💳 Use Cases

Transaction Intelligence

Sub-50ms semantic intelligence for payments. Parse merchant descriptors, triage disputes, and route mobile banking queries inside the authorization window.

<35ms
End-to-end per transaction
3 models
Parsing, triage, routing
On-device
Mobile routing at 150MB INT4

Three specialist models replace regex-based merchant parsing, manual dispute triage, and cloud-dependent mobile NLU. Each operates within the payment authorization window: parsing cryptic merchant descriptors, converting free-text complaints to structured triage JSON, and routing mobile banking queries on-device with zero network latency.

3 specialist models

How It Works

One specialist model per payment decision,running inside the authorization window

01

Merchant Descriptors Parsed Semantically in the Auth Window

'SQ *JOES CFF SHP NY' is meaningless to regex. Cloud enrichment APIs parse it but add latency that breaks the 50ms authorization window. A specialist LFM parses merchant descriptors semantically in under 35ms, directly in the hot path. No cloud round-trip, no per-call cost. New POS formats adapt via LEAP in minutes.

02

Free-Text Complaints to Structured Triage in 40ms

Dispute complaints are emotional, messy, and full of implicit context. Manual triage creates million-case backlogs. Cloud LLMs could parse them at 800ms+ with PII exposure. A specialist LFM outputs structured triage JSON in under 40ms, on your infrastructure. Deterministic output for auditable decisions. The backlog clears.

03

On-Device Banking Queries at Zero Marginal Cost

Millions of mobile banking queries arrive with typos and abbreviations. Keyword matching fails. Cloud NLU adds latency and per-query costs that compound at scale. A specialist LFM quantized to 150MB deploys on-device: typo-resilient, zero network latency, zero marginal cost. Intent understood, not keywords matched.

Try each model

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Semantic payment intelligence.Sub-50ms. On-prem. On-device.