AI360

The core hosting engine maximizes GPU efficiency through advanced slicing, parallelism techniques (Tensor, Pipeline), and optimized kernel execution. This ensures low-latency inference and the ability to run multiple large models cost-effectively on shared infrastructure.

This critical layer enforces safety and responsible AI by implementing guardrails, content filters, and toxicity checks on all inputs and outputs. It also ensures data privacy compliance through PII anonymization and secure, audited access to the model.

It acts as a smart, resilient traffic controller that intelligently distributes requests across multiple GenAI providers using load balancing and secure authentication. The gateway guarantees high availability and cost-efficiency with features like rate limiting, circuit breakers, and automatic model fallback to prevent service disruption.

This component provides end-to-end visibility into the entire agentic pipeline, tracking critical metrics like model performance, cost (token usage), and response latency. It enables proactive health checks and root cause analysis by detecting data/model drift and correlating LLM tracing with infrastructure resources in real-time.

The platform enables autonomous, goal-driven execution through the orchestration of sophisticated multi-agent workflows and seamless Agent-to-Agent (A2A) communication. It powers intelligent RAG-based assistants that ground responses in proprietary knowledge and execute complex, multi-step actions.

Integrations provide zero-friction adoption by connecting the entire AI 360 platform—from the Gateway to Agentic Workflows—with existing enterprise ecosystems (CRMs, ERPs, databases, etc.). This ensures that the new AI capabilities are embedded directly into current business processes, transforming traditional operations without requiring a rip-and-replace of legacy systems.