Scale what makes
you win.
ARPIA amplifies the advantage already inside your company.
Meet Oria
The super agent that knows how your organization works.
It reads the systems you already run through a governed reflection of them, and every account arrives with Cerebro, the institutional memory your people already wrote down. Your team asks, analyses, builds and acts from the first session, with budgets and an audit trail.
Oria is the way in. This is what it opens.
The platform
Your systems connected, your ontology governed, any model, and every decision reconstructable. Eight surfaces, one governed layer, and Oria runs on all of it.
See the platform →Sovereignty
When the data is not allowed to leave the building, ARPIA Edge runs the execution inside it, on your keys and your own GPUs, while the part that builds stays with us.
See ARPIA Edge →Forward deployed
An engineer works inside your operation for a fixed number of weeks and comes back with what to build, what it costs and in which order. Then builds it with your people.
See the plans →Scale what makes
you win.
Companies that lead don't run the standard. ARPIA turns your DNA into sovereign, governed superintelligence: your ontology, your rules, your strategic advantage. Replace your stack or amplify what you run today.
Superintelligence (SI), the way ARPIA builds it: everything your organization knows, decides and runs, working with every AI model you choose, under your governance.
Not five tools. One infrastructure. First use case in 30 to 90 days.
of AI-breach victims had no AI access controls
extra breach cost when shadow AI is involved
of agentic AI projects abandoned by 2027
Sources: IBM Cost of a Data Breach Report 2025 · Gartner, June 2025
ARPIA holds SOC 2 Type II and ISO 42001, the international management standard written for AI systems, both audited by A-LIGN. The reports are available on request.
We didn't hire ARPIA to build a tool. We're building our intelligence layer. The first use case, our collections pipeline, went from days of analyst work to 13 minutes in production. But what convinced us this was the right platform was how fast the second and third use cases came together. The data layer and ontology were already there. We're now building our fourth pipeline on the same infrastructure. Every one has been faster and cheaper than the last.
VP of Enterprise AI Finance & Retail Multinational Group