Secure Vault
01Credentials, files, and company context. Agents use them without ever seeing the secrets.
Manifesto
Your company will run dozens of agents. Worklayer is the one place they all work from: your context, your tools, your rules, and everything they learn.

Correlating Sentry regressions with PostHog cohorts and Graphite PRs...
The short version
Models will keep improving. Agents will keep changing. The thing worth owning is the place where they do the work.
Your company won’t run one agent. Engineering will live in Claude Code and Cursor. Ops will use Claude. Sales will buy a vertical agent. Someone will build an internal one next quarter, and an open-source model will be good enough for half the work by the end of the year.
Each one arrives with its own memory, its own app connections, its own permissions, and its own way of running work. So every time a team teaches an agent how the company works, that knowledge lands inside one vendor’s product. It can’t be audited in one place. It can’t be handed to another agent. And it leaves when the vendor does.
The better agents get, the faster your company’s know-how scatters.
Today, the agent and the place it works are sold as one product. Adopt the agent and you also adopt where your context lives, how permissions work, and where work runs.
Worklayer pulls them apart. The company owns the environment, and any approved agent plugs into it. Context, tools, rules, and saved work stay with you, not with the vendor. A simple agent becomes powerful when it walks into the right office.
So you never have to pick a winner. If Claude gets better, it gets better inside your office. If a cheaper model shows up tomorrow, it starts on day one knowing everything the last one knew.
Agents are replaceable. What they learned shouldn’t be.
An office gives people what they need to do the job: resources, a place to work, rules to follow, and a sense of what’s worth doing. Worklayer gives agents the same four things. None of it resets when the conversation ends.
Credentials, files, and company context. Agents use them without ever seeing the secrets.
A sandbox where agents write and run code across your apps, in one pass instead of one tool call at a time.
Policies, approvals, and an audit trail that apply the same way to every agent.
Notices the work people repeat and suggests turning it into something any agent can run.
A support lead uses Claude to work out how to triage refund requests: which Stripe fields matter, when to escalate, what to tell the customer. They save it to Worklayer.
That night, an internal agent runs the same process on the overnight queue. A week later, finance uses it from Codex to reconcile disputes. Nobody rebuilt anything. Nobody switched agents.
Every saved process, permission, and piece of feedback makes the next agent more useful. Over time it adds up to a map of how your company actually works: people, apps, data, rules, and the agent activity between them. That map belongs to you.
Nothing an agent learns here has to be learned twice.
The AI stack is pulling power inward: toward the labs that own the models, the products that own the interfaces, and the vendors that own the places agents work. Each layer makes it a little harder to leave.
Worklayer pushes it the other way. Let agentic work spread as fast as your teams want, and keep the controls, the context, and the history somewhere you own. Switch models, mix vendors, and experiment without rebuilding anything.
The intelligence can be rented. The know-how should be owned.
Agent adoption is slow for an awkward reason: to get productive with agents, people first have to be unproductive. They learn what agents can do, connect their tools, gather context, and debug their first workflows before anything pays off.
Worklayer shortens that part. It works with the agents and apps people already use, so one person can connect it to their current agent and feel the difference the same day.
Then it spreads in a way single-vendor tools can’t. A process one team works out in Claude can be picked up by another team in ChatGPT, Codex, Notion, or an internal agent. Every team that joins makes the office more useful for the next one.
End state
get agents that already know how the company works, without becoming agent experts.
get one place to set permissions, approve actions, and audit every agent.
gets vendor independence, and keeps the company’s know-how under its own roof.