AI Squared
AI Squared is an enterprise data-and-AI integration platform that connects data sources (Snowflake, BigQuery, Databricks, Redshift, PostgreSQL, S3, Salesforce and more) to AI/ML model endpoints (OpenAI, Anthropic, Google Vertex, AWS Bedrock, SageMaker, WatsonX) and then pushes the resulting insights back into the business applications where work happens. The company acquired Multiwoven, the open-source Reverse ETL / composable CDP project, in 2024 and now develops it as the open core of the platform under AGPL-3.0. Its public REST API at api.squared.ai covers connectors, connector definitions, models, catalogs, syncs, sync runs and sync records, authenticated with a JWT bearer token. AI Squared is SOC 2 Type II certified and ships SaaS, cloud, on-premise and air-gapped federal deployments.
AI Squared publishes 1 API on the APIs.io network. Tagged areas include Data Integration, Reverse ETL, Artificial Intelligence, Machine-Learning, and Customer Data Platform.
AI Squared’s developer surface includes documentation, API reference, getting-started guide, support, engineering blog, pricing, signup flow, and 32 more developer resources.
Kin Score
APIs 1
Individual APIs this provider publishes, each with its own machine-readable definition.
AI Squared API
REST API for the AI Squared platform covering connectors (data and AI/ML sources and destinations), connector definitions and connection checks, models, catalogs, syncs, schedul...
MCP Servers 1
Model Context Protocol servers that expose these APIs to AI agents.
AI Squared Documentation MCP Server
An anonymous, read-mostly MCP server over the AI Squared documentation corpus, advertised by AI Squared at /.well-known/mcp.json on its own documentation host. It exposes docume...
MCP SERVERPricing Plans 1
Published pricing tiers and plan structures.
Rate Limits 1
Documented rate limits and quota policies.
Ai Squared Rate Limits
RATE LIMITSSecurity Posture 4
Authentication, domain security, vulnerability disclosure, and trust-center signals.
Resources
Get Started 3
Portal, sign-up, and the first successful call
Documentation 3
Reference material describing how the API behaves
Agent Surfaces 4
MCP servers, agent skills, and machine-readable catalogs
Design & Contract 6
Pagination, idempotency, versioning, errors, and events
Build 6
SDKs, sample code, and the tooling you integrate with
Access & Security 5
Authentication, authorization, and security posture
Operate 3
Status, limits, changes, and where to get help
Commercial 4
Pricing, plans, and the legal terms of use
Company 3
The organization behind the API
Other 2
Properties that don't map to a standard resource type
Source (apis.yml)
Work with this as data
Every provider here is available over the APIs.io API and to AI agents over MCP.