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Real-Time Decision Models

Every signal scored.
Every decision explained.

Propensity, churn, fraud, eligibility, NBA, generative AI and your own models — scored in milliseconds, explainable end to end.

50+
Pre-built models
<10ms
Scoring latency
8
Model families
See it in action Explore the Decide Layer
Decision Engine · 8 Model Families
LIVE
Propensity
Churn
Fraud
Eligibility
NBA
GenAI
Agents
Custom
+ Risk + Embeddings + Rules + Anomaly 50+ pre-built
Model families

Every kind of model your decisions need.

Predictive or generative, classical ML or LLM — Appice scores them all on the same decision, in milliseconds.

Predictive AI
Propensity Churn risk Fraud detection Eligibility Credit scoring Customer lifetime value Anomaly detection Next best action
Generative AI · Rules · BYOM
Content generation Multilingual templates Conversational agents Summarisation Sentiment Business rules engine Decision trees Bring your own model
Model stack

8 model families. 50+ pre-built. Every signal scored.

A real preview of what each model returns — the score, the reason codes, the recommended action.

01 — Propensity Scoring

Likelihood of action, calibrated

Propensity · Pre-approved loan
0.78
HIGH
Salary credit (+0.31)today
App activity (+0.22)7d
FD maturity (+0.15)21d
→ Trigger NBA · personal loan offer

Predicts the probability of a customer taking an action — purchase, conversion, click, response. Calibrated, monitored, retrained on the live feedback loop.

Propensity Calibrated Real-time Drift-monitored
02 — Churn & Retention Risk

Early warning before the cancellation call

Churn risk · 30-day
62%
WATCH
Voice usage-40%
Support tickets+3
App opens-65%
→ Fire retention play · personalised win-back

Survival-based churn models with time-to-event predictions and reason codes. Triggers retention journeys 30–60 days before the customer leaves.

Churn Survival Retention Time-to-event
03 — Fraud & Anomaly Detection

Sub-30ms scoring on every event

Fraud risk · Card swipe
0.92
BLOCK
Geo mismatchMumbai → Lagos
Velocity3 txn / 60s
Device unknownyes
→ Hold transaction · notify cardholder

Transaction fraud, SIM swap, account takeover and behaviour anomaly — ensemble of supervised and unsupervised models, auditable reason codes per decision.

Fraud Anomaly Sub-30ms Ensemble
04 — Credit & Eligibility

Bureau, exposure and KYC in one score

Eligibility · Personal loan
₹3L
APPROVED
Bureau (CIBIL)768
Exposure ceiling
KYC vintage< 12m
→ Pre-approved · surface in-session

Real-time eligibility scoring fuses bureau, exposure, KYC vintage and policy rules. Pre-approved loan offers, limit changes, cross-sell eligibility — fired the instant a signal qualifies.

Credit Bureau pull KYC Exposure
05 — Next Best Action / Offer

Ranks every eligible product, every moment

Next Best Action · Ranked
1FD renewal · bonus 7.5%
0.81
2Personal loan · ₹3L
0.74
3Card upgrade · zero fee
0.62

Multi-objective ranking across every eligible offer for every customer moment — propensity × value × cost × compliance, evaluated under 30 ms.

NBA NBO Multi-objective Ranked
06 — Generative AI

Subject lines, body copy, multilingual

Generated · 3 languages
EN
Anita, your salary lands today. Pre-approved up to ₹3L — activate now.
HI
अनीता, आज आपका वेतन आ रहा है। ₹3 लाख तक प्री-अप्रूव्ड — अभी सक्रिय करें।
AR
أنيتا، راتبك يصل اليوم. معتمد مسبقاً حتى ٣٠٠٠٠٠ — فعّل الآن.

Subject lines, body copy, multilingual templates and personalised content — generated in seconds with tone and regulatory rules applied per locale.

LLM Multilingual Compliant Tone-aware
07 — Conversational Agents

Chat and voice, guardrailed

Conversation · live
When is my EMI due?
Your next EMI of ₹12,500 is due on 18 May. Tap to pay now — saves 0.5% late fee.
✓ Policy check passed · PII masked

Chat and voice agents with policy guardrails — handle customer queries, KYC updates, claim filing, balance lookups, no hallucinations, no PII leakage.

Conversational Voice Guardrailed PII-safe
08 — Custom & BYOM

Any model, any framework, any cloud

$ appice models register
POST /v1/models/your-credit-v2
// runtime: Snowflake · Vertex · Bedrock · REST
✓ deployed · scoring at 8ms

Bring your own models from Snowflake, Vertex AI, AWS Bedrock, Azure OpenAI or any REST endpoint — deploy alongside Appice's library, same scoring pipeline, same audit trail.

BYOM Snowflake Vertex Bedrock REST
Model principles

Explainable. Real time. Compliance-first.

Every model running in Appice is built for regulated environments — auditable, governed, scored inside your perimeter.

01

Explainable by default

Every score ships with reason codes, feature attributions and confidence. Regulators see the “why”, not just the number.

02

Real-time inference

Scoring latency under 10 ms end-to-end. No nightly batch, no queue. Models fire on the signal, not the schedule.

03

Compliance-first by design

RBI, SAMA, MAS, GDPR and DPDP guardrails enforced before the model fires — consent, residency, audit trail per decision.

04

BYOM ready

Bring your models from Snowflake, Vertex, Bedrock, OpenAI or any REST endpoint — deploy beside Appice’s 50+ pre-built models, same pipeline, same audit.

Model onboarding

From first decision to live model in days.

Pre-built models hit production fast. Custom and BYOM follow the same pipeline.

01

Week 1 — Pick decisions

Identify the decisions to model: pre-approved loans, churn flags, NBA, fraud. Choose pre-built families.

02

Weeks 2–3 — Connect & calibrate

Pre-built models tune on your historical data. BYOM models register via REST. Reason codes emit from day one.

03

Weeks 4–6 — Live, audited

Every score in production, every reason code logged. Drift monitoring and retraining schedules live.

In production

Live at IDBI Bank India — 50+ models, every signal scored.

Propensity, churn, fraud, eligibility, NBA and generative AI — running inside the bank’s perimeter, every score audited with reason codes. Same models live at Tier-1 lenders across the GCC and South-East Asia.

Model tooling

Works with your ML stack — bring your own.

Appice ships with 50+ pre-built models and integrates with the providers your data-science team already uses.

Cloud ML platforms

Google Vertex AI AWS Bedrock Azure OpenAI SageMaker

LLM providers

OpenAI Anthropic Google Gemini Mistral Llama (self-host)

Data & warehouse

Snowflake BigQuery Databricks Redshift

OSS frameworks

TensorFlow PyTorch scikit-learn XGBoost

Vector & embeddings

Pinecone Weaviate pgvector

Rules & orchestration

Allyvate AI Rules engine REST / BYOM
FAQ

Model questions.

Can we bring our own models?

Yes. Register any REST endpoint, Snowflake-native model, Vertex / Bedrock deployment or local container. Appice scores it on the same pipeline as the built-in models, with the same reason-code logging.

How do you handle model drift and retraining?

Every pre-built model has built-in drift monitoring on prediction distribution, input drift and outcome calibration. Retraining schedules are configurable; outcomes from Act and Learn feed back into the loop automatically.

Are decisions explainable for regulators?

Yes — every decision ships with reason codes, top features and confidence. RBI fair-practice, GDPR right-to-explanation and DPDP requirements are first-class. Audit trail per decision is exportable.

Where do the LLMs run? Does customer data leave the perimeter?

Your choice. Use Azure OpenAI / Bedrock inside your VPC, self-host Llama or Mistral on-premise, or call third-party LLMs with PII masking enforced before egress. On-prem deployments keep all data inside your data centre.

See your decisions modelled in 30 minutes.

Bring a decision. We’ll show you the model, the reason codes, the explainability and the integration path — on your data, your perimeter, your regulators.

Book a Technical Demo