//   "locations": ["San Francisco", "New York", "London", "Remote"],
//   "recent_postings": 15
// }

<?php
// composer require webscraping-ai/webscraping-ai-php
// https://packagist.org/packages/webscraping-ai/webscraping-ai-php
require 'vendor/autoload.php';

use WebScrapingAI\Client;

$client = new Client('YOUR_API_KEY');
$result = $client->fields('https://target-company.com/careers', [
    'total_openings'     => 'Total number of open positions',
    'departments_hiring' => 'Which departments are hiring',
    'engineering_roles'  => 'Number of engineering positions',
    'sales_roles'        => 'Number of sales positions',
    'locations'          => 'Locations with open positions',
    'recent_postings'    => 'Jobs posted in the last 30 days',
]);
print_r($result);
// Response:
// {
//   "total_openings": 47,
//   "departments_hiring": ["Engineering", "Sales", "Marketing", "Operations"],
//   "engineering_roles": 23,
//   "sales_roles": 12,
//   "locations": ["San Francisco", "New York", "London", "Remote"],
//   "recent_postings": 15
// }

# gem install webscraping_ai
# https://rubygems.org/gems/webscraping_ai
require 'webscraping_ai'

client = WebScrapingAI::Client.new(api_key: 'YOUR_API_KEY')
result = client.fields(
  'https://target-company.com/careers',
  fields: {
    total_openings:      'Total number of open positions',
    departments_hiring:  'Which departments are hiring',
    engineering_roles:   'Number of engineering positions',
    sales_roles:         'Number of sales positions',
    locations:           'Locations with open positions',
    recent_postings:     'Jobs posted in the last 30 days',
  }
)
puts result.inspect
# Response:
# {
#   "total_openings": 47,
#   "departments_hiring": ["Engineering", "Sales", "Marketing", "Operations"],
#   "engineering_roles": 23,
#   "sales_roles": 12,
#   "locations": ["San Francisco", "New York", "London", "Remote"],
#   "recent_postings": 15
# }

// go get github.com/webscraping-ai/webscraping-ai-go/v4
// https://pkg.go.dev/github.com/webscraping-ai/webscraping-ai-go/v4
package main

import (
    "context"
    "fmt"

    webscrapingai "github.com/webscraping-ai/webscraping-ai-go/v4"
)

func main() {
    client, _ := webscrapingai.NewClient(&webscrapingai.Config{APIKey: "YOUR_API_KEY"})
    result, _ := client.Fields(context.Background(), &webscrapingai.FieldsOptions{
        URL: "https://target-company.com/careers",
        Fields: map[string]string{
            "total_openings": "Total number of open positions",
            "departments_hiring": "Which departments are hiring",
            "engineering_roles": "Number of engineering positions",
            "sales_roles": "Number of sales positions",
            "locations": "Locations with open positions",
            "recent_postings": "Jobs posted in the last 30 days",
        },
    })
    fmt.Println(result.Result)
}
// Response:
// {
//   "total_openings": 47,
//   "departments_hiring": ["Engineering", "Sales", "Marketing", "Operations"],
//   "engineering_roles": 23,
//   "sales_roles": 12,
//   "locations": ["San Francisco", "New York", "London", "Remote"],
//   "recent_postings": 15
// }

// Maven: ai.webscraping:webscraping-ai:4.0.0
// https://central.sonatype.com/artifact/ai.webscraping/webscraping-ai
import ai.webscraping.Client;
import ai.webscraping.Config;
import ai.webscraping.option.FieldsOptions;
import ai.webscraping.result.FieldsResult;

Client client = new Client(Config.builder().apiKey("YOUR_API_KEY").build());
FieldsResult result = client.fields(FieldsOptions.builder()
    .url("https://target-company.com/careers")
    .addField("total_openings", "Total number of open positions")
    .addField("departments_hiring", "Which departments are hiring")
    .addField("engineering_roles", "Number of engineering positions")
    .addField("sales_roles", "Number of sales positions")
    .addField("locations", "Locations with open positions")
    .addField("recent_postings", "Jobs posted in the last 30 days")
    .build());
System.out.println(result.getResult());
// Response:
// {
//   "total_openings": 47,
//   "departments_hiring": ["Engineering", "Sales", "Marketing", "Operations"],
//   "engineering_roles": 23,
//   "sales_roles": 12,
//   "locations": ["San Francisco", "New York", "London", "Remote"],
//   "recent_postings": 15
// }

// dotnet add package WebScrapingAI
// https://www.nuget.org/packages/WebScrapingAI
using WebScrapingAI;

var client = new WebScrapingAIClient(new WebScrapingAIClientOptions { ApiKey = "YOUR_API_KEY" });
var result = await client.FieldsAsync(new FieldsRequest {
    Url = "https://target-company.com/careers",
    Fields = new Dictionary<string, string> {
        ["total_openings"] = "Total number of open positions",
        ["departments_hiring"] = "Which departments are hiring",
        ["engineering_roles"] = "Number of engineering positions",
        ["sales_roles"] = "Number of sales positions",
        ["locations"] = "Locations with open positions",
        ["recent_postings"] = "Jobs posted in the last 30 days",
    },
});
Console.WriteLine(result.Result);
// Response:
// {
//   "total_openings": 47,
//   "departments_hiring": ["Engineering", "Sales", "Marketing", "Operations"],
//   "engineering_roles": 23,
//   "sales_roles": 12,
//   "locations": ["San Francisco", "New York", "London", "Remote"],
//   "recent_postings": 15
// }

Surface executive announcements from press releases

curl -G "https://api.webscraping.ai/ai/question" \
  --data-urlencode "api_key=YOUR_API_KEY" \
  --data-urlencode "url=https://target-company.com/press" \
  --data-urlencode "question=What are the most recent announcements? Are there any executive changes, partnerships, or product launches mentioned?"

# pip install webscraping_ai
# https://pypi.org/project/webscraping-ai/
from webscraping_ai import Client

client = Client(api_key="YOUR_API_KEY")
answer = client.question(
    "https://target-company.com/press",
    question="What are the most recent announcements? Are there any executive changes, partnerships, or product launches mentioned?",
)
print(answer)

// npm install webscraping-ai
// https://www.npmjs.com/package/webscraping-ai
import { WebScrapingAI } from 'webscraping-ai';

const client = new WebScrapingAI({ apiKey: 'YOUR_API_KEY' });
const answer = await client.question({
  url: 'https://target-company.com/press',
  question: 'What are the most recent announcements? Are there any executive changes, partnerships, or product launches mentioned?',
});
console.log(answer);

<?php
// composer require webscraping-ai/webscraping-ai-php
// https://packagist.org/packages/webscraping-ai/webscraping-ai-php
require 'vendor/autoload.php';

use WebScrapingAI\Client;

$client = new Client('YOUR_API_KEY');
$answer = $client->question(
    'https://target-company.com/press',
    'What are the most recent announcements? Are there any executive changes, partnerships, or product launches mentioned?',
);
echo $answer;

# gem install webscraping_ai
# https://rubygems.org/gems/webscraping_ai
require 'webscraping_ai'

client = WebScrapingAI::Client.new(api_key: 'YOUR_API_KEY')
answer = client.question(
  'https://target-company.com/press',
  question: 'What are the most recent announcements? Are there any executive changes, partnerships, or product launches mentioned?'
)
puts answer

// go get github.com/webscraping-ai/webscraping-ai-go/v4
// https://pkg.go.dev/github.com/webscraping-ai/webscraping-ai-go/v4
package main

import (
    "context"
    "fmt"

    webscrapingai "github.com/webscraping-ai/webscraping-ai-go/v4"
)

func main() {
    client, _ := webscrapingai.NewClient(&webscrapingai.Config{APIKey: "YOUR_API_KEY"})
    answer, _ := client.Question(context.Background(), &webscrapingai.QuestionOptions{
        URL:      "https://target-company.com/press",
        Question: "What are the most recent announcements? Are there any executive changes, partnerships, or product launches mentioned?",
    })
    fmt.Println(answer)
}

// Maven: ai.webscraping:webscraping-ai:4.0.0
// https://central.sonatype.com/artifact/ai.webscraping/webscraping-ai
import ai.webscraping.Client;
import ai.webscraping.Config;
import ai.webscraping.option.QuestionOptions;

Client client = new Client(Config.builder().apiKey("YOUR_API_KEY").build());
String answer = client.question(QuestionOptions.builder()
    .url("https://target-company.com/press")
    .question("What are the most recent announcements? Are there any executive changes, partnerships, or product launches mentioned?")
    .build());
System.out.println(answer);

// dotnet add package WebScrapingAI
// https://www.nuget.org/packages/WebScrapingAI
using WebScrapingAI;

var client = new WebScrapingAIClient(new WebScrapingAIClientOptions { ApiKey = "YOUR_API_KEY" });
var answer = await client.QuestionAsync(new QuestionRequest {
    Url = "https://target-company.com/press",
    Question = "What are the most recent announcements? Are there any executive changes, partnerships, or product launches mentioned?",
});
Console.WriteLine(answer);

Benefits for Investment Firms

Unique Signals: Access data not available in traditional feeds.

Leading Indicators: Detect trends before they appear in financials.

Custom Data Sets: Build proprietary data assets.

Flexible Schema: Extract exactly the data points you need.

API-First: Easy integration with existing data pipelines.

Alternative Data Types

Job Posting Data

Track hiring velocity as a growth indicator

Pricing Intelligence

Monitor competitor and market pricing

Web Traffic Proxies

Estimate consumer interest and demand

News & Sentiment

Track news flow and market sentiment

Related Use Cases

Start Collecting Alternative Data

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Alternative Data for Investment