GigaSpaces

GigaSpaces provides the Zaphira Agentic Data Platform, a decoupling layer positioned between AI agents and existing Java applications and databases. It addresses the load, privacy, and cost risks that arise when autonomous agents generate continuous, parallel, machine-paced traffic against systems sized for human-paced interaction and scheduled batch jobs. Zaphira absorbs and shapes agentic traffic before it reaches production systems, helping protect them from database bottlenecks, ad hoc aggregation pressure, concurrency limits, sensitive-data exposure, and rising LLM token costs, without requiring rewrites to existing code.

Zaphira works through four phases: Predict, Analyze, Remediate, and Prove. It reconstructs an estate map from distributed traces, metrics, logs, API specifications, source code, and data-source metadata, then projects selected agentic workflow patterns onto that estate to produce an Agentic Workload Prediction. The platform analyzes where predicted demand will collide with current capacity, identifying hotspots, missing interfaces, and unshielded data paths. Remediation uses Agentic Data Units (ADUs), purpose-built data-layer components that provide persistent per-agent state, shared cross-agent context, event-driven reasoning, and elastic concurrency. GigaSpaces also operates in-memory data grid and smart data integration infrastructure. Zaphira is aimed at enterprises running mission-critical Java applications and databases, including banking, insurance, travel, manufacturing, telecom, and public sector organizations.