Operational AI
Is your enterprise AI running on stale data and incomplete context? Every decision your AI makes depends on data that changes with every transaction. If the infrastructure cannot keep pace, the model operates on a version of reality that no longer exists.
The problem
Models are commoditizing. Compute is scaling. Applications and agents are multiplying. But the operating loop breaks if the operational intelligence layer cannot keep pace. Aerospike serves the current facts decisions depend on, records the outcomes, and feeds them back into the next cycle.
What matters is continuity across stages. If the consequence of the last action has not been recorded before the next decision begins, the system operates on a version of reality that no longer exists. At millions of decisions per second, a break in that continuity compounds.
A payment arrives. Within 200 milliseconds, the fraud model must approve, flag, or decline. PayPal runs three concurrent processes on an entity graph linking customers, devices, IP addresses, merchants, and payment instruments across 400+ million active accounts, 100+ petabytes of risk data, and 8M+ operations per second. Powered by real-time state and context from Aerospike, PayPal has reduced fraud by 98%.
AMD runs 20M+ compute jobs daily across its HPC grid, with 1M+ concurrent at peak. The scheduler must decide in real time which jobs to launch, throttle or reassign based on live CPU and DRAM consumption and user information. Aerospike provides the real-time state and context layer that lets the scheduler do its most important job, scheduling, not querying.
The platform
The real-time state, context, and decisioning platform for operational AI.
Millions of ops/sec at predictable tail latency. Decisions meet their time budgets under production load.
Indexes in memory, data on SSD or persistent memory. In-memory speed at a fraction of all-RAM cost.
Concurrent actors see current state, not stale snapshots. Critical when multiple evaluations for the same entity overlap.
Active-active replication across data centers and regions via XDR. Production resilience without compromise.
Complex structures within records. Daily aggregates stored as lists, enabling single-digit reads for even the most active accounts.
PayPal cut from 1,024 to 120 servers. $9M+ annual savings. 80%+ TCO reduction vs. prior in-memory system.
Start here
Pick one workload where decisions depend on facts that change continuously. Two assessments, two perspectives, one clear picture.