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EmidLabs — Quant Trading Infra Review

EmidLabs provides infrastructure for quantitative research and market execution, offering APIs for backtesting, live execution, and developing strategies with integration support for AI agents.

shipped Aug 28, 2026codefreemium
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EmidLabs — Quant Trading Infra — product screenshot

Why it matters

1Offers a freemium pricing model, including a Free tier at $0/month with 5 execution units.
2Provides an API-first infrastructure for backtesting and live execution of quantitative trading strategies.
3Supports direct integration with MCP-compatible AI agents like Claude and ChatGPT.
4Features a composable Domain Specific Language (DSL) for defining strategies as structured JSON objects.

About EmidLabs — Quant Trading Infra

Business Model
Subscription SaaS
Free Credits
5 execution units / month
Platforms
Web, API
Target Audience
Developers, quants, and traders

Pricing Plans

Free
$0 / monthly
  • • 5 execution units / month
  • • 1 concurrent live subscription
Explorer
$9.90/mo
  • • 100 execution units / month
  • • 3 concurrent live subscriptions
Research
$29.90/mo
  • • 500 execution units / month
  • • 10 concurrent live subscriptions
Institutional
$99.90/mo
  • • 2,500 execution units / month
  • • 25 concurrent live subscriptions
API Docs

Specs

API Docs

View Documentation →

API Available

Yes, public API

overview

What is EmidLabs — Quant Trading Infra?

EmidLabs — Quant Trading Infra is a quantitative research and market execution infrastructure tool developed by EmidLabs that enables dev-traders, independent quants, and small systematic teams to build and execute quantitative trading strategies. It offers a programmable API for server-side backtesting, live execution, and developing strategies, supporting integration with AI agents without requiring users to build their own environment.

features

Key Features of EmidLabs — Quant Trading Infra

EmidLabs — Quant Trading Infra provides an API-first infrastructure with specific features designed for systematic quantitative workflows. The platform's capabilities are exposed through a programmable interface, allowing for automation and integration.

  • Backtesting API for server-side execution of trading strategies.
  • Live Execution API (beta) for subscribing validated strategies to real-time market data.
  • Hosted Model Context Protocol (MCP) Servers for direct AI agent integration.
  • Composable Domain Specific Language (DSL) for defining strategies as structured JSON objects.
  • Real-time strategy signals based on defined entry and exit conditions.
  • No environment setup required, providing immediate access to infrastructure.
  • Rigorous backtest engine enforcing deterministic execution and configurable risk models.
  • Support for multiple positions, fee simulation, and conservative ambiguity handling in backtests.
  • Strict enforcement of no lookahead bias in all backtesting operations.

use cases

Who Should Use EmidLabs — Quant Trading Infra?

EmidLabs — Quant Trading Infra is designed for specific user segments within the financial technology domain, focusing on programmatic and systematic approaches to market analysis and execution. Its API-first design caters to users who prioritize automation and integration over manual operation.

  • Dev-traders: For building, testing, and deploying custom quantitative trading strategies via API.
  • Independent Quants: For conducting large-scale quantitative research and analysis without managing infrastructure.
  • Small Systematic Teams: For automating research pipelines and integrating trading logic into existing systems.
  • Developers building quantitative infrastructure: For leveraging a pre-built, robust API for backtesting and live execution.
  • AI Agent Developers: For connecting MCP-compatible AI agents (e.g., Claude, ChatGPT) directly to market data and execution APIs.

how to use

How to Use EmidLabs — Quant Trading Infra

EmidLabs — Quant Trading Infra is accessed primarily through its API, allowing users to define and execute strategies programmatically. The platform eliminates the need for local environment setup, enabling immediate development and testing.

  • 1Access the EmidLabs platform via the web interface or directly through its API.
  • 2Define trading strategies using the composable Domain Specific Language (DSL) as structured JSON objects.
  • 3Utilize the Backtesting API to execute server-side backtests and analyze strategy performance.
  • 4Integrate MCP-compatible AI agents (e.g., Claude, ChatGPT) to submit backtests and read results.
  • 5Subscribe validated strategies to the Live Execution API (beta) to receive real-time signals.
  • 6Consult the API documentation at https://emidlabs.com/en/docs for detailed integration instructions and endpoint specifications.

pricing

EmidLabs — Quant Trading Infra Pricing & Plans

EmidLabs — Quant Trading Infra operates on a freemium model, offering multiple tiers to accommodate different usage levels and requirements. Each tier provides a specific allocation of execution units and features.

  • Free: $0/month, includes 5 execution units per month.
  • Explorer: $9.90/month, designed for individual exploration and basic research.
  • Research: $29.90/month, suitable for more intensive quantitative research and development.
  • Institutional: $99.90/month, tailored for professional systematic teams requiring higher capacity and advanced features.

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Pros

  • +API-first design enables extensive automation and integration into existing systems.
  • +Direct integration with MCP-compatible AI agents (e.g., Claude, ChatGPT) simplifies AI-driven strategy development.
  • +Composable Domain Specific Language (DSL) allows for programmatic generation and iteration of strategies.
  • +Server-side backtesting offers rapid execution, with benchmarks showing ~200ms for 5 years of BTC data at 15M timeframe.
  • +Rigorous backtest engine enforces deterministic execution, configurable risk models, and strict no lookahead bias.
  • +Eliminates environment setup, allowing users to focus directly on strategy development and testing.

Cons

  • −Specific user reviews are not readily available, making it difficult to assess broad user reception.
  • −The Live Execution API is currently in beta, indicating potential for ongoing development and changes.
  • −The platform is not designed for retail traders or those seeking a traditional trading platform with dashboards.
  • −Requires programming knowledge to fully leverage its API-first infrastructure and DSL.

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