Swarmix

The platform has three parts, all built and running. Studio is a desktop application where an organisation spawns and directly controls specialist AI agents, each with its own identity and permissions. A transformation pipeline sits between the organisation's and the vendor models. It intercepts traffic to Claude, OpenAI and Codex, Google, DeepSeek and Perplexity (and local or air gapped providers), and masks, captures and compresses data on the device before anything leaves it. The Orchestrator coordinates the agents and records the work: structured conversations, proposals and consensus with mandatory reasoning, governance and remit enforcement, a versioned knowledge base with semantic search, plans with approval gates, and several connectors to external applications and services. Governance is enforced in real time, at the moment an agent is spawned, a tool is called, or data is about to leave the device, so it is applied before the fact rather than reported afterwards. The intelligence layer Swarmix captures more than 500 qualitative and quantitative metrics across three layers: user interactions in Studio, security and compliance events, and coordination decisions. Content stays on the device, and only structural metrics aggregate upward under anonymity. This produces intelligence the organisation owns across six areas: cost, adoption, governance scoring, workforce effectiveness, model strategy and predictive analytics. Because every vendor sees only its own slice, this cross-vendor view exists only at the neutral layer where the work is coordinated. Deployment and enterprise fit Swarmix deploys from shared cloud through hybrid managed infrastructure, on-premises, and fully air-gapped for regulated environments. It integrates with enterprise identity and distribution pipelines with attribute base control access and policy as code. Business model Swarmix sells recurring annual enterprise licences, B2B, priced by governance gates rather than seats: moving AI into production, rolling it out across the workforce, bringing regulated data into scope, needing decision records that count as audit evidence, and governing higher-risk AI under regulatory frameworks. Four tiers run from evaluation to a dedicated, air-gapped deployment, with heavy intelligence usage metered and deployment, support and training contracted separately. Market Swarmix sits between two markets projected for 2030: enterprise AI management, about $35B, and enterprise intelligence systems, about $93B, a combined $128B.

Enterprises are adopting AI across many vendors faster than they can govern it. Each vendor shows only its own usage, sensitive data leaves untracked, decisions are delegated to models with no record, and the intelligence about how the company works flows to the vendors instead of staying with the business. As the EU AI Act makes oversight mandatory, this fragmentation becomes a compliance and financial liability.