The graph your
business runs on.
Graph OS keeps a living, versioned graph of your whole business: customers, deals, orders, quotes, and conversations, synced from the tools you already use. Agents work on top of it. Every action starts as a draft, cites the records it touched, and lands in an audit log.
We build yours for a fixed fee. You own it outright.
Your business
is flying blind.
Every company we've walked into has a version of the same story. The CRM is outdated. Quoting is a series of heroics held together by one person who knows where everything is. The answers live in six tools that don't talk to each other. And nobody has the space to fix it, because fixing it isn't in anyone's job description. It IS the job.
One graph underneath everything.
Adapters normalize every source into one entity graph, so nothing downstream depends on your particular stack. The graph keeps full history, what was true and when. Agents run over it in narrow scopes, and every action carries its receipts.
CRM, email, Slack, e-commerce, billing, spreadsheets: adapters turn each source into normalized entities and relationships. Your stack stays where it is, the graph stays in sync.
Customers, deals, orders, quotes, and conversations become entities, relationships, and facts with full history. Query the business as it is today, or as it was the day a decision got made.
Agents work over the graph in narrow scopes. Every action leaves a trace, proposed, approved, executed, citing the records it touched. Everything starts as a draft, and actions graduate only under your approval policy.
Once the graph exists, features stop being projects.
The expensive part of CPQ, forecasting, or ops automation was never the feature. It's assembling the state the feature needs. On Graph OS that state already exists, so the first build pays for the substrate and everything after it is configuration.
Products, pricing, and approval chains live on the graph, so an agent can build, price, and route quotes where your reps already work: in Slack and in your CRM. Pricing is deterministic. The LLM extracts intent and never computes a number. In production today.
Pipeline analytics, forecasting, lead routing, and commission modeling, computed off live graph state instead of a stale CRM export. The same substrate that quotes your deals tells you where the quarter actually stands.
Agents that chase renewals, draft customer replies, reconcile orders, and triage incidents, each with citations, each under your approval policy. Built-to-order shops get the same tooling as SaaS revenue teams.
CPQ, running on the graph.
We build the graph. You run the business.
Every engagement is fixed-fee and fixed-scope, for scaling SaaS revenue teams and for built-to-order hardware shops. Our job is to make ourselves unnecessary. You end with a system your team owns, documentation they can follow, and enough internal context that you never need us again, unless you want to build the next thing.
Why it works.
Graph OS wasn't built for a client as a first attempt. It runs Campus Dyno's own operations, powers a CPQ in production inside a real revenue team, and runs ops for built-to-order manufacturing. You get that iteration history without paying for it.
A typical enterprise CPQ or systems-integration project runs $150k–$300k in vendor fees, plus ongoing licensing, admin overhead, and the consultant you'll need when it breaks. A graph build is fixed-fee, fully documented, and owned outright. No licensing tail, no dependency. The comparison isn't close.
Features share the substrate. Once the graph exists, adding quoting, forecasting, or an ops agent is configuration over state that's already there, not another 6-month integration project. That's the whole point of building the graph first.
You work directly with the person who scopes, builds, and documents the system. No account managers, no handoffs, no telephone game.
If the move looks hard, that's exactly why we're here.
Tell us what you're trying to build, or what's broken and needs fixing. We'll tell you straight whether it's a fit, what it takes, and how long.
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