One person behind every session
A session belongs to the person who opened it and is tied to their sign-in at the identity provider. Another person cannot pick it up.
AI agents can use every staff capability over MCP, under the authority of the person they act for. You decide how far each agent may go, from drafting to signing, and the audit trail always shows who did what.
Every agent session belongs to one person and is anchored on that person's own sign-in. The agent gets what the person may do, narrowed by the agent policy you write, and never anything more.
A session belongs to the person who opened it and is tied to their sign-in at the identity provider. Another person cannot pick it up.
The agent policy is applied on top of the person's own policy and can only add restrictions. A missing or failing agent policy denies.
Each session sees only the operations its person may use. A restricted person's agent sees exactly what that person sees.
A download link handed to an agent stops working if its person is disabled after the link was issued.
An agent cannot learn that a record exists if its person may not see it. Search returns nothing the person could not open.
Refused agent actions reach the security event stream, so your security team sees an agent pushing at its limits.
Agents are not handed a chat window on top of a user interface. They reach every staff capability, 142 operations in the current catalog, through a standard MCP server, and never with more than the people they work for.
Typed tools for the everyday work: search, read, history, trace links, draft, capture a record, move it through its lifecycle, complete a task, comment, compare versions.
A generated catalog lets an agent find, read and invoke any other operation its person and your policy allow, so an agent is never limited to a fixed tool list.
Each operation is a read, a write, a write that waits for a person, or a floor act that only a person may perform. A few, such as approving a confirmation, are never reachable by an agent.
Streamable HTTP, an OAuth 2.1 resource server with protected resource metadata, read and write scopes with step-up, and token audiences bound to the MCP resource.
The server passes the official MCP conformance scenarios that apply to a product server.
The server name, its instructions and the confirmation text carry your product name, set in configuration.
Your agent policy answers allow, confirm, or deny for each action and for each lifecycle event. A deployer can require a person's confirmation for any write it chooses, and leave the rest to the agent.
| Answer | What the agent experiences | Example |
|---|---|---|
| Allow | The call runs under the person's permissions and is recorded with the agent session. | Search procedures, draft a revision, capture an event record |
| Confirm | The call waits until the person approves the exact command out of band. | Move a deviation to review, update a draft |
| Deny | The call is refused and recorded; the agent is told it may not. | Anything your policy keeps for people only |
Agent rules live in the same signed configuration release as every other rule, so they are reviewed as a diff and approved by people other than the author.
Rules can look at the tool, the client, the session, its trust level and the preset, as well as the person, the record and its state.
An operation the catalog keeps for people stays with people, whatever a policy says.
High-risk actions are commands computed by the server and confirmed by the person outside the agent's channel. The agent cannot approve its own request.
The person approves a summary built by the server from the exact command, not text the agent chose to show.
Only the person who owns the session can approve, and only with an interactive sign-in inside the signature window.
The command is authorized again under both policies when the person approves it, not only when the agent asked.
If anything the command depends on changed in between, the confirmation fails whole. Nothing is half applied.
A command too large to display in full gets no approve button.
The number of pending confirmations per session is capped, so an agent cannot bury its person in requests.
Prompt injection is handled in the server, not left to the model. When an agent reads text it cannot vouch for, its session loses trust, and lower trust narrows what it may write.
A session starts trusted. Reading another party's text or content that has not been scanned lowers its trust, and it never climbs back within the session.
Policy narrows what a session may write as its trust drops, so text planted in a document cannot widen what the agent may do.
The defense holds even if the model follows the injected text: the server decides what the session may do, not the prompt.
Search hits require access to the content itself, so search cannot reveal what a permission withholds.
The deployer chooses a preset. Under the regulated preset only named people approve and sign. Under the flexible preset you open individual permissions, one switch at a time.
No agent, under any preset, places a legal hold, proposes a disposition, creates a disclosure, erases a person's data, or changes the configuration on its own word.
Creating, widening or ending a share or an inspector session is a floor act for agents unless the flexible preset opens sharing.
Each tool call and agent action is written to the audit ledger with the person and the agent session behind it, in the same chained history as everything people do.
Every entry names the person and the agent session, so a reviewer can tell what a person did from what an agent did on their behalf.
Who approved which command, and when, is recorded beside the action it released.
Agent entries sit in the same hash-chained ledger with signed checkpoints, and verify offline with everything else.
An agent drafts a deviation record, is refused the approval under the regulated preset, and asks. The person confirms out of band with a fresh sign-in, and each step lands on the ledger.
The draft EU GMP Annex 22 keeps generative AI out of critical GMP applications and expects qualified people to stay responsible for AI outputs. Tabellix is built for the human oversight the draft Annex 22 expects for generative AI: under the regulated agent preset, agents draft and named people review, approve, and sign, with every agent action recorded in the audit trail. Validating an AI model remains the regulated user's responsibility.
Frameworks and evidenceNo. Each session belongs to one person, and the agent policy is applied on top of that person's own policy and can only remove permissions. A missing or failing agent policy denies.
Only under the flexible preset, only with the signature meanings the deployer lists, and only while its person's own sign-in is recent enough. The record, the signed page and the audit entry always say the agent applied it for that person. Under the regulated preset, only named people sign.
The server computes the exact command and a summary of it. The person who owns the session approves it outside the agent's channel, with an interactive sign-in inside the signature window, and the command is authorized again at that moment. The agent cannot approve its own request.
In the server. When a session reads another party's text or unscanned content, its trust drops and stays down, and lower trust narrows what it may write. The defense does not depend on the model ignoring the injected text.
MCP clients on the current protocol revision or the previous one. The server passes the official conformance scenarios that apply to a product server, and signs a person in with standard OAuth 2.1.
Every tool call and agent action is in the hash-chained audit ledger with the person and the agent session behind it, and verifies offline with the rest of the history.
Tell us what your agents should do and who answers for it. We'll show you how the presets, the confirmation and the audit trail fit your product.