Where documents are many
The problem is real — no one sifts through thousands of files by hand — and the engine has mass to work with. Without volume, there's no pain that justifies the AI.
Solutions · Use cases
Where Orion solves what the cloud can't.
The same core, applied where it pays off most: sectors that pile up both a lot of documents and a lot of secrecy — and where, by law or by duty, the data cannot leave the organization's network.
In those places, an AI that runs inside the organization's own infrastructure stops being a convenience and becomes the only viable option. Below, three target use cases on a single foundation.
Target use cases · core functional in a test environment (TRL 4)
These are application scenarios the core points toward, described from what it already does — not clients served. What is built and what is the next step are marked at the end of the page.
The criterion
Lots of documents. High secrecy. One engine.
Where secrecy is high
Sending the content to a foreign cloud AI runs into data-protection law and data sovereignty. There, running locally is not a preference: it's the condition for being able to use AI at all.
At the intersection of both
That's where Orion stops being "a better option" and becomes the only viable one. A reusable core serves these verticals on the same foundation — the core-first strategy.
Public sector
Target use case
Intelligence over documents that never leave the agency's network.
The problem
Public agencies pile up cases, opinions, regulations and official letters in a volume no one can sift through by hand; finding the right information takes hours. And the obvious way out — a cloud AI assistant — runs into data-protection law and data sovereignty: sensitive documents cannot travel to third-party servers abroad.
How Orion solves it
The model runs inside the agency's own infrastructure. Orion indexes the internal documents and answers in natural language, citing the source document behind every answer — the officer checks the origin instead of trusting blindly. Nothing travels outside.
Who benefits
Civil servants and managers recover in seconds what used to take hours; the citizen feels it downstream, in faster responses. Compliance and data sovereignty become a consequence of the architecture, not an afterthought.
The climax — where sovereignty becomes an absolute requirement
There's a point in the public sector where "it'd be good not to leak" turns into "it cannot leave the network, under any circumstances": defense and intelligence. That's where intelligence briefings, dossiers and classified reports pile up — enormous document volume at the highest level of secrecy. There, any solution built on a foreign cloud is out of the question: the data cannot, under any circumstances, transit through infrastructure under another country's jurisdiction. Orion's architecture was conceived to operate self-contained: with all components — models, index and reranker — running inside the network, processing happens with no external dependency at use time, able to run in an isolated environment. It's the edge case that reveals why the foundation was built this way: it's not the interface that guarantees secrecy, it's the engineering beneath it.
Legal
Target use case
Search across the archive with a traceable answer and preserved confidentiality.
The problem
Law firms and legal departments hold thousands of contracts, filings, opinions and internal case law. Search is slow — and a generic AI that "invents" precedent is a known, serious risk in legal practice.
How Orion solves it
Meaning-based search with neural re-ranking over the firm's own archive, and an answer that always carries the source of the excerpt. It's anti-hallucination by design: the answer is born anchored in the real document, with its origin in plain sight. Running locally, judicial secrecy and attorney-client privilege are preserved.
Who benefits
Lawyers and in-house legal teams gain speed and stop running the risk of citing something that doesn't exist. The confidential archive never leaves the firm's infrastructure.
Where the fit is sharpest
Attorney-general offices, courts and comptroller bodies concentrated in Brasília are, at once, legal and public sector — the intersection of the country's highest document volume and highest secrecy, in the territory with the greatest density of federal agencies. It's the point where the two verticals meet and the sovereignty argument is strongest.
Healthcare
Target use case
Clinical knowledge and medical records without exposing patient data.
The problem
Clinics pile up medical records, reports, exams and protocols — high volume and of the strictest secrecy, since health data is a special category under data-protection law. Sending it to a cloud AI is legally unfeasible.
How Orion solves it
Each clinic runs its own instance, inside its own infrastructure, over its own document base — answering with the source cited. The medical record never leaves the institution's infrastructure, because the processing happens right there.
Who benefits
Professionals recover clinical information at the right moment, with answers anchored in the real document, not an invention. It's precisely the sector where "runs locally" stops being an advantage and becomes the legal condition for using AI.
One foundation, several verticals. The same engine — local AI, with the source cited — applied where documents are many and secrecy is non-negotiable.
Transparency
What already works and what is the next step.
The use cases above rely only on what the core does today. What doesn't exist yet enters as roadmap — never as a delivered feature.
- Running AI models locally, inside the client's infrastructure.
- Reading and organizing documents, with each excerpt's origin recorded.
- Meaning-based search with neural re-ranking of the most relevant excerpts.
- An answer that returns the source document it was built on.
- Resilient runtime with failure recovery and a runtime audit trail.
- Authentication and access control.
- Effective isolation between clients (multi-tenant).
- An interface for the end user.
- Verticalization — the product layer for each sector.
- Accreditation and certification required by sectors such as defense.