Sentiment analysis and behavioral biometric analysis, configured to the specific risk or experience problem each industry actually has. Two products. One engine. No analysis run where it isn't relevant to the use case.
Live Signal Feed
CORE ENGINE
Two products. One underlying engine. Pulse and Nudge draw from the same signal-processing core, configured differently for every industry and use case. Sentiment analysis runs everywhere. Behavioral biometric analysis is enabled only for the specific use cases that call for it: fraud prevention in financial services, claims fraud mitigation in insurance, and voice fingerprinting in telecom call centers. The engine does not run biometric analysis by default, and never outside a named, industry-specific use case.
Layer 01
Continuous analysis of sentiment across calls, chat, claims narratives, surveys, and written communications. Language pattern detection tuned to the specific use case, churn risk, adverse event language, claims fraud indicators, morale signals, or real-time CX sentiment.
Layer 02
Enabled only for fraud prevention in financial services, claims fraud mitigation in insurance, and voice fingerprinting in telecom call centers. Analyzes interaction and voice patterns relevant to fraud detection and caller verification. Not enabled for healthcare, HR, or general customer experience use cases.
Layer 03
Real-time routing logic that powers Nudge, directing sentiment and biometric signals to the correct team based on signal type, severity, and configurable business rules. Under 500ms alert latency.
The Data Flywheel
Aggregated, anonymised signal data from every customer deployment feeds back into the core engine — improving baseline accuracy, intervention precision, and behavioral pattern detection. The more we deploy, the wider the moat.
ARCHITECTURE
From raw interaction data to routed alert, three stages, no gaps.
Customer interactions, claims calls, support conversations, and, for specific use cases, biometric data, are ingested from existing systems. REST and WebSocket ingest endpoints for system integration. Under 3ms capture latency.
Sentiment analysis runs on all ingested data. Behavioral biometric analysis runs only where the use case configuration enables it. Real-time classification and pattern detection tuned to the specific industry use case.
Flagged signals are routed to the relevant team through Nudge, by severity, signal type, and business rule. Outcomes are tracked to refine future routing.
Customer interactions, claims calls, support conversations, and, for specific use cases, biometric data, are ingested from existing systems. REST and WebSocket ingest endpoints for system integration. Under 3ms capture latency.
Sentiment analysis runs on all ingested data. Behavioral biometric analysis runs only where the use case configuration enables it. Real-time classification and pattern detection tuned to the specific industry use case.
Flagged signals are routed to the relevant team through Nudge, by severity, signal type, and business rule. Outcomes are tracked to refine future routing.
SIGNAL LAYERS
Signal Taxonomy
| Signal | Category | Used In |
|---|---|---|
| Customer sentiment | Sentiment | Financial Services, Insurance, Telecom |
| Adverse event language patterns | Sentiment | Healthcare and Life Sciences |
| Claims call sentiment and fraud language | Sentiment | Insurance Services |
| Internal communication and survey sentiment | Sentiment | Enterprise HR Tech |
| Behavioral interaction patterns (fraud) | Biometric | Financial Services (fraud prevention only) |
| Behavioral interaction patterns (claims fraud) | Biometric | Insurance Services (claims fraud only) |
| Voice fingerprinting | Biometric | Telecom (call center only) |
Stats
INTEGRATIONS AND API
OntarioAI surfaces sentiment and biometric intelligence inside the tools your teams already use.
We built native integrations with the CRM, claims management, and contact center platforms where this data already lives. The REST API covers everything else, documented, versioned, and maintained to the standard system integrators and delivery partners require.
Key Endpoints
SECURITY AND PRIVACY
Every architectural decision in the OntarioAI platform was made with individual privacy as a hard constraint. Behavioral biometric analysis is enabled only for the three named use cases where it is the right tool for the problem, fraud prevention, claims fraud mitigation, and voice fingerprinting, and is never enabled by default or used for general workforce or customer monitoring.
Certifications
SOC 2 Type II
Annual audit · Current
ISO 27001
Information security management
GDPR Compliant
EU data processing agreements in place
Data Architecture Principles
Signals are aggregated to the cohort or case level wherever individual-level detail is not required for the use case.
Behavioral biometric analysis is enabled only for fraud prevention, claims fraud mitigation, and voice fingerprinting. It is not enabled for healthcare, HR, or general customer experience use cases, structurally, not just by policy.
Customer data stays in the region they choose. EU customer data never leaves EU infrastructure.
All data is encrypted at rest and in transit. Customer-managed encryption keys are available on the Enterprise tier.
Every demo is tailored to your industry and the specific use case relevant to your team. You will see live platform data and speak with a specialist who understands your industry. No slide decks.