AI Orchestration & Governance Platform
Aiboostr is the enterprise AI governance platform that gives companies full control over how AI agents and models are deployed, accessed, and governed across the organization.
Bring structure and AI governance to enterprise AI
End shadow AI - govern all AI usage from a single control plane
Manage access, cost, and security across every department and use case - with full visibility into which models are deployed, who uses them, and how data flows through the system.
Stay compliant with the EU AI Act regulation
Built-in governed AI system inventory, guardrails, and interaction logging address EU AI Act compliance requirements. Compliance embedded in the platform, not added as an afterthought.
Reduce operational overhead through self-service
A self-service catalog of models and agents lets business units discover, request, and access AI capabilities independently — without manual provisioning by platform teams for every new use case. Governance stays centralized; delivery stays self-service.
Governed AI, three ways to begin
Aiboostr for AI Orchestration
Every model, agent, and prompt under control.
As AI projects multiply across departments, visibility and control erode and shadow AI spreads. Aiboostr provides a unified control plane for all model access, cost governance, and agent governance - across every team and use case.
Aiboostr for Private AI
Private LLMs within your environment.
Routing sensitive data through external AI APIs creates regulatory and security risk. AIBoostr lets you run open-source LLMs directly on your own infrastructure — full AI capability, zero data exposure.
Aiboostr for EU AI Act
EU AI Act compliance built into your AI infrastructure.
The EU AI Act introduces operational obligations for organizations using AI systems. AIBoostr delivers the infrastructure to meet them — AI system inventory, policy enforcement, log retention, and continuous monitoring.
Everything you need to govern AI at enterprise scale
AI gateway and unified access
The AI gateway is a single access point for all models - private and public. Rate limiting, token budgets, per-team policies, and a full audit trail on every call.
Model and agent catalog
All AI models and agents registered in one discovery catalog. Teams find, request access to, and reuse existing capabilities without going through IT each time.
Private model serving
Optimized inference for self-hosted LLMs and predictive models - with autoscaling, model versioning, and staged deployments.
Agent runtime and MCP integration
Stateful execution environment for agentic AI and multi-agent workflows. MCP-based tool integration connects agents to enterprise systems and APIs through a governed interface.
Cost and usage monitoring
Track token consumption, API costs, and usage patterns across teams, projects, and models - with attribution for budget control.
Observability and tracing
Prompt and response level traces. Full execution tracing for agent runs — every LLM call, tool invocation, and inter-agent interaction recorded and queryable.
Guardrails and policy enforcement
Configurable input/output filtering and safety controls applied consistently across all models and access paths - global or scoped per team and use case.
AI inventory and model registry
A complete AI inventory of every model, agent, and application deployed across the organization. With risk classifications, intended use, and access records - foundational for EU AI Act compliance.
Ready to take control of AI in your organization?
Book an Aiboostr demo
FAQ
AI governance questions, answered.
An AI governance platform gives an organization one place to control how every AI model and agent is deployed, accessed, and monitored. It combines an AI inventory, access controls, guardrails, cost tracking, and compliance evidence — so AI scales across teams without losing visibility, security, or regulatory oversight.
Aiboostr builds EU AI Act compliance into your infrastructure. It maintains a governed AI system inventory, enforces policies, retains interaction logs, and monitors AI continuously — producing audit-ready evidence from day one. Compliance is embedded in the platform, not bolted on after deployment.
An AI gateway is a single, governed access point for every AI model — private and public. It enforces access policies, rate limits, and token budgets per team, provides one unified API across providers, and records a full audit trail on every call for cost control and compliance.
Governing agentic AI means controlling not just the model but every action an agent takes. Aiboostr runs agents in a stateful, governed runtime, connects them to enterprise systems through MCP-based tool integration, and traces every LLM call and tool invocation — so autonomous behavior stays visible and enforceable.
Aiboostr deploys on your existing infrastructure — any Kubernetes environment, on-premises, on EU cloud providers, or any major public cloud, with no migration required. Regulated organizations keep AI, data, and governance inside their own perimeter and data-residency boundary.
Shadow AI is any AI model, agent, or tool used inside an organization without approval or oversight. Aiboostr surfaces it by routing all model traffic through a single AI gateway, so every call is logged and unsanctioned usage becomes visible — then brought under one governance policy.
Yes. Aiboostr runs open-source LLMs directly on your own infrastructure, so sensitive data never leaves your environment. You get full AI capability with zero data exposure to external APIs — with private model serving, autoscaling, versioning, and staged deployments included.
An AI inventory is a complete registry of every AI model, agent, and application deployed across an organization, with risk classifications, intended use, and access records. It is foundational for EU AI Act compliance, which requires organizations to document and monitor the AI systems they operate.
Aiboostr provides a self-service catalog where business units discover, request, and access approved AI models and agents on their own — without manual provisioning by platform teams. Governance stays centralized while delivery stays self-service, so teams move fast and IT keeps control of access, cost, and policy.
An AI gateway controls traffic — it routes and enforces policy on every model call. An AI governance platform documents and manages risk across the AI lifecycle: inventory, compliance, and monitoring. Aiboostr combines both, so the gateway's audit trail feeds governance automatically.