Apache Kafka and Apache Iceberg: Every state change an event, every decision context-aware, every audit trail immutable.
Orchestration Layer
The event-native substrate: every change a governed event.
Stream
Every state change becomes an event the moment it occurs.
Govern
Audit trails are replays of the log, not assembled reports.
Query
Reconstruct any moment. Live and historical on one substrate.
The Orchestration Layer is the AFI Platform's event-native substrate: every action, every state change, every decision becomes an immutable, governed event the moment it occurs. Apache Kafka streams those events across the bank's systems; Apache Iceberg makes them queryable, so people and AI agents reason on one live context.
Experience above, Runtime beneath. The Orchestration Layer sits between.
The bank's human-facing surfaces: customer journeys under the bank's brand, operator work on the XYB Console.
The event-native substrate: every state change a governed, replayable event.
Container-first, the base the platform is built on: scales with demand, deploys where regulations or strategy require.
Apache Kafka streams those events across the bank's systems; Apache Iceberg makes them queryable: warehouse-grade ACID and time-travel on the data lake.
What the bank gains
No batch reconciliation lag. No cross-system drift.
Every stakeholder sees the same evidence, in real time.
Agents reason against the live event stream, not yesterday's batch.
New Solutions inherit the substrate as-is.
The Orchestration Layer is where banking orchestration becomes real:one event-native substrate, one live context, every system reasoning on current state.
What it delivers.
Across every platform service. Every action published to the log the moment it occurs.
State changes reach every orchestrated system in under a second. No reconciliation window.
Append-only by construction. Nothing is edited or deleted; the history is the log.
What it delivers.
Live streams and deep history analyzed on one substrate. No second warehouse to reconcile.
An open table format brings transactional guarantees to the data lake. No proprietary format, no lock-in.
Query the exact state of any entity at any point in time. For audit, recovery, or dispute.
Middleware passes messages between systems. Orchestration moves all three together: on the same event stream, under the same governance.
AI agents, legacy cores, payment rails, and ledgers move against one ordered event log.
The humans and agents who run the bank act on the same live context, not siloed copies.
End-to-end workflows execute as events flow. Evidence produced continuously, not after the fact.
Because every agent reasons against the same live event stream — not private, stale copies of the data — they operate in context: consistent state, consistent policy, consistent audit trail across the orchestrated bank. Governance is not bolted onto AI after the fact; it is a property of the substrate the agents run on.
Independent research is converging on the same architecture: an event-native, standardized substrate for AI across the bank.
BCG with OpenAI
How Retail Banks Can Put Agentic AI to Work, 2026
“…a single, standardized control plane for all AI applications across the organization.”
Bain & Company
Why Agentic AI Demands a New Architecture, March 2026
“Supporting multi-turn, adaptive workflows requires capabilities that legacy stacks were never built to provide, including shared context, orchestration, and runtime governance.”
McKinsey
Extracting value from AI in banking: Rewiring the enterprise, December 2024
“…this sublayer is used to store, transform, and access large unstructured data sets, which are critical for training multiagent systems.”
See the event-native substrate in motion: governed, replayable events as the single source of truth across the bank.