Overview
Vidai is described as a self-hosted AI gateway and control plane. It is intended to govern enterprise AI traffic from one boundary, with every AI call, cost, and policy seen and enforced in one place across teams, models, and providers. The site positions it as a control room for AI requests, costs, and compliance on the user's own infrastructure.
The product sits between applications and AI providers. It sees, controls, and records every request, and the site states that everything between apps and providers stays inside the network boundary. It supports any model and framework with one-line integration, and switching providers is described as a configuration change rather than a long procurement cycle.
Vidai is built for high-stakes AI in regulated, latency-critical, and sovereign settings. The site lists a 25 MB engine, 21,803 RPS verified peak on a single node, 1.95ms median latency under load, and 0 data sent outside the network. It also presents use cases for controlling AI spend, proving AI compliance, running AI safely at scale, and running latency-critical AI.
Pricing
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Use Cases
- Finance and CFO teams use Vidai to control AI spend by seeing what every team, project, and product spends before invoices arrive.
- Compliance and risk teams use Vidai to prove AI compliance with a record of the percentage of AI traffic that was actually protected.
- Platform and engineering teams use Vidai to run AI safely at scale with one system in front of every AI provider on their own infrastructure.
- Teams with latency-critical AI use Vidai to run AI when a millisecond is money.
- Teams use Vidai to avoid model lock-in by switching providers as a configuration change.
- Teams use Vidai to keep AI traffic inside their network boundary.
Features
AI assistant
Natural language interface
Workflow automation
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