Platform
Anima
The AI inference orchestration and runtime layer of the Agentycs platform.
Anima makes AI inference controllable, predictable, and deployable in real-world environments.
It controls how models are selected, where inference runs, and how workloads are scheduled, while enforcing cost, latency, resilience, and data locality policy across customer-assigned infrastructure.
Why Anima is needed
Inference is where AI systems become difficult to operate in reality: costs are unpredictable, execution is opaque, data control weakens, and deployment is often constrained by shared-service assumptions. Anima solves this by treating inference as infrastructure.
How Anima works
Receive an application request
Inference begins with a task request from an application or workflow.
Select the right model
Route tasks to models based on task type, policy, sensitivity, and performance requirements.
Schedule across compute
Balance workloads across available heterogeneous compute for cost, latency, and throughput.
Enforce locality and governance
Keep data inside approved environments and apply governance controls at runtime.
Resilience and fallback
Maintain reliability with monitoring, failover, and controlled degradation where needed.
Anima benefits
Predictable inference cost
Plan and budget for inference with controlled routing and scheduling.
Controlled latency and performance
Stabilise response times under real demand and constrained environments.
Sovereign deployment support
Run inference where you need it without uncontrolled data egress.
Abstract model complexity
Expose a stable interface while Anima handles model selection and orchestration.
Operate under constraint
Maintain capability across edge, on-prem, or disconnected environments.