Service revenue caps at headcount. Agents do not.
Build and run AI-native services for your clients on an operating system you do not have to build. You keep the client, the brand and the expertise. We run everything underneath.
Your workflows, your client, your log.
Every new client means new hires, and every playbook you have refined lives in people's heads. Agents on the Agent OS change the shape of the business: the playbook becomes a workflow you own, customised per client, and revenue scales with your client book.
Own the workflows
Workflow know-how is the moat, not domain knowledge. Your playbooks, customised per client, reusable across every client.
Own the client
Your brand on top, the OS underneath. Per-client licence and metered inference at wholesale; you set the price.
Show the log
Every agent action in a run log your client can read.
Build with us.
The first deployments are built alongside founding partners, around real client work. Your expertise shapes what is built, and the work remains yours to run.
Hiring a CTO to build this from scratch? Don't.
License the OS, put your brand on top, and train your team as operators, not builders. A first workflow can be live in weeks.
Prototype in weeks, not quarters.
Start from the OS and the catalog, not from an empty repository.
A small team runs it.
No platform engineering hires. Your people operate workflows; we run what is underneath.
Your edge is the workflow, not the model.
General intelligence is a race to the bottom. Vertical know-how is what clients pay for.
Everything under your workflows. Nothing to build.
A vault per client
Scopes per team and project. Context compounds inside the client's vault, not inside a vendor.
A memory bank per client
What every workflow learns stays with that client and sharpens your playbook for the next run, without client data moving between accounts.
A catalog of models
By capability: classify and route, extract, embed, reason, transcribe. Tuned small models underneath.
Isolated by design
A vault per client and an isolate per run. Dedicated inference endpoints when a client needs them.
A run log per client
Every agent action recorded in the client's run log.
Founding-partner label
A published case study and direct engineering support.
Wholesale economics
Per-client licence plus metered inference. You set the retail price.
Thirty days to a live workstream.
Scope
One workstream and the sources it needs.
Connect
Each agent gets scoped, time-bound access.
Run
Agents run. Every run is logged.
Review
Outcomes weekly. The second workstream starts from what the first learned.
What agencies ask before the first call.
What do I resell?
Workflows you build and own, running for each client on that client's own vault: lead generation, follow-up, reporting and the playbooks you already sell as services. Your brand stays on top.
How do the economics work?
A licence per client vault plus metered model usage, at partner rates. You set the price your client pays. We share the partner card on a call.
Who owns the client relationship?
You do. We are partner-led: when you bring a client, we work through you, and the client sees your brand.
What does the first workstream look like?
One client, one workstream, a 30-day trial. We scope it together, connect the sources it needs, run it, and review outcomes before you decide to continue.
Do I need engineers or a platform team?
No. Provisioning, hosting, scaling and model serving are run for you. Your team designs the workflow and owns the client outcome.
Where does my client's data live?
In that client's own vault, divided into scopes. Each agent reaches only the scope its connection names, and every run is logged.
Can we white-label it completely?
Yes. The product runs under your brand, with the Agent OS underneath.
Does what we learn on one client help the others?
Your workflows and templates improve across your book. A client's data and memory bank stay in that client's vault and are never shared with another client.