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EntPEP Agent Fleet Manager
How it works Watch the demo
LLM agents for regulated work

Each session starts its own isolated agent.

Approve what it can reach: your files, company data, the web. Nothing else gets in or out, and every prompt, reply and access lands in your own data lake.

Every agent is a sealed unikernel VM: no operating system, no shell, no disk, and no route to the internet. The host makes the approved connections for it, and it runs on your own server.

How it works

A new agent for every session.

Nothing carries over from one session to the next unless you choose to resume it, and nothing is reachable until you approve it.

01

Launch

Each session starts a fresh agent in its own sealed VM. Nothing is shared with other sessions or the host.

02

Approve

Switch on only what the work needs. Every capability starts off, and its choices appear only when you turn it on.

03

Enforce

The database decides which rows an agent sees, not the prompt. Grants are per table and time-boxed.

04

Record

Prompts, replies, queries and blocked attempts are written to your data lake, with signals flagged by severity.

What an agent can reach

Pick the sources. Launch.

Most sessions need one to three sources, and each stays off until you approve it. Audit, skills, sub-agents and archive are on by default, one click away under Advanced. The launch line spells out exactly what the agent may reach before it exists.

Sources · off until you approve them
SharePoint

One SharePoint folder, copied into RAM inside the agent. It is all of SharePoint the agent can reach, and it vanishes when the agent stops.

site · folder · read-only or read-write · 512 MB · 1 GB · 2 GB
Data Lake

Data with row-level authorization: each desk sees only its own rows.

choose a desk · grant tables
Web Search

Policy-filtered results, with guardrails against prompt injection.

filtered
Advanced · on by default
Audit

Prompts, replies and signals are written to the data lake.

five interception hooks
Skills

Approved, pre-loaded skills your team publishes.

skills.md
Sub-agents

Hand a task to a background agent with the same permissions. Its result lands in the parent's workspace.

up to 1 · 3 · 5
Archive

Session context and data can be saved and restored, or opened read-only.

new · resume

More connectors, such as Splunk-style MCPs and other internal systems, are on the roadmap, each behind the same approval.

Where the model runs

Choose the model server. Keep one set of rules.

Every model server runs under the same enforcement: a sealed VM per session, every prompt, model call, tool call and reply intercepted, credentials never shown to the model, and one audit trail.

Model servers

Anthropic, your AWS, or your premises

Admin enables one or more: the Anthropic API, Claude on Amazon Bedrock in your own AWS account (no Anthropic key in the VM), or a private server on your premises, where nothing leaves your network. With more than one enabled, the launch bar offers the choice and Admin sets the default. A sub-agent uses its parent's server.

Labels

No write-down

Every agent is labelled at launch: confidential if it can reach the Data Lake, external if it has Web Search or uses the Anthropic API. Bedrock in your account and your private server count as internal. Nothing moves from a confidential agent to an external one. With “Keep confidential data internal” on, one agent can't be both: the launch is refused and the refusal is audited.

Research sub-agents

Claude researches, the data stays put

The analyst stays confidential on an internal model. A person can hand public research to a sub-agent on Claude with Web Search only: no Data Lake, SharePoint or workspace. The typed task is checked against every value the Data Lake returned to the session and audited in full, and the results flow back to the analyst.

Admin, Model servers: Anthropic API, Amazon Bedrock and Private server, each with its own switch, and a default for new agents.
Admin: switch on the model servers you allow and pick the default for new agents.
A launch with the Data Lake and Web Search on is refused: confidential data stays internal, so an agent with the Data Lake can't use Web Search.
With the policy on, Data Lake plus Web Search is refused before the agent exists.
Why a sealed agent

Governed by construction, not by instruction.

An agent on a laptop inherits everything the laptop can do. An EntPEP agent can only do what was compiled in and approved for this session.

Agent on a laptopEntPEP agent
Reach
Your files, keys, network and every signed-in account.
Only the resources approved for this session.
Tools
A shell and an interpreter: it can run anything.
A fixed, audited tool set compiled into the agent. No shell, no interpreter.
Data access
Whatever your credentials return.
Row-level policy in the database, per desk, plus time-boxed table grants.
Network
The open internet.
No route to the internet: the host makes approved connections for it. No DNS inside the agent.
Leftovers
Files and history stay on the laptop.
RAM only. When the agent stops, its workspace is gone.
Record
Whatever the app chose to log.
Every prompt, reply, query and block in your own data lake.
Patent pending

Every action, intercepted before it takes effect.

EntPEP's patent-pending method intercepts each action an agent requests, evaluates it against centrally managed policy, enforces the decision before the action takes effect, and logs it to one record across users and agents. In Agent Fleet Manager it runs at five points inside every agent.

UserPromptSubmit

Your prompt

Before anything is sent.

PreApiCall

Each model request

Context, memory and history included, before it leaves the agent.

PreToolUse

Each tool call

Before it runs.

PostToolUse

Each tool result

Before the model sees it.

PreResponse

Each reply

Before it reaches you.

Each hook can be switched on or off per agent, and every interception is written to your data lake. The same method governs Claude Code on the laptop and Claude.ai in the browser.

Built for

Real work on real data.

Teams that can't hand an agent the keys to everything, and still need it to read forty files and run the numbers.

Deal teams

Stage a data room into the agent's workspace, search it, and draft the summary. The files never land on a disk.

Desks and analysts

Ask questions of trade and loan data in plain English. Each desk sees only its own rows.

Compliance

Review flagged communications under a time-boxed grant, with every query on the record.

New · insurance claims

Claims pour in. Every decision follows the book.

A live claims queue, one click to take a claim, and an agent that checks it against the policy, the claims guidelines and past decisions before your adjuster or reviewer decides. Two walkthroughs: Property & Casualty (every new claim) and Life & Health (the claims that pend for a person). The model never sees who: names, emails, addresses and policy or member numbers reach it only as stand-ins.

Sample data for a fictional insurer, Brightwater Mutual, and its health plan, Brightwater Health. Agent answers are quoted from real runs on the claims shown.

Why EntPEP: beyond Copilot and agent harnesses

Copilot finds. EntPEP proves.

Copilot answers from the passages most relevant to your question. That's fine for finding a document, and blind to what isn't there. Agent harnesses such as Claude Code make agents capable, but their rules and credentials live where the agent runs. EntPEP's agent gives every file a verdict, checks documents against your systems of record row by row, and compares wording with your house standard word for word, while the rules are enforced from the host, outside the agent. The appliance, not the model, keeps the ledger, and every step lands in your own data lake.

Every file

Completeness sweeps: a verdict for every file in scope, unreadable files listed with the reason, and no report may say “all” or “none” unless a finished sweep backs it.

Every row

Documents against the system of record: every confirmation matched to the trade blotter exactly, including the trades that have no confirmation at all.

Every word

Deviation from house standard: Legal's clause library against every agreement, approved fallbacks recognised, deviations saved as a Word redline.

Recorded live on the EntPEP Agent Fleet Manager; all demo data is simulated. Claude, Claude.ai and Claude Code are trademarks of Anthropic. Copilot is a trademark of Microsoft.

See it in action

One agent per session. Approve what it can reach.

A short walk-through: pick sources and launch a sealed agent, choose where the model runs, see a confidential launch with Web Search refused, hand research to a Claude sub-agent, then watch the database return only one desk's rows, block an ungranted table, and log it all.

Use case

LLMs on your most confidential data, under your control.

A credit risk VP has to decide on a Barclays limit increase the same day. EntPEP lets her use large language models (LLMs) on data classified Confidential and Highly Confidential: it checks every agreement and confirmation, traces every figure to its source, and puts a signed record behind her decision. Simulated data; Barclays is only the example counterparty.

See the actual run on screen: MP4 · PDF

Already using Claude Code or Claude.ai? EntPEP also enforces policy on the endpoint and in the network, under one grant per user. Patent pending.

See the endpoint & proxy demo Sign in
Get started

Launch your first agent.

We'll set up Agent Fleet Manager on your server and connect your first resources.