Arena empowers businesses across industries to make high frequency, critical path decisions fully autonomous.
Similar to a physical robot, Autonomy OS is composed of three components: the Sensor, the Brain, and the Arm. The Sensor measures, the Brain makes decisions, and the Arm takes action. The whole system operates automatically and in real-time.
Autonomy OS ingests and encodes heterogeneous data with different latency profiles – from streaming real-time and structured time series, to unstructured data like images and text – into features that train machine learning models. Autonomy OS also augments data with contextual data from Arena’s Demand Graph – a daily updating index of factors that affect consumer demand and supply – from product prices and availability by location, to demand proxies from social media platforms.
Customer preferences and behaviors change, supply routes are unexpectedly disrupted, and competitors alter strategy. Autonomy OS lets teams build and deploy contextual active learning models that balance exploration with optimization – constantly updating their understanding of a changing world by actively acquiring information.
In complex, multiplayer environments where the sequence of actions matters, Autonomy OS provides high-fidelity simulations of your environment to train deep reinforcement learning AI agents and make better decisions.
Autonomy OS integrates with your existing enterprise systems (or builds new ones) to make end-to-end integration easy. Easy to use, configurable UIs enable users to track business impact at various levels, providing visibility down to each individual autonomous decision and its inputs. The arms are integrated back to the sensors, with a robust coupling that enables continuous online learning and self-improvement.