ORVYX FOR AGENCIES
Run every client from one system, without blending them.
An agency's hardest problem is not producing work. It is that every client is a separate world, and one mistake in context handling costs the relationship. Orvyx is designed to make that separation structural rather than a matter of discipline.
Orvyx AI is in private beta. What follows is designed to describe the operating model, not a list of features you can use today.
THE PROBLEM
What you are doing by hand today.
Context bleeding between clients
Voice, audience, and history crossing accounts because separation relies on everyone remembering it.
Onboarding rebuilt each time
The same setup work repeated per client, per project, per campaign.
Approvals chased by hand
Tracking what is waiting on which client, across people and threads.
Capacity invisible
Not knowing workload or utilisation until someone is already overloaded.
Margin discovered late
Finding out a project was unprofitable after the work is done.
Renewal risk noticed late
Client health as a feeling rather than as a signal you can see.
WHAT ORVYX TAKES OVER
The coordination you stop doing by hand.
Separates client context structurally
Brand, audience, campaigns, approvals, history, and agent context are designed to stay partitioned per client.
Standardises onboarding
Client setup is designed to be a repeatable intake rather than bespoke work each time.
Coordinates delivery
Research, campaigns, agents, content, and approvals are designed to stay attached to the correct account.
Surfaces account risk
Account health and renewal risk are designed to be visible before the client raises them.
Surfaces exceptions only
The intent is exception-only management: review what needs attention, not every workflow.
THE ENGINE, FOR YOU
What is designed to be available to you.
- Client onboarding
- Isolated client context
- Client-specific agents
- Client context firewall
- Campaigns
- Approvals
- Client approvals
- Client portal
- Campaign recovery
Workload · Utilisation · Margin · Profitability · Account health · Renewal risk · Upsell · Resource allocation · Proposal support
- Workload
- Utilisation
- Margin
- Profitability
- Account health
- Renewal risk
- Upsell
- Resource allocation
- Proposal support
Reporting · White-label reports · Competitor monitoring · Outcome tracking
- Reporting
- White-label reports
- Competitor monitoring
- Outcome tracking
CORE ORVYX ENGINES
The same operating layer, weighted for you.
- Understand
- A Context Firewall is designed to keep one client's knowledge out of another client's work.
- Decide
- Client objectives and constraints are designed to be explicit, so scope creep has something to check against.
- Execute
- Client-specific agents are designed to run against partitioned context rather than a shared pool.
- Control
- Approvals, resource limits, and exception-only review are designed per account.
EXAMPLE OBJECTIVES
What you would actually ask for.
Onboard this new client and draft the first campaign plan
Intake, context capture, and a plan generated from that client's material only.
Show me every approval waiting on a client this week
One queue across accounts, with what each approval is blocking.
Which accounts are at renewal risk, and why
Account health signals surfaced against delivery, engagement, and scope.
Compare utilisation across the team this month
Where capacity went, and which projects are consuming it.
APPROVAL AND CONTROL
You are in charge of what runs.
- Client approvals are first-class. A client is designed to be able to approve or reject work without internal mediation.
- Budgets are scoped per account. Spend and compute limits are designed to be enforceable per client, not globally.
- Context is partitioned. One client's information is designed to be unable to appear in another client's output.
- White-label reporting. Client-facing reporting is designed to carry your brand, not the operator's.
Security agents are designed to defend, contain, and report. They are not designed to autonomously rewrite production systems.
OUTCOMES AND LEARNING
Every completed task makes the next one better.
- Decision
- What was committed to the client.
- Action
- What was delivered, and what was approved.
- Outcome
- Performance against what was promised.
- Evidence
- The data behind the claim, with correlation marked as correlation.
- Learning
- What is designed to inform the next pitch or renewal.
Attribution is designed to distinguish correlation from causation, and to say plainly when it cannot.
DIRECT ANSWERS
Questions, answered plainly.
How can agencies use Orvyx?
Orvyx is being designed for agencies around structural client isolation. Client context, campaigns, approvals, reporting, and agent context are intended to stay separated per account, while delivery is coordinated from one system. Supporting capabilities include client onboarding, client-specific agents, approvals, a client portal, white-label reporting, and commercial signals such as workload, utilisation, margin, account health, and renewal risk. This is designed capability, not currently available functionality.
Can agencies keep client data isolated?
Client isolation is a stated design goal, backed by a Context Firewall. Orvyx is intended to keep one client's information out of another client's output rather than relying on process discipline. This is designed behaviour, not yet generally available.
How does Orvyx handle client approvals?
Approvals are designed as a first-class part of the workflow rather than an email thread. Work is intended to be held at an approval point until a decision is made, with the intent that a client approves or rejects directly.
Is Orvyx available for agencies now?
Orvyx AI is in private beta and public availability has not been announced. The homepage collects waitlist interest. Capabilities on this page are described as designed or being built, and are not yet generally available.
CONTEXT CREATES EVERYTHING.
Stop managing clients from separate inboxes.
One operating layer, partitioned per account.