Multi-agent systems multiply token costs — unless the platform is built against it. orqo was engineered against it from the start.
Here's the uncomfortable math of multi-agent AI: every agent maintains its own context window, and that context grows with every message exchanged between teammates.
Most platformsA team of five agents discussing a problem means the same conversation living — and growing — in five context windows at once. They let that happen, and the bill follows.
orqoEngineered against it from the start.
During the preview you bring your own keys and pay your provider directly. The plan for paid plans makes that a choice, not a chore.
Anyone runs workflows from day one — no provider account to create, no key to paste, no quotas to misunderstand, no procurement detour, and the accountant with the Run button never needs to know what an API key is. That's coming. During the preview, you bring your own keys.
Plug in your own provider keys — encrypted, injected at runtime — and pay your LLM provider directly, at provider prices. Switch per agent, per workflow, per sensitivity level. No lock-in on the token side, ever. And if you run your own models on your own hardware, your heaviest workloads cost you nothing per token. Run it where your data lives
Either way, a run that has started always finishes. Credits are checked when a run begins, never while it is running — so you never lose half-completed work to a balance reaching zero part-way through a job.
Each one attacks token cost at a different point — and they compound across a full staff of agents, every day.
Context compaction — up to 4×. Every agent's working memory is kept lean automatically, so it gets up to 4× the work from the same token budget — measured on long-running research workflows. Multiplied across a full staff of agents, every day, that's not a tweak — it's a budget line. How compaction works
Side conversations. When two agents need a token-heavy exchange — a deep research dive, a long debugging session — they break out into a side conversation the rest of the team never pays for. The team gets the conclusion, not the transcript. How context is allocated
Self-improving workflows. Every run stores its metrics, and orqo analyzes them. The workflows that recur — the ones that actually drive your bill — get more efficient the more you run them. Most platforms' cost grows with usage. orqo's cost per result shrinks.
A memory that answers in three hops. Where keyword search burns 10+ retrieve-and-read cycles, orqo's agents traverse a typed knowledge graph in 2–3 hops — so research that used to cost dozens of LLM calls costs a handful. How the memory works
No trust required: every run's detail view charts each agent's context window over time, token by token.
One line per agent, compactions visible as the line drops. You don't take our word for the economics — you watch the budget hold, run after run.
Fair question — and the answer is the unit we charge for. orqo isn't a token reseller: the paid model meters agentic activity — the work an agent does, priced by the model's tier and deliberately decoupled from the raw provider price. So burning more tokens never pads our revenue the way it pads a reseller's; it only runs up cost. Which is exactly why we engineer it down.
And the saving lands with you, however you pay. Bring your own keys and it's a smaller provider invoice, outright. Pay by subscription* and part of that fee arrives as a monthly credit pool — leaner runs simply make it go further: more work before you top up, because the job took fewer, lighter agentic turns. Either way the bet we're glad to make is the same — that what we cut from your costs comes to cover the orqo subscription itself. And bring-your-own-tokens is always one click away, which keeps the pricing accountable by design.
* Subscriptions and usage credits aren't switched on during the current sneak preview — today everyone brings their own keys and pays the provider directly. This is how paid plans will work once the preview graduates. What the sneak preview is
The preview is open and your keys plug in at runtime. Bring a workflow that's been eating your budget and watch the line drop. Claim your slot