AI is multiplayer. Run teammates and applications together in one shared runtime.
Turn any workflow into a Sandcastle. A secure, purpose-built app your team and AI teammates can use together.
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Sandcastles open alongside your AI teammates, giving people and agents a shared workspace to collaborate, make decisions, and get work done.
What we allow, who signs off, and how the exceptions turned out.
What would you like to do today, Yara?
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People and AI teammates work the same application at the same time, and you can see who is in it and what they are doing.
The teammate running against an app shows up in that app's presence list the same way a person does, so its work is visible rather than something that happened elsewhere.
Whoever runs the process describes the application it needs and gets a working one back, without waiting on a queue to be staffed.
What they build goes through your approval process on the way to production, so the shortcut is to the first version, not around the review.
Hosting, provisioning and role-based access come from the platform, so putting an application in front of a team does not mean standing up infrastructure for it.
Every application answers to the policies your company already set, and access can be widened or pulled back after it ships.
Turn support, renewals, collections, ecommerce, and manufacturing workflows into AI teammates.
Connect your AI team to the APIs and EDI systems behind each workflow, then wrap every action in policy.
Every action the AI team takes is checked against role-based policy before it can read or write data.
Break your spend into tokens, tool calls, LLM spend, and tool spend, so teams can see what a workflow costs, compare it to business impact easily, and optimize usage.
Break total token costs down by AI teammate instead of hiding them in a blended platform bill.
Model costs stop being a blended line item and become something operations teams can actually tune.
Track connector and action costs alongside model usage instead of hiding them in platform overhead.
Every workflow shows the model spend, tool spend, total, and share of the monthly bill.
Find expensive runs and agents, and tighten workflows before usage drifts.
See which AI teammates, models, and tool calls drive spend so teams know where to optimize.
Assist has been the scaffolding that we needed, as people who did not have any software development background, to build exactly what we were looking for.
People's had exact operational workflows to build, but did not have software development capacity inside the team.