Remesh Connect: Bring Your Data and Remy Wherever You Work

Research shouldn't have to live inside one platform, and your organization's data shouldn't have to either.

Remesh Connect makes both possible. Work with your Remesh data and Remy's agentic ability directly inside the AI tools your team already uses, like Claude or ChatGPT, or bring your enterprise data, like your HRIS and other systems, into Remesh, so Remy has more context to build on. Either way, the power of Remesh and Remy travels with you, so you can get the most out of your data while working out of the tools that work best for your team.

Bring Remesh into the tools you already use

Your research belongs to you, and it should work wherever you do. Starting now:

• Connect your own AI directly to Remesh. Our Model Context Protocol (MCP) server lets your team plug Claude, ChatGPT, or any supported MCP client straight into your Remesh workspace. Browse conversations, build and manage studies, and run Remy's analysis from inside your own tools, with the same citations you get via Remy, so every answer links back to the source. Access is authenticated and scoped to what each user can already see in Remesh, and rate limited.
• Take everything with you. Full exports and API access have always been part of Remesh. We will not lock your data in. Ever.

That last point is a commitment, not a feature. Your data is yours. Use the models you choose, on your terms, and check every answer against its source.

Bring your data into Remesh

Connecting your enterprise data into Remesh links Remy to the systems your team relies on, so Remy can understand your existing research and HR data, find the gaps, and run new studies to close them without leaving the platform. As of today you can:

• Bring your files into the conversation. Attach a brief, a prior discussion guide, or background material directly in Remy chat, and Remy uses it as context while planning and building with you.
• Give your survey archives a second life. Import past survey data, including Qualtrics exports, and it becomes a fully analyzable Remesh conversation: ask questions, cut by segments, and get cited answers from research you already paid for.

With Remesh Connect, you can also connect document repositories like Google Drive, OneDrive, and SharePoint, and systems like Workday HRIS and your BI and survey archives. Once connected, Remy can:

• Build context by pulling from sources like your document repositories (Google Drive, OneDrive, SharePoint), HR systems like Workday, and your BI and survey archives
• Identify gaps between what your data already tells you and what you still need to know
• Run the research to close those gaps, directly inside Remesh

That last part is the difference. Remy does not just point out what is missing. It builds and runs the study to go get it.

Because these integrations touch more of your organization's systems, they typically involve more setup, working directly with our team to get connected. If there is a specific system your team depends on, reach out and we will build an integration plan to make it happen.

From research silos to a research flywheel

Here is a scenario that shows what this looks like in practice.

An organization runs its annual engagement survey and sees a dip in one department's scores. In the past, that finding would sit in a slide deck until someone had time to dig into it. With Remesh Connect, Remy flags the dip and can run a new Remesh follow-up discussion with that team right away, asking what has changed and why. From there, Remy connects what the team said to structural data from the company's HR system, like team structure, headcount, and tenure. A pattern emerges: the dip tracks closely with a recent change in team structure.

That is the part generic AI tools cannot do. They can tell you a dip exists and guess at why. Remy goes and asks, in a live study built in minutes and fielded quickly, then connects what it learns back to the rest of your data.

Each study makes the next one sharper too, because Remy draws on a growing, connected base of institutional knowledge instead of starting from zero every time. That is the flywheel: better context leads to better questions, better questions lead to new research, and new research leads to decisions that actually move the organization forward.

Where to start

Remesh Connect meets your team where its data already lives, and where your team already works.

If your team wants Remesh research flowing into its own tools, that is the fastest place to start: connect an MCP client, import a survey archive, or attach files in Remy chat.

For bringing your enterprise data into Remesh, we start with document repositories like Google Drive, OneDrive, and SharePoint, and extend to systems like Workday and your BI and survey archives. A flexible framework lets us bring in other sources as needed. Because these connections touch more of your systems, we work with your team directly to set them up.

See how Remesh Connect can work for you:

Frequently asked questions

What is Remesh Connect?

‍Remesh Connect makes Remesh and Remy more flexible. It lets you work with your Remesh data and Remy's agentic ability from your own AI tools through our MCP server, import survey archives for full cited analysis, and attach files as context in Remy chat. It also can also bring external sources such as Google Drive and Sharepoint into Remesh, to build context for your studies, surface knowledge gaps, and run research that adds to your organization's institutional knowledge.

What can Remesh Connect connect to?

‍For inbound data, Remesh Connect works across document repositories (Google Drive, OneDrive, SharePoint), HRIS systems, and popular BI and survey archive platforms, with a flexible framework for adding other data providers on request. If there is a source your team depends on, let us know.

What is the benefit versus exporting files into Claude or ChatGPT?

‍You do not have to choose. Connect your LLM to Remesh through our MCP server and it gets live, cited access to your research instead of stale exports. And where generic LLMs stop at suggesting what to research next, Remy builds and runs the studies needed to fill those gaps, so you get the missing data rather than just a roadmap for finding it.

What security measures does Remy Connect use? Remy Connect is designed around enterprise security and privacy expectations, guided by a few principles:

• Least-privilege in every direction. When your AI tools connect to Remesh (for example, the Remesh MCP server connected to a Claude, ChatGPT, Gemini, or Microsoft Copilot instance), they can do what that user can already do in Remesh, and nothing more. That includes building and managing studies, so creating, editing, and deleting content is possible, but always within that user's existing workspace permissions, exactly as if they were working in the dashboard. When Remy connects to your data sources, access is read-only: Remy reads only the data you explicitly authorize from each connected source and cannot modify or delete anything in your systems.
• You stay in control. Every connection is set up and authorized by your team and can be revoked at any time. MCP connections are authorized by each user through a standard browser sign-in using OAuth 2.1, scoped to what that user can already see and do in Remesh, and rate limited per workspace and user. Data source connections are set up by your administrators through each system's native access controls.
• Encrypted in transit and at rest. Connections are secured with HTTPS and TLS. Connecting your own AI tools creates no additional copies of your data in Remesh, and any data you import or authorize Remy to read is stored encrypted and scoped to your organization.
• Your data stays yours. We do not use your connected data to train foundation models, and access is scoped to your organization. When you connect your own AI tools, the data you bring into them is governed by your agreements with those providers.
• We work within your compliance framework. We are glad to complete security reviews, execute a data processing agreement, and discuss data residency and specific compliance requirements as part of onboarding.