Raily · data infrastructure for the agentic economy

    Your data enabled for any AI experience

    Raily is the layer for data to exist inside AI. We power the access, usage and economics of every AI interaction with your data, at scale.

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    Sources

    Connect your existing data stack.

    Databases, storage systems, CRMs, CMSs, vector databases, and file repositories. Raily turns them into AI-ready endpoints with an easy integration.

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    Why Raily

    One control plane for any AI access.

    Transform data into AI-ready endpoints and deliver it across AI applications and agents. Support text, images, video, web content, with any authentication model from a single platform. Bring your own infrastructure or host on Raily. Everything needed to make data AI-ready is built in, getting you up and running in days.

    Single control planeManage access, authentication, analytics, and distribution across every AI channel from one place.
    Built for any AI surfaceSupport GPT apps, MCP, SDKs, APIs, agents, and future protocols without rebuilding integrations.
    Flexible deploymentKeep data where it is or run on Raily-managed infrastructure with the same capabilities.
    FAQ

    Questions about Raily, answered.

    Answers to the questions teams ask most.

    What is Raily?

    Raily is the layer for data to exist inside AI. It turns a source you already own into a governed AI endpoint that ChatGPT, Claude, Gemini, Perplexity and any MCP agent can search. Every answer stays grounded in your data, and every query is logged.

    Which AI assistants and agents can connect to Raily?

    Any assistant that speaks MCP, the Model Context Protocol. That includes ChatGPT, Claude, Gemini, Perplexity, Mistral, Microsoft Copilot and Cursor, plus automation platforms like n8n, LangChain, Slack and Teams. You publish your endpoint once and every MCP client can reach it.

    Is my data used to train AI models?

    No. Your data is never trained on. Raily serves grounded answers from your content at the moment of each query and returns the sources it used, so your content answers questions without ever becoming part of someone else's model.

    How do I connect my data to AI with Raily?

    Three parts, and most of the work is on us. On you: point Raily at a source you already own, such as a Pinecone index, a Postgres table, a Salesforce object or a folder of files, and decide who can reach it. On us: Raily profiles the data, generates the search config, turns it into a governed endpoint, and logs every query. For your agents: ChatGPT, Claude or any MCP agent queries it in plain language and gets answers with every source cited.

    What data sources does Raily support?

    Vector databases, SQL and document databases, data warehouses, CMS platforms, file and image stores, websites, spreadsheets and APIs. Named connectors include Pinecone, Salesforce, Contentful, WordPress and Amazon S3, and the list grows as new sources are added.

    What is an MCP endpoint?

    MCP, the Model Context Protocol, is the open standard AI assistants use to reach external tools and data. A Raily endpoint is an authenticated MCP server that exposes your content for search, so any MCP client can query it securely while you stay in control.

    How does Raily keep my content secure?

    Every endpoint requires sign in, so you decide who reaches your content. Access is governed by identity, every query is logged, and answers stay grounded in sources you control. Nothing is exposed to an agent without authentication.

    How is Raily priced?

    Raily meters every query, so you can measure and monetize each AI interaction with your data. You can start free and pricing scales with usage. Book a demo and we will map a plan to your organization's volume and sources.

    Get started

    Make your data part of every AI interaction.

    Deliver content and data through the AI applications and agents your users already use, with governance, analytics, and control from a single platform.