Neuro-Symbolic AI: The Architecture
Regulators Trust
Not probabilistic. Not a black box. Our hybrid approach combines agentic AI execution with deterministic decision-making, purpose-built for regulated industries.
The Problem with Probabilistic AI
Large language models are powerful, but they're probabilistic. Given the same input twice, they might produce different outputs. They can't explain their reasoning in terms regulators understand.
For claims decisions, this is unacceptable.
Separation of Concerns
Two layers, each optimized for what it does best
Agentic AI Layer
Flexible and adaptive
- Document reading
- Data extraction
- Classification
- Orchestration
Uses machine learning to handle unstructured data, understand context, and orchestrate complex workflows.
Deterministic Logic Engine
Precise and auditable
- Coverage rules
- Policy logic
- Cost calculation
- Decision output
Applies encoded business rules to produce consistent, explainable decisions every time.
Complete Audit Trail
Every field traces to source documents. Every decision traces to policy terms. Full transparency for regulators and auditors.
The Decision Dossier
Every claim decision produces a complete, replayable audit record, your defense in any audit or dispute.
Input Summary
Complete claim data as received: documents, parties, timeline, facts
Policy Match
Specific policy clauses applied, with clause IDs and exact text references
Logic Trace
Step-by-step decision path: conditions checked, rules applied, branches taken
Evidence Links
Every field linked back to source documents with page and location
Confidence Score
Automation certainty level with flagged areas requiring human review
Replay Capability
Re-run with identical inputs, get identical outputs, every time
Unlike black-box AI: Every True Aim decision can be replayed, explained, defended.
The Control Layer
Automation with oversight. Every feature designed to keep humans in control where it matters.
Replay Logs
Re-run any decision with the same inputs and get identical outputs. Every execution is deterministic and reproducible.
Rule Traceability
Every coverage decision is mapped to specific policy clause IDs. See exactly which rules fired and why.
Approval Gates
Configure thresholds for human review escalation. High-value or edge cases automatically route to experts.
Exception Routing
Automatic routing based on claim complexity score. Unusual patterns flagged for manual inspection.
Confidence Scoring
Field-level certainty indicators show where the system is confident and where human review adds value.
Our philosophy: AI should handle the heavy lifting, but humans must always be able to understand, verify, and override. Every control exists because regulated industries demand it.
Not Another Black Box
See how True Aim compares to traditional AI approaches
| Capability | Traditional AI | True Aim |
|---|---|---|
| Decision consistency | Variable | Deterministic |
| Audit trail | Partial | Complete |
| Explainability | "Model said so" | Traceable to clause |
| EU AI Act ready | Unclear | Yes |
Security & Compliance
Enterprise-grade security built for regulated industries
Data Protection
- Swiss-based hosting available
- GDPR-aligned architecture
- Encryption at rest and in transit
Access Control
- Role-based permissions
- SSO integration support
- Full audit logging
Regulatory Alignment
- EU AI Act transparency requirements
- FINMA guidelines for automated decisions
- ISO 27001 roadmap (2026)
Research Partnership
Our technology was developed in collaboration with ZHAW (Zurich University of Applied Sciences). The original developer, Dr. Dandolo Flumini, leads ongoing R&D through an Innosuisse-funded research program.
See the Technology in Action
Book a technical deep-dive to understand how our neuro-symbolic architecture can work for your claims operations.
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