Data That Moves Before the Market Does

Research-grade data with full history, normalized and ticker-mapped across every dataset. Granular enough for backtesting, clean enough for production.

AI Price Forecasts

Daily and monthly AI price forecasts with confidence intervals.

Analyst Ratings

Track analyst upgrades, downgrades, and price target changes from major institutions.

Insider Trading

Real-time SEC Form 4 filings. Track executive purchases, sales, and option exercises.

Put/Call Ratios

Options market sentiment data. Monitor put/call ratios and options flow signals.

News Sentiment

AI-powered sentiment scores from financial news. Gauge market mood and momentum.

LinkedIn Metrics

Track employee counts and follower growth. Early indicators of company trajectory.

App Store Ratings

Mobile app performance data from iOS and Android stores. User sentiment signals.

Reddit Mentions

Track ticker mentions across Reddit communities like WallStreetBets and r/stocks.

Congressional Trades

Monitor US House Representatives trading activity. Disclosure-based signals.

Corporate Lobbying

Federal lobbying disclosures. Track corporate influence and regulatory exposure.

Coming Soon

Government Contracts

Federal contract awards and modifications. Revenue signals from government spending.

Coming Soon

Patent Filings

Track patent applications and grants by ticker. Early signals of innovation and R&D activity.

25,000+

Tickers Covered

20

Global Markets

10+

Datasets

70+

Countries Served

99.9%

API Uptime

REST API & SDKs

One integration for your engineering team. Build trading systems, research platforms, and client-facing applications in days.

Deploy in Hours, Not Months

A single REST API with full historical data and consistent schema across all datasets. One integration covers everything — no vendor patchwork, no missing history.

Unified schema, all datasets - Consistent endpoint structure eliminates per-vendor integration work
Python SDK - pip install finbrain-python for rapid prototyping and production use
High-throughput access - Built for backtesting, live trading, and platform integrations
Full data history - Years of granular historical data for backtesting, model training, and research

Get Started Python SDK Docs

from finbrain import FinBrainClient

fb = FinBrainClient(api_key="YOUR_API_KEY")

# Get AI predictions
predictions = fb.predictions.ticker("AAPL",
    as_dataframe=True)

# Get insider trading data
insider = fb.insider_transactions.ticker("AAPL",
    as_dataframe=True)

# Get news sentiment
sentiment = fb.sentiments.ticker("NVDA",
    as_dataframe=True)

# Get AI predictions
curl -H "Authorization: Bearer YOUR_API_KEY" \
  "https://api.finbrain.tech/v2/predictions/daily/AAPL"

# Get insider transactions
curl -H "Authorization: Bearer YOUR_API_KEY" \
  "https://api.finbrain.tech/v2/insider-trading/AAPL"

# Get sentiment data
curl -H "Authorization: Bearer YOUR_API_KEY" \
  "https://api.finbrain.tech/v2/sentiment/NVDA"

const headers = { "Authorization": "Bearer YOUR_API_KEY" };
const BASE = "https://api.finbrain.tech/v2";

const predictions = await fetch(
  `${BASE}/predictions/daily/AAPL`, { headers }
).then(res => res.json());

const insider = await fetch(
  `${BASE}/insider-trading/AAPL`, { headers }
).then(res => res.json());

#include <curl/curl.h>
#include <nlohmann/json.hpp>

json get_predictions(const std::string& symbol,
                     const std::string& api_key) {
    CURL* curl = curl_easy_init();
    std::string response, url =
      "https://api.finbrain.tech/v2/predictions/daily/" + symbol;
    std::string auth = "Authorization: Bearer " + api_key;
    struct curl_slist* hdrs = curl_slist_append(nullptr, auth.c_str());

    curl_easy_setopt(curl, CURLOPT_URL, url.c_str());
    curl_easy_setopt(curl, CURLOPT_HTTPHEADER, hdrs);
    curl_easy_setopt(curl, CURLOPT_WRITEDATA, &response);
    curl_easy_perform(curl);
    curl_slist_free_all(hdrs);
    curl_easy_cleanup(curl);
    return json::parse(response);
}

use reqwest::blocking::Client;
use reqwest::header::{AUTHORIZATION, HeaderValue};

fn get_predictions(symbol: &str, api_key: &str)
    -> Result<serde_json::Value, reqwest::Error> {
    let url = format!(
        "https://api.finbrain.tech/v2/predictions/daily/{}",
        symbol
    );
    Client::new().get(&url)
        .header(AUTHORIZATION, HeaderValue::from_str(
            &format!("Bearer {}", api_key)).unwrap())
        .send()?.json()
}

FinBrain Terminal

Visual analytics for team members who need insights without writing code.

Point-and-Click Alternative Data

Give analysts, PMs, and research teams direct access to all FinBrain datasets through an intuitive dashboard. No engineering tickets required.

AI price predictions - Daily and monthly forecasts for all tickers
Alternative data insights - Insider trades, congressional activity, sentiment scores
Interactive charts - Visualize predictions, sentiment trends, and insider activity
Stock screeners - Filter 25,000+ tickers by AI signals, insider buying, and more
Portfolio tracking - Monitor holdings with customizable team dashboards

Get Started Terminal Docs

MCP for LLM Integration

Give your team's AI assistants direct access to FinBrain data. Accelerate research workflows across the organization.

AI-Native Data Access

Use the Model Context Protocol (MCP) to connect FinBrain data to Claude, ChatGPT, and custom LLM applications. Multiply analyst productivity.

Natural language queries - Analysts query predictions, insider trades, and sentiment in plain English
Claude Desktop integration - Just pip install finbrain-mcp and add your config
Custom LLM apps - Build internal research copilots and client-facing AI tools
Real-time data - Always current market intelligence across your team’s AI workflows

Get Started MCP Docs

”Compare AI predictions for our portfolio holdings"

"Show insider trades for AAPL in the last 30 days"

"How has sentiment shifted across our S&P 500 coverage?"

"Flag congressional trades that overlap with our positions”

Plans That Scale With Your Team

From individual seats to custom enterprise plans. Scale as your team grows.

Monthly Annual Save 17%

Individual

$149 /month

All 10+ alternative datasets
25,000+ tickers across 20 markets
Interactive charts
Alternative data screeners
Portfolio tracking
Recent data history
Daily and monthly predictions
Email support

Get Started

Individual

$499 /month

Everything in FinBrain Terminal
Full data history
Full REST API access
2,000 API requests/hour
Python SDK included
MCP for LLM integration
Custom integrations
Priority support

Get Started

For Teams

Custom

Everything in Terminal + API
Dedicated account manager
Custom data delivery
SLA guarantees
On-premise deployment options
Custom rate limits
Custom integrations
White-label solutions

Book a Demo

Frequently Asked Questions

Common questions about integration, coverage, and enterprise plans.

Getting Started

Questions about API access and setup.

Data & Coverage

What data is available and how often it updates.

Pricing & Support

Subscription plans and support options.

How do I get started?

Sign up at terminal.finbrain.tech for instant access. Most users are in production within a day. Enterprise clients can contact sales for guided onboarding.

What programming languages are supported?

We provide an official Python SDK with pip install finbrain-python. For other languages, use our REST API directly with any HTTP client.

What are the rate limits?

Individual plans include 2,000 requests per hour. Enterprise plans offer custom rate limits to match your team's throughput requirements.

Can we redistribute or display the data to clients?

Redistribution and client-facing display rights are available with our Enterprise plan. Contact sales to discuss licensing for your use case.

What markets are covered?

We cover 20 global markets including US equities (S&P 500, NASDAQ, NYSE), international stocks, forex, crypto, and commodities. Over 25,000 tickers with daily predictions.

How often is the data updated?

AI predictions update daily before market open. Insider transactions and congressional trades update in real-time as filings are published. Sentiment scores update throughout the trading day.

How far back does historical data go?

Historical data varies by dataset. AI predictions have 5+ years of history for backtesting. Insider and congressional data goes back to when disclosure requirements began.

How should we evaluate the AI predictions?

Our deep learning models are trained on historical price data and alternative signals. Full historical data is available for independent backtesting. See our backtesting guide for methodology.

What plans are available for teams?

FinBrain Terminal at $149/month and Terminal + API at $499/month for individual users. Enterprise plans offer custom pricing with SLAs, dedicated support, and custom rate limits for teams and institutions.

What support is available?

All plans include email support. Terminal + API plans include priority support. Enterprise clients get a dedicated account manager and SLA-backed response times.

What does the Enterprise plan include?

Custom rate limits, dedicated account management, SLA guarantees, custom data delivery formats, and on-premise deployment options. Enterprise plans are tailored to your team's specific requirements.

Can we start with an individual plan and upgrade later?

Yes. Many teams start with an individual Terminal + API plan for evaluation, then upgrade to Enterprise as they scale. Your data and integrations carry over seamlessly.

Alternative Data for Systematic Edge

Data That Moves Before the Market Does

REST API & SDKs

Deploy in Hours, Not Months

FinBrain Terminal

Point-and-Click Alternative Data

MCP for LLM Integration

AI-Native Data Access

Plans That Scale With Your Team

FinBrain Terminal

Terminal + API

Enterprise

FinBrain Terminal

Terminal + API

Enterprise

Frequently Asked Questions

Getting Started

Data & Coverage

Pricing & Support

How do I get started?

What programming languages are supported?

What are the rate limits?

Can we redistribute or display the data to clients?

What markets are covered?

How often is the data updated?

How far back does historical data go?

How should we evaluate the AI predictions?

What plans are available for teams?

What support is available?

What does the Enterprise plan include?

Can we start with an individual plan and upgrade later?