Real-Time Decisioning Platform
Behavior sees the click. We see the customer. Appice ingests every signal — behavioural, transactional, operational — resolves them to the person, and decides the right action in under 200 milliseconds. The Action Layer for humans and agents.
Why real-time, why now
Every enterprise use case that used to run on the "next-day batch" now needs to run in the same session. Three shifts made that true simultaneously in 2026.
Once the fraudulent transaction is settled, it's a chargeback, an investigation, a regulatory notice. Sub-100ms decisioning is the difference between prevention and post-mortem. Batch fraud scoring runs at the wrong speed to matter.
The best cross-sell offer for a customer who just paid off their loan is not the same as the offer for the same customer tomorrow morning. If you deliver the right offer 12 hours late, you've delivered the wrong offer.
When an AI agent asks "what should I do for this customer right now", the answer needs to arrive inside the same conversation turn — not in the next batch cycle. Agents don't wait, and neither should the decisioning layer serving them.
The architectural shift
Marketing automation platforms and lifecycle engagement tools were built around a fundamentally different loop: segments overnight, campaigns tomorrow. Real-time decisioning inverts every part of that loop.
Batch loop
Real-time loop
The Appice architecture
Four capabilities. One real-time loop. This is how Appice turns customer signals into compliant actions in under 200 milliseconds.
01
Ingest signals from every source — behavioural, transactional, operational — and resolve them to the person.
02
Apply rules and ML models to choose the next best action for this customer at this moment.
03
Execute the action across every channel — push, SMS, email, WhatsApp, in-app, web, agent.
04
Capture outcomes, feed them to the model, close the loop. Every decision makes the next one better.
Real-time examples
Real-time decisioning isn't a marketing gimmick. These are three concrete use cases where a decision one hour late is a decision that doesn't matter.
A customer completes a large transaction. Appice checks the fraud signal AND generates a best-next-product recommendation in the same 200ms decision. If the transaction is clean, cross-sell fires. If not, no offer, and the risk team is notified. One decision, one round trip.
Customer's data allowance drops below 20%. Appice sees the signal, checks the customer's usage pattern, and fires a personalised recharge offer while the customer is still using the app. Conversion rate on in-session offers vs next-day batch: 6 to 8x.
Auto-debit failure detected. Appice fires the intervention (WhatsApp message with one-tap payment link) inside 30 seconds of the failure — not in the overnight lapse-report batch tomorrow morning. Recovery rates on same-day intervention are dramatically higher.
The competitive reality
Braze, MoEngage, CleverTap, and every lifecycle-engagement platform in the category will tell you they support real-time. What they mean is: a webhook can trigger a campaign in near-real-time. That's not the same thing as decisioning. True real-time decisioning requires three things they don't natively deliver:
Signal in → model inference → rules evaluation → action fired. Not just "webhook received in real-time" — the full decision cycle, including any ML inference, inside 200 milliseconds.
Real decisioning needs transactional data (transactions, payments, claims, orders) at the same latency as behavioural data. Most competitors were built for behavioural-only ingestion and struggle with transactional throughput.
Not as a downstream filter after the decision fires. Regulated decisioning requires compliance rules that run inside the decision step itself, with the same latency budget.
See how Appice compares on real-time decisioning specifically: All alternatives, vs Braze, vs MoEngage, vs CleverTap, vs Adobe.
A real-time decisioning platform ingests customer signals as they happen, decides the next appropriate action using rules and AI models, and executes that action within milliseconds. Unlike marketing automation (which schedules campaigns) or customer data platforms (which store profiles), a decisioning platform is the layer that turns customer signals into action, in the moment the signal arrives.
Marketing automation orchestrates campaigns on a schedule — segment overnight, send tomorrow morning. Real-time decisioning listens to signals continuously and decides in the moment. When a customer opens the app, drops out of a form, misses a payment, or hits a fraud flag, decisioning fires a response inside 200ms. Marketing automation fires a response in the next scheduled batch.
Journey orchestration executes a pre-designed flow (welcome, day 3, day 7, day 14). Decisioning decides at each moment what the right next action is, given everything known about that customer right now. A journey is a script. A decision is a judgment. Real decisioning systems can adapt in real-time; journey tools require you to design every branch upfront.
They offer trigger-based campaign firing, which is often labelled real-time. True real-time decisioning requires three things they don't natively deliver: sub-200ms latency including model inference, transactional data ingestion at scale (not just behavioural signals), and compliance rules that run inside the decision step rather than as downstream filters. Appice is built around these three requirements.
For fraud, real-time means under 100ms of the signal. For next-best-action in a digital session, sub-200ms so it feels part of the experience. For churn or lapse prevention, seconds may be acceptable. Appice defaults to sub-200ms end-to-end (signal in, decision out, action fired) across all use cases — set once by architecture, not tuned per use case.
Yes. Appice exposes its decisioning capability via MCP (Model Context Protocol), so AI agents can request decisions the same way a channel would. This lets agents ask "what should I do for customer X right now" and get an answer inside the same compliance and latency envelope as human-triggered decisions. See Appice for AI Agents.
A 30-minute call with an engineer. We walk through one of your real use cases and show how Appice would decide it in under 200 milliseconds — end to end.
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