Aperiodic
DataAlpha
CatalogOrder FlowL1 & L2Derivatives & Market Data
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For AI Agents

The Agent-Friendly Market Data Platform

Aperiodic is built for AI agents. Structured API responses, Python SDK, llms.txt, OpenAPI spec — everything your agent needs to research, analyze, and backtest crypto markets.

Why Agents Need Structured Market Data

Research at Scale

Agents can query 19 datasets across order flow, L1/L2 book data, derivatives, and market OHLCV — programmatically, without manual data wrangling.

Faster Than Manual

What takes a quant hours of data pipeline work, an agent can do in seconds: fetch data, compute signals, evaluate strategies, and report findings.

Point-in-Time Integrity

Every dataset is immutable and exchange-timestamped. Agents get clean, bias-free data without worrying about survivorship or look-ahead issues.

How Aperiodic is Built for Agents

Python SDK

pip install aperiodic — one-line access to every dataset. Agents can fetch DataFrames directly without parsing raw API responses.

View on PyPI →

llms.txt & llms-full.txt

Concise summary at /llms.txt, comprehensive reference at /llms-full.txt — agents get exactly the depth they need.

Read llms-full.txt →

OpenAPI Specification

Full OpenAPI 3.0 spec for tool-use integration. Agents can auto-generate API calls from the spec without custom code.

View OpenAPI spec →

A2A Agent Card

Google A2A-compliant agent discovery at /.well-known/agent.json — capabilities, auth, and skills declared for agent-to-agent orchestration.

View agent card →

AI Plugin Manifest

Standard ai-plugin.json at /.well-known/ai-plugin.json for ChatGPT-style plugin discovery and authentication.

View manifest →

Agent Workflow Examples

Market Research Agent

An agent fetches OHLCV, funding rates, and order flow data to produce a daily market report. It identifies unusual flow toxicity spikes, extreme funding regimes, and OI divergences — then summarizes findings for a human analyst.

ohlcvflowfundingopen_interest

Factor Construction Agent

An agent constructs cross-sectional factors from microstructure data: flow imbalance, funding carry, spread, and volatility factors. It computes information coefficients and long-short portfolio returns to evaluate which signals have predictive power.

flowfundingl1_priceohlcv

Strategy Backtesting Agent

An agent implements and backtests trading strategies using historical data. It fetches order flow and price data, defines entry/exit signals, simulates execution with realistic costs, and reports Sharpe ratios, drawdowns, and win rates.

ohlcvflowimpactfunding

Quick Start

Point your agent to these resources:

LLM summaryaperiodic.io/llms.txt
LLM full refaperiodic.io/llms-full.txt
OpenAPI specaperiodic.io/api.data.specification.json
Agent cardaperiodic.io/.well-known/agent.json
AI pluginaperiodic.io/.well-known/ai-plugin.json
Python SDKpip install aperiodic
Auth headerX-API-KEY: YOUR_KEY

Ready to power your agents?

Get an API key and start querying 19 datasets in minutes.

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Aperiodic

Order flow, liquidity, and derivatives metrics with full exchange universe coverage.

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NOT INVESTMENT ADVICE

The Content is for informational purposes only, you should not construe any such information or other material as legal tax, investment, financial, or other advice. Nothing contained on our presentation constitutes a solicitation, recommendation, endorsement, or offer by Aperiodic or any third party service provider to buy or sell any securities or other financial instruments in this or in in any other jurisdiction in which such solicitation or offer would be unlawful under the securities laws of such jurisdiction.

All Content on this presentation is information of a general nature and does not address the circumstances of any particular individual or entity. Nothing in the presentation constitutes professional and/or financial advice, nor does any information on the Presentation constitute a comprehensive or complete statement of the matters discussed or the law relating thereto.

Aperiodic is not a fiduciary by virtue of any person's use of or access to the Presentation or Content. You alone assume the sole responsibility of evaluating the merits and risks associated with the use of any information or other Content on the Presentation before making any decisions based on such information or other Content. In exchange for using the Presentation, you agree not to hold Aperiodic, its affiliates or any third party service provider liable for any possible claim for damages arising from any decision you make based on information or other Content made available to you through the Presentation.

INVESTMENT RISKS

There are risks associated with investing in securities. Investing in stocks, bonds, exchange traded funds, mutual funds, and money market funds involve risk of loss. Loss of principal is possible. Some high risk investments may use leverage, which will accentuate gains & losses. Foreign investing involves special risks, including a greater volatility and political, economic and currency risks and differences in accounting methods. A security's or a firm's past investment performance is not a guarantee or predictor of future investment performance.