So we built our own.
Hundreds of active labour cases per lawyer. Deadlines spread across five different court portals. Client updates managed in spreadsheets. AI tools that either didn't speak Portuguese, didn't understand CLT, or hallucinated case outcomes with total confidence.
The problem wasn't effort — the professionals were exceptional. The problem was the absence of a tool built specifically for this work, in this legal system, in this language.
Hundreds of pages of HLD and LLD documents sat in SharePoint, unread after approval. Test cases were written manually, weeks after the architecture had already changed. No one knew what was covered, what wasn't, or whether the team was ready for SIT.
This happened in Telecom. In Banking. In IPTV. In every domain where specification documents existed but no intelligence connected them to delivery.
Djanai was formed by a team that had spent years inside these problems — inside law firms, inside telecom operators, inside banking projects and IPTV rollouts. We understood the workflows, the edge cases, the things that break in production that no generic AI tool had ever seen.
We built two platforms. Not one — because the problems, while rooted in the same failure (disconnected knowledge, generic AI, manual processes), demanded fundamentally different solutions. Prisma Iuris is built for the rhythm of Brazilian labour law: CLT, TST, Datajud, the PJe portal, the language, the deadlines. Aurora is built for the rhythm of engineering delivery: specifications, objectives, coverage, execution, learning.
Both share the same conviction: AI that can't show its work is AI you can't trust. Every answer cites its source. Every insight is traceable to a document in your corpus. And because your data is sensitive — whether it's case files or architecture specifications — both platforms run entirely on your own infrastructure.
A model that knows everything about everything knows nothing about your domain. The best AI tools are the ones that understand your specific workflows, your specific language, your specific data — and are honest about what they don't know.
Case documents, architectural specifications, client information, business logic — none of it should travel to a third-party cloud to be processed. Both platforms run on your own GPU infrastructure, with local LLM inference. Privacy is not a feature. It's the architecture.
Aurora's knowledge distillation engine learns from every project cycle. The more you use it, the more it understands your domain, your terminology, your patterns. It doesn't just answer questions — it adapts to the way your team works.
We will never try to build a tool for everything. Prisma Iuris is for Brazilian labour law. Aurora is for engineering project intelligence. We go deep on specific problems, not wide on general ones. That's the only way to build something genuinely useful.
Djanai is a young, independent software company. We don't have a large team, a big marketing budget, or a decade of institutional history. What we have is two production-ready platforms, real deployments, and a clear conviction about where AI in professional services is going.
We believe the next wave of AI adoption won't come from companies that bolt AI onto existing generic products. It will come from those who understand specific domains deeply enough to build AI that genuinely earns the user's trust — because it's accurate, because it cites its sources, and because it gets better over time.
That's what we're building. If you're working on a problem that sounds like ours — reach out. We'd rather talk to someone in the middle of the problem than someone who's moved on from it.
Whether you're evaluating Prisma Iuris, Aurora, or just want to understand what we're building — we're easy to reach.