Work with any AI tool and switch anytime

Everything your team builds is stuck inside one company's tool

Your team keeps the AI tools they already chose. What they build is saved in the workspace, so it is not held inside any one product.

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Integrations Workspaces

The Challenge

You standardize on one AI tool, and six months later the better one is somewhere else
Half the team already prefers something different and uses it anyway
Everything the team has built is shaped around one company's product, so moving means building it again
The vendor changes its pricing or its rules, and you find out how little say you have
Telling people which AI to use is an argument you do not win, and should not have to have

The Runwork Solution

Everyone keeps the AI tool they already chose, and the team still works from one shared set of skills and connected tools
60+ AI tools are in the registry, reached over MCP or through synced skills
What the team builds is saved in the workspace rather than inside an AI product, so it is not held anywhere you cannot take it from
Somebody wants to try a new AI tool. They connect it and reach the same skills and the same data, so it is their choice rather than a company decision
You never have to pick one winner for everybody, which is the decision most likely to be wrong in a year

What your team gets

Two people, two AI tools, one set of skills

One works in Claude, one in ChatGPT. Both reach the same saved skills and the same connected data, and neither had to be talked out of their preference.

Where the work is actually stored

Skills, instructions and connected tools sit in the workspace, not inside any AI product. Whichever tool somebody opens, that is what it reads from.

The tool your new hire already knows

They arrive fluent in something nobody else here uses. They connect it and start, instead of spending their first week learning your tool rather than your business.

A vendor announcement that changes nothing for you

Pricing moves, or a product does. It is a question about one tool rather than a question about everything your team has built.

One connection, not one per tool

Your CRM is connected once at the workspace. It does not have to be connected again for each AI tool somebody in the team happens to use.

What the support actually looks like

60+ AI tools in the registry. The main ones are configured over MCP and reach the full shared set; the rest receive the team's synced skills.

A Day in the Life

9:00 AM. Nobody was told what to open. Your analyst works in Claude, your ops lead in ChatGPT, one engineer lives in Cursor. All three reach the same saved skills and the same connected data, because that is held in the workspace rather than in any of the three.

10:30 AM. A new tool turns up. Someone read about a tool nobody here has used and wants to try it. They connect it and it reaches the skills the team has saved. If it is one of the main tools, it reaches the workspace data too. Trying it is now their afternoon rather than a decision somebody has to make on behalf of forty people.

12:00 PM. A new hire starts. They are already good at one particular AI tool and have never opened the one your company pays for. They connect the one they know, and spend their first week on your business instead of on your tooling.

2:00 PM. A vendor announcement. One of the AI companies changes its pricing. Your team reads it as news about one tool. Nothing your team has built is inside that product, so the question is whether anyone wants to move, not what it would cost to.

4:00 PM. A contractor joins for six weeks. They bring their own AI setup, as contractors do. You give them access to the workspace, and they work in the tool they already had open.

5:30 PM. Nothing was standardized today. Five people used four different AI tools and worked from one shared set of skills, data and connections. Nobody had to change how they work for that to be true.

Frequently Asked Questions

Which AI tools does Runwork work with?

Claude, ChatGPT, Cursor, Codex, Copilot, Gemini, Windsurf, Cline and a long list beyond them: 60+ AI tools are in the registry today. They connect either over MCP or through skills synced by the CLI, and new ones get added as they appear, which is the only realistic way to keep up with a category that changes every few weeks.

Does every AI tool get exactly the same thing?

Not identically. The main tools are configured over MCP and reach the full shared set: skills, workspace data and connected tools. The rest, which is most of the 60+ in the registry, receive the team's synced skills without the MCP connection. So somebody on a less common tool still gets what the team has taught its AI, and somebody on a main tool gets that plus live access to your data.

Do we have to standardize on one AI tool?

No, and we would argue against it. Standardizing is a bet on which product is best in two years, and the honest answer is that nobody knows. The reason teams do it anyway is to stop knowledge fragmenting across tools, which is a real problem with a different solution: keep the shared skills and data in one place underneath, and let people choose what they open.

What happens to our work if we change AI tools later?

It is not inside the tool, so there is nothing to move. Skills, instructions, workspace data and connected tools are saved in the workspace, and an AI tool reads from there. Connecting a different tool is the same job as connecting the first one. That is a fact about where things are stored rather than a promise about how a change would go for you.

What about the AI tool somebody uses that we have never heard of?

The registry covers a wide range precisely because teams do not use a tidy list. If something is not in it, that is a gap worth telling us about, since the registry is the part that grows. What does not change is where your team's work is kept, which is the part that would otherwise have to be rebuilt for each new tool.

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