OPAL deploys autonomous AI agents across fraud detection, risk management, compliance, and portfolio operations — integrated into your existing infrastructure in days, not months.
Each OPAL agent is a specialised model trained on financial domain data. They run independently and share a unified event bus for cross-agent coordination.
OPAL's agent pipeline is designed for the latency requirements of live financial markets. Every step is auditable and reversible.
Raw financial events — transactions, market data, regulatory feeds — stream in via WebSocket or REST API with end-to-end encryption.
The OPAL dispatcher classifies each event and routes it to the appropriate agent or agents in parallel with sub-millisecond overhead.
The assigned agent runs inference on the event, cross-references shared memory, and produces a structured decision with a confidence score and audit trail.
Decisions are delivered to your system via webhook or direct DB write. Every action is logged immutably for regulatory reporting and model auditing.
"Most AI platforms are horizontal tools retrofitted for finance. OPAL is built from the ground up for the compliance, latency, and explainability requirements of regulated financial institutions."