An intelligence layer
with a developer surface.
Not a chat box on a vector store — a service your whole stack can call. Doyna runs where your data lives and exposes company-wide intelligence through one API.
One API for company-wide intelligence
Your CRM, ERP, support desk or internal app queries the same resolved corpus through a single endpoint — and gets back not just documents, but completed work.
Your data and logic stay local
Your corpus, all three indexes and the agent logic run inside your perimeter — on-prem or in your own private cloud. Your data never leaves your walls.
It reasons over relationships — then acts.
Four layers turn a pile of documents into intelligence that does the work.
Full-corpus RAG
Reads everything, every day — automatically. Email, SAP, contracts, SharePoint, Drive, meetings.
Three indexes
A vector index for meaning, a Neo4j graph + entity resolution linking contract → vendor → project → thread → person, and PostgreSQL for exact values.
Agentic file-ops
An agent that executes: builds decks, runs risk radars, performs document operations.
Always-on monitors
Background watchers fire on project stall and emerging risk — the company never misses what matters.
The moat is the graph: the longer it runs, the richer the corpus — and the harder we are to replace.
The window for private enterprise AI is open right now.
Four forces just converged — and every one points to on-prem, correctness-first AI.
Sovereignty is law
Since 2 August 2026 the EU AI Act’s transparency and AI-literacy duties apply; the high-risk regime moved to 2 December 2027 under the Digital Omnibus. Deadlines shift — the exposure of holding your corpus in a US cloud does not.
Infra left the cloud
56% of enterprises now run or plan to run production AI inference on private cloud, while public cloud fell from 56% to 41% in a year. Source: Broadcom Private Cloud Outlook 2026, 1,800 IT decision-makers.
Pilots keep failing
95% of enterprise GenAI pilots show no P&L impact. Buyers are done paying for demos that fail on their own data. Source: MIT NANDA, The GenAI Divide, 2025.
Models are commoditized
Inference at GPT-3.5 quality fell from $20.00 to $0.07 per million tokens between Nov 2022 and Oct 2024 — a 280× drop. Raw intelligence is table stakes; privacy, the graph and correctness are the moat. Source: Stanford HAI AI Index 2025.
Intelligence got cheap. Trust got scarce. Doyna is built for the world that creates.
- The same offer as everywhere else on the site: a technical conversation, not a sales call.
Private AI, your way. On hardware you own.
It goes up inside your network in a day, on hardware that stays yours. The same AI everyone else rents, built for the budget you actually have.
Live in production · On your own hardware · Single-tenant always