Use cases · solution patterns

The model proposes. It never decides.

Four patterns we design and deploy — each one separates what an AI suggests from what a deterministic, auditable system allows to happen.

FinTech / Payments

Real-Time Fraud & AML Detection

A three-tier decision system: deterministic guardrails, a real-time model that scores every transaction in milliseconds, and generative AI that explains a decision only after it has been made.

85–90%Fraud detection rate at fixed false-positive rate (target, from ~62%)

Read the pattern →

Digital Lending / NBFC

Agentic Underwriting & Document Processing

A five-stage document-to-decision pipeline: ingest and classify every document, extract fields with confidence scores and citations, verify with specialist agents, decide with a deterministic policy engine, and route to a human based on confidence.

HoursTurnaround, application → decision (target, from 3–5 days; fast-track: minutes)

Read the pattern →

Healthcare / Life Sciences

Clinical & Regulatory Evidence Copilot

A five-layer, grounded generation architecture for regulatory documents: every fact carries provenance, every number comes from a deterministic calculation, and a qualified human signs off on every draft.

8–15 minPatient narrative authoring time, review + edit (target, from 45–90 min)

Read the pattern →

Retail / D2C / Ecommerce

Conversational Commerce & Personalization

Three capabilities behind one assistant: semantic and multimodal discovery, a grounded conversational assistant, and real-time personalization. Prices, stock, and offers are never generated.

<8%Zero-result search rate (target, from ~34%)

Read the pattern →

Figures are illustrative engineering targets for each solution pattern, not guaranteed results for a specific deployment.