Humans. Amplified.

AI that works for you. Not instead of you.

Morgan makes the calls, sends the emails, chases the refunds, books the appointments and follows things up — the everyday admin you never get to. It waits for your yes on anything that matters, and keeps a record of everything.

You set the outcome and the boundaries. Morgan does the work.

morgan.app/home

What's on this morning?

I found 7 things worth your attention. 4 need a decision — starting with a customer escalation. Cursor already found the likely cause.

Dashboard export broken

Today, 08:58
Needs you

A customer needs the dashboard export for tomorrow's board pack. Cursor found the likely cause; a customer-safe update is drafted and waiting for your approval to send.

Watching for replyApprove the customer update
Reading the customer escalation thread…

Needs you

Live
Insurance renewal

Approve a 5-min call?

Morgan calls in your voice, within locked limits.

Approve
Cursor · scoped claim

Read-only repo + logs · 29 min left

Refund missionWatching

A model answers. Morgan governs action.

The model is the smallest part. The value is everything around it: the mandate to act, the limits it can't break, the credentials it never sees, and the receipts it always leaves.

Without Morgan

  • A chatbot gives advice, then hands the work back to you
  • You hand an agent your passwords and hope it behaves
  • Every new model means re-wiring tools, context and trust
  • No record of what was proposed, approved, or actually done

With Morgan

  • Morgan proposes, gets approval, executes, and closes the loop
  • Credentials stay behind Morgan; agents never hold your keys
  • Swap the model underneath; your authority and context persist
  • Every action is payload-bound, policy-checked, and receipted

1 · Real-world execution

It sends, calls, researches, and follows through — end to end.

Beyond answering, Morgan writes and sends email, makes and takes phone calls in your own voice, runs research, and tracks open work until the loop is closed. It is an assistant face on top of a governed execution system.

Dashboard export broken

Today, 08:58
Needs you

A customer needs the dashboard export for tomorrow's board pack. Cursor found the likely cause; a customer-safe update is drafted and waiting for your approval to send.

Watching for replyApprove the customer update

Refund for broken headphones

Today, 09:21
Watching

Return request sent to the retailer after your approval. Return window closes in 4 days. Morgan is watching for a reply and will follow up Friday if it's quiet.

Watching for replyWait for retailer reply (follow-up Friday)

2 · You hold the authority

Propose, approve, execute — approval bound to the payload.

Morgan proposes the precise action first: this call, this recipient, this message, this budget, before this expiry. Your yes is confirmed on your device with Face ID or a passkey and cryptographically signed to that exact payload — so agents can't stretch it, replay it, or backtrack after you grant it.

Needs you · Insurance renewal

Approve a 5-minute call to NorthCare?

Negotiate the renewal down, strictly within limits.

Locked to this exact action

NumberNorthCare retentions
Budget5 min · £0 spend

Allowed

Ask for a discount · cancellation deadline

Not allowed

Accept a contract · share payment details

Confirmed with Face ID — cryptographically signed, bound to this exact action.

In practice

The kind of work Morgan actually does.

From the first fragment to a resolved, receipted outcome — across email, voice, portals, and other agents.

A single gated line

Give out Morgan's number, not yours. It screens callers, routes the ones that matter to you, and handles the rest — your real number stays private.

Calls in your own voice

Chases a refund or negotiates a renewal in a voice that sounds like you — strictly inside the budget, time, and script you approved.

Email, drafted and sent

Reads the thread, drafts a reply in your tone, and sends it once you approve — then watches for the response and follows up.

GP appointment

Reads the NHS app screen, calls the surgery, works through the menu and hold, and brings back slots for you to pick.

Letters and bills

Turns scanned post into evidence, extracts the deadline, prepares the payment, and waits for your yes.

Research that acts

Compares options, gathers the evidence with sources, and turns the result into a proposed action — not just a summary.

A downstream coding agent

Cursor points at Morgan, inherits your tools, and works through a scoped 30-minute claim — no credentials handed over.

Meetings and follow-ups

Joins the call under a summarize-only mandate, captures the actions, and tracks their owners afterwards.

3 · Governs every agent

Morgan is the authority layer every next agent runs through.

Cursor can code, voice agents can call, browser agents can operate the web. They act through Morgan under short-lived, scoped claims — and credentials stay behind the gateway, injected server-side only when an approved action runs. The model never becomes the security boundary.

Cursor

Coding agent · active claim

Expires in 29 min

Allowed

  • Inspect the reporting repo
  • Read related logs
  • Run safe tests

Forbidden

  • Send the customer email
  • Read secrets
  • Deploy to production

Credentials stay behind Morgan's gateway — injected server-side only when an approved action runs.

The idea

Own what lasts. Rent the intelligence.

A model is a utility, like electricity — real value, but interchangeable, and best sourced from whichever provider is strongest today. Everything durable stays yours.

You own — durable

Agency & actions

governed by your authority

Control plane & rules

limits and approvals you set

Data & context

held by you, not fed upstream

Memory & continuity

persists across models and years

Identity & channels

your number, voice, relationships

You rent — swappable

The raw model is a metered, commodity input. Morgan routes to the strongest available and swaps it underneath — your authority, data, memory, and identity never move.

GPTClaudeGeminiLlamanext model
Swap the intelligence anytime — nothing you own changes.

4 · Follows through

It keeps the situation alive until it's resolved — on record.

Morgan watches for replies, promised callbacks, refunds, confirmations, and missed deadlines. Context compounds across channels and time, so it surfaces what needs you rather than waiting to be asked. And as you grant standing rules, it quietly handles more of the routine on its own — always inside the bounds you set.

Watching for replyFollow-up scheduledDeadline tracked
  1. 09:12Matched receipt + photo to order
  2. 09:14Return window detected — 4 days left
  3. 09:16Drafted return request
  4. 09:20You approved the message
  5. 09:21Request sent to retailer
  6. NowWatching for retailer reply

5 · Evidence, not chat history

Everything Morgan sees becomes traceable evidence.

Emails, calls, receipts, screenshots, portal captures, and letters come in as fragments. The original stays intact, Morgan's interpretation is layered on top, and related pieces consolidate into one situation you can trace back to source.

Situation forming

Possible chargeback forming

A dispute notice and an angry customer reply appeared within minutes of each other.

Stripe dispute notice · £480
Customer reply: "I want my money back"
Vo

Voicemail: clinic callback

07:54

Bright Dental

Linked to mission

NC

Insurance renewal — price up 33%

17:19

NorthCare

Linked to mission

6 · A personal OS for your AI

A friendly assistant on top. A secure operating system underneath.

Isolation, wallets, mandates and MCP governance are the foundations; the assistant is just the face. Connect a tool once and every agent beneath it inherits only the access Morgan grants — new agents bootstrap with your tools, skills, memory, wallets and mandates already wired, and no agent ever holds your credentials.

Morgan gatewayConnect onceEvery agent inherits

Tools, skills, memory, mandates, wallets, and credentials live behind Morgan. Downstream agents request claims instead of asking you to wire the same stack again.

Your tools

Gmail
Calendar
Browser portals
Custom MCP

Morgan

Policy, credentials, memory, receipts, and capability routing.

Claims issued per mission
Wallet caps enforced
Audit written automatically

Any agent UI

Cursor
Voice agent
Browser agent
New agents bootstrap from Morgan, not from scratch.

The guarantee

Authority enforced outside the model.

The AI never gets to be the security boundary. Mandates, wallets, short-lived claims, a credential gateway, and receipts mean limits are enforced by the system — not the model's judgment.

Claims, not credentials

Short-lived JOSE claims let agents act through the gateway without ever holding your tokens or keys.

Wallets

Hard caps on money, model spend, tool calls, minutes, emails, and risky actions.

Mandates

Your standing rules decide what can happen automatically and what needs approval.

Audit

Every signal, claim, approval, tool call, and outcome stays inspectable.

How a yes holds

Approval is cryptographic, not a checkbox.

A tap in a chat window isn't authority. Morgan turns your decision into a signed, bound instruction — verified on your device and enforced by the system, not the model.

Signed, not just clicked

Every approval is confirmed on your device with Face ID or a passkey, then cryptographically signed — bound to the exact payload and your identity. A yes can't be forged, replayed, or moved to a different action.

Deterministic outside the model

Once you approve, execution runs a fixed, pinned flow outside the model. The AI can't rewrite the request, widen the scope, or backtrack on what you signed — the payload is locked.

Agents get claims, never keys

Downstream tools and agents act on short-lived JOSE claims issued through Morgan's gateway. Keys stay with your wallets, mandates, and the credential proxy — the model never holds them.

The stakes

Trust is the bottleneck. Morgan is built for it.

Organisations are giving AI the power to act faster than they can safely delegate, bound, approve, and audit it. That gap — not intelligence — is where deployments fail.

~0%

of enterprises expected to demote or decommission agents by 2027 — after governance failures found in production.

0%

of enterprises report an AI-agent security incident or near-miss. The risk is authority, not intelligence.

L3

“Act with Approval” — the tier analysts call hardest. Morgan's home ground, done the non-fake way.

Figures reflect 2026 industry and analyst commentary on autonomous-agent governance.

For people, not just engineers

Advanced AI capability — without becoming a developer.

Turning tools, agents, and safeguards into something that can truly act has been the preserve of specialists and big platforms. Morgan does that assembly for you and hands it over through one simple, controllable assistant — real leverage, with you in authority.

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Early access for people who want AI that works for them — with the final say always theirs.