Build a predictable AI cost base, keep sensitive workloads on-prem, and govern local and cloud AI from one place. DANI turns existing enterprise hardware into scalable local AI capacity, without new infrastructure or a large specialist team. Built for regulated industries, but designed for any enterprise scaling AI.
Defense · Healthcare · Finance · Government · Energy · Telecommunications
Working with regulated enterprises and institutional partners
Our thesis
Regulated industries feel the AI infrastructure problem first. Banks, hospitals, government agencies, defense organizations and critical infrastructure companies hold valuable data that cannot always be processed through external AI services. But the challenge is becoming much broader. Every large enterprise is being asked to plan future AI spending without knowing how many employees, applications, agents and automated workflows will consume it. At the same time, companies are adopting multiple cloud models, internal tools and local AI environments, often without one place to manage policies, access, cost and execution. The answer is not to choose between local AI and cloud AI. Enterprises need a predictable local capacity layer, cloud flexibility where appropriate, and one governance layer across both.
The answer isn’t another hosted product. It’s infrastructure the customer already owns, running modern AI under their governance, with nothing ever leaving their perimeter.
That’s what Loxia Labs builds.
The enterprise AI problem
This problem is not limited to regulated industries. Every enterprise adopting AI faces the same budgeting challenge: How do you plan next year’s AI spend when you do not yet know how many users, agents, applications and automated workflows will depend on it?
Regulated organizations have an additional constraint: many of their most valuable workloads cannot leave the organization. DANI addresses both problems by creating a predictable local foundation and governing how workloads are distributed across local and cloud AI.
Relevant to every enterprise. Stabilize a known part of the organization’s AI workload and reduce reliance on fully variable consumption-based costs.
Essential for regulated and data-sensitive sectors. Keep sensitive data and protected workloads inside the organization’s existing environment.
Relevant to every enterprise. Apply consistent access, model, provider, data and cost policies across both local and cloud AI.
Who DANI is for
DANI is initially focused on industries where data residency, security and operational control are critical. These organizations feel the need for local AI most urgently.
But two of the problems DANI solves are becoming universal: AI costs are increasingly difficult to predict. Local and cloud AI environments are being adopted without one unified governance layer. Any enterprise operating multiple models, providers, applications or internal AI workflows will eventually need a consistent way to control where AI runs, what data it can access and how much it costs.
What we build
DANI is the infrastructure layer. OnBuzz is the flagship application that demonstrates what secure, on-prem AI unlocks.
Decentralized AI Network Infrastructure
On-premise AI inference across the hardware your enterprise already owns. Zero cloud exposure. Minutes to deploy. Auditable end-to-end.
AI agent teams for real work
OnBuzz helps anyone create teams of AI agents that execute real business tasks, not just answer questions. Use agents for lead generation, enrichment, marketing workflows, Discord management, travel planning, research, support, and daily admin work, all from one flexible workspace.
Who we build for
Classified-adjacent workflows that can’t touch public cloud. Air-gapped operation. Chain-of-custody on every inference.
PHI stays inside the hospital perimeter. HIPAA-aligned audit posture. No BAA gymnastics with external LLM vendors.
Trading data, customer records, and model outputs governed by a single control plane you operate. Regulator-ready trails.
Sovereignty by default. Data residency enforced at the network boundary. Transparent, Western-aligned supply chain.
Apply AI to operational and infrastructure data without moving it outside the organization, while controlling local and cloud usage through one layer.
Process internal and customer data under clear policies while coordinating AI workloads across edge, local infrastructure and cloud services.
Security posture
CISOs don’t need another marketing deck. They need a clean architecture diagram, a crisp data-flow story, and a control plane they can audit. That’s what we build toward.
Read the full security postureNo data ever leaves your perimeter.
Outbound connectivity policy-gated.
Every inference logged and attributable.
Microsoft for Startups, transparent supply chain.
SOC 2 and ISO 27001 in progress.
Whether your main challenge is sensitive data, rising AI consumption or fragmented governance, DANI helps create one controlled foundation across local and cloud AI. We will review your existing infrastructure, expected AI workloads, data requirements, governance policies and what part of your future AI usage could be stabilized locally.
