The Unified Financial Data Core

All your market, macro and analytics data in ONE API

JungleTrade brings together real-time and historical prices, indices, macro data, indicators, models and triggers into a single, unified API — so you can focus on building strategies and products, not maintaining data pipelines.

API Documentation

Products

  • Market Prices
  • Historical Data
  • Real-time Feeds
  • Economic Indicators
API Response
[
  {
    "price": 79719,
    "timestamp": 1778763660000
  },
  {
    "price": 79767.11,
    "timestamp": 1778763600000
  },
  ...
]
Who It's Built For

Built for the Architects of Trading

We understand your pain points. Whether you build models, "read tape", or manage capital — JungleTrade is designed around the workflows of modern market professionals

For Professional Traders

Gain deeper visibility into market sentiment, liquidity, and macro conditions.

Use realtime analytics and trading triggers designed for professional market participants.

For Institutions

Enterprise-grade market infrastructure.

Built for funds and institutional trading teams requiring reliable market data infrastructure at scale.

For Automated Trading Platforms

Scalable infrastructure for automated trading ecosystems.

Combine market data, macro intelligence, analytics, and realtime triggers into a unified automation layer.

Production-Ready Infrastructure

Performance at Scale

Data Delivery
24/7
Historical and realtime market data infrastructure for quantitative workflows.
Real-Time Performance
0ms
Low-latency infrastructure for realtime market delivery.
Archive Acceleration
0ms
Fast access to historical datasets and analytics infrastructure.
Technical Integration

Easy to integrate

Power your trading and monitoring infrastructure with realtime, historical, and analytics datasets delivered through a unified API layer. Integrate market intelligence into dashboards, trading systems, analytics workflows, and financial platforms.

Quick start in 3 steps

  1. 1
    Request Your API Key

    Access to the API requires authentication credentials. Contact our team to receive your API key and enable access to JungleTrade infrastructure and datasets.

  2. 2
    Authenticate your requests

    Integration is straightforward. Include your API key in the header of every request:

    X-Api-Key: YOUR_API_KEY
  3. 3
    Make your first request

    Send authenticated REST requests from any standard HTTP client to access realtime and historical financial datasets.

C:\Windows\System32\cmd.exe
Modular Precision for Institutions

The Engine Room: Modular Alpha for the Modern Architect

Stop trading on filtered noise. Access our core 'Titans'—modular, high-performance data streams designed for institutional-grade precision. Pick your components, fuel your API, and build the edge that others can't see.

MENTIS: News Sentiment

M1
Models

News analysis tool that generates structured impact scores, direction, time horizon, and affected entities for trading and analytics systems.

Impact ScoresSentiment Data
The Problem
  • Unstructured information flow
  • Delayed signal generation
  • Limited market context extraction
Our Solution
  • Structured impact scores
  • Directional sentiment analysis
  • Confidence-weighted output
Usage via API
GET /v1/mentis/sentiment Response: { score: 0.87, direction: "bullish", entity: "BTC" }
View Docs
Usage via UI

Monitor live sentiment flows, filter by asset or time horizon, and visualize impact scores across your watchlist at a glance.

OMNIS: Market Condition Model

M2
Models

OMNIS is a market condition modeling system that generates a unified view of crypto market behavior by aggregating News Sentiment outputs over time. The model combines weighted sentiment scoring, confidence-adjusted analysis, and time-decay methodologies to identify evolving market conditions, directional bias, and broader sentiment regimes across the digital asset ecosystem.

Aggregated SentimentMarket RegimesDirectional BiasCrypto Intelligence
The Problem
  • Fragmented market sentiment signals
  • Excessive short-term informational noise
  • Difficulty detecting market regime transitions
Our Solution
  • Unified market condition representation
  • Weighted temporal aggregation
  • Confidence-adjusted sentiment modeling
Usage via API
GET /v1/omnis/condition Response: { condition: "bullish", score: 0.72, confidence: 0.89 }
View Docs
Usage via UI

View aggregated market conditions across time horizons with confidence metrics and trend visualizations.

Coming Soon

HELIOS: India Regional Price Network

D32
Data

The most granular regional price network for Gold and Silver in India, covering 50+ major cities and regions with local market dynamics.

IndiaRegional PricingAsia-PacificLocal Markets
The Problem
  • No regional price visibility
  • Missing local market data
  • Lack of intra-city analytics
Our Solution
  • 50+ Indian regional locations
  • City-specific price discovery
  • Hyper-local market analytics
Usage via API
GET /v1/helios/india Response: { mumbai: 60750, delhi: 60800, bangalore: 60725 }
View Docs
Usage via UI

Explore regional gold and silver prices across 50+ Indian cities with local market trend analysis.

M1

MENTIS: News Sentiment

Trusted By Traders

What Professionals Are Saying

From independent alpha traders to institutional capital managers—built for those who demand precision at every layer.

JungleTrade puts market data, indicators, models, and triggers in one integrated environment. Everything in one place, which makes building trading and monitoring systems far more efficient. I built it into dailymarket.report and would recommend it without hesitation.

Vladislav Dramaliev

Founder, Bithope Foundation

dailymarket.report

As developers, speed, reliability, and data consistency are critical for us. JungleTrade provides fast APIs, structured market data, and analytical models within a single integrated environment, significantly simplifying the development of trading and monitoring systems.

Ivaylo Borisov

CTO, Serial entrepreneur

Production-ready in minutes—no messy docs, just a clean X-Api-Key integration. The archive acceleration is the real highlight; pulling massive historical datasets with 200ms response times has made our backtesting cycles significantly faster.

Liam Sterling

Lead Quant Developer