Integration · Operations and Data

Make Agentforce aware of events the moment they happen

Apache Kafka is the event backbone: producers publish what just happened — an order shipped, a payment failed, a threshold tripped — onto topics, and consumers react in their own time. Nothing else in most stacks knows the present tense this well. Emerge Digital connects that stream to Salesforce Agentforce so events reach the agent layer: a conversation can reflect something that happened moments ago, and specific events can put an agent to work instead of waiting for someone to notice.

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What this unlocks

Business events flowing through your topics — shipments, payments, status changes — become context an agent can reflect in conversation, close to the moment they were published.
Events can initiate agent work: a delivery exception or a failed renewal charge arriving on a topic can start an agent preparing the follow-up, with a person approving anything customer-facing.
Consumer groups and topic ACLs bound what the agent layer subscribes to, so exposure to the stream is a deliberate, governed choice made topic by topic.
Where a schema registry defines your event shapes, the integration consumes them as contracts, so the agent-side view of an event stays consistent as producers evolve.

In the customer journey

The conversation knows the shipment went out

A customer asks about a delivery minutes after the carrier-scan event hit the topic — and the agent's answer includes it, because the state it reads was updated from the stream rather than an overnight batch.

An exception event starts the outreach

A payment-failure event lands; an agent drafts the retry-and-notify sequence for that customer and queues it for human approval, so the response begins when the event does, not when a report gets read the next morning.

Incident-aware answers

When a service-disruption event is published for a region, customer-facing agents acknowledge it in their replies instead of contradicting what customers are experiencing.

Kafka's contribution is temporal rather than stage-bound: at Engage and Convert it closes the gap between something happening and the conversation reflecting it, and at Optimize the retained event log is an honest record of what actually occurred, in order. Wherever an agent's usefulness depends on now rather than yesterday, the stream is what supplies it.

How Emerge integrates Apache Kafka

Emerge Digital treats Kafka integration as an architecture engagement, because agents do not sit on a topic the way a stream processor does. We select the topics that carry decision-relevant events, build the consuming services that turn those events into state and triggers Agentforce can use, and configure ACLs so the agent layer touches only the streams it was granted. Event-driven agent actions get a human checkpoint wherever the action reaches a customer or moves anything of value — the stream supplies awareness; people keep the judgement calls.

How we structure an engagement

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FAQ

Does the Agentforce agent subscribe to Kafka topics directly?

Effectively no — and it should not. Emerge builds consuming services between the stream and the agent layer: they read the granted topics, maintain a current-state view or fire a trigger, and give agents something queryable. That indirection is where governance and reliability live.

Is this something we can switch on from a marketplace listing?

No. Which events matter, how they map to customers, and what an agent should do about them are design decisions specific to your topics — so Emerge delivers this as a services engagement, not an installable product.

Can any event make an agent act without review?

Only where you decide the stakes allow it. Emerge designs each event-to-action path explicitly, and anything customer-facing or financially meaningful carries a human approval step by default.

Ground your agents in Apache Kafka.

Tell us what your agents need to read and write in Apache Kafka, and we'll design the integration and the governance around it.

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