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Sentinel SYX
Sentinel SYX · Veterans services
Business outcome
Personalized claims guidance in minutes, around the clock
Veterans now receive personalized guidance in minutes instead of waiting months for answers. Claims support is available around the clock.
The problem
Veterans faced long waits for disability-claim guidance. The claims process is complex, and applicants often did not know which evidence they needed or what their eligibility was.
What Centcept built
Centcept built an AI-powered platform for Sentinel SYX that automates claims assistance, eligibility guidance, and case tracking. The AI walks applicants through their situation and points them to the right evidence and next steps.
Implementation
Discovery → design → build → deploy (phased)
Architecture
A React front end backed by Node.js services, with an LLM-powered guidance layer over a structured claims domain model. Eligibility logic is rules-based and auditable; the AI layer handles natural-language intake and next-step recommendations.
AI / Automation
The AI layer automates eligibility guidance and claim-status assistance, with human escalation for edge cases. Conversation transcripts and decisions are logged for audit.
Context
Customer context
Veterans applying for disability-claim guidance faced long waits, and the claims process is complex. Applicants often did not know which evidence they needed or what their eligibility was.
Existing process
Guidance was delivered manually over the phone and in person during office hours, with no self-service path for applicants to check eligibility or track a claim.
Constraints
The claims domain is rules-heavy and sensitive: eligibility logic must be auditable, and applicant conversations and decisions need to be logged.
Why previous approaches failed
Static information pages could not adapt to each applicant's situation, and a fully manual process could not scale to round-the-clock demand.
How we built it
Data / model approach
A structured claims domain model keeps eligibility rules deterministic and auditable, while the LLM layer handles natural-language intake and next-step recommendations over that model.
Evaluation methodology
— to be verified —
Deployment
— to be verified —
Security
Conversation transcripts and decisions are logged for audit; eligibility decisions stay on rules-based logic rather than model output alone.
Team
Centcept delivery team (strategy, design, engineering, deployment)
Before / After
Guidance delivery
Before
Months of waiting
After
Minutes
Availability
Before
Office hours only
After
24/7
Lessons learned
— to be verified —
Technology
ReactNode.jsLLM integrationClaims domain model
"Centcept turned our vision for an AI-powered veterans platform into a reality. The claims automation they architected is exactly what we imagined."
— Sentinel SYX
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