Edge Ingestion
Ingest incoming handwritten claim documents and unstructured PDFs.
Use Case 11 · Banking, Finance & Insurance
Multi-model agentic extraction and validation for complex claims and RFPs.
Customer need & pain point
Step-by-step execution
Ingest incoming handwritten claim documents and unstructured PDFs.
Route document vision parsing to Qwen 2.5/DeepSeek-R1 to extract structured claim fields.
Validate extracted line items against core insurance back-end policy databases using MCP tools.
Issue automated approval for claims below threshold or flag fraud risk scores.
Quantifiable ROI & impact
The “aha” moment
“Claims processing time dropped from 8 days to 4 minutes while saving 50% on underlying compute costs.”
Enterprise data is vast, fragmented, and hidden beneath legacy silos. Traffelo AI harvests that intelligence from the core.
Operating entirely inside your security perimeter, raw streams are scrubbed locally, with zero PII egress — architected against KVKK, GDPR and PDPL.
Tokenised intent payloads are routed dynamically across leading language models — chosen per workload for latency, reasoning depth, and cost.
Turning signals into immediate commercial execution. Traffelo AI. Sovereign intelligence, orchestrated.
Key management, AES-256 encryption at rest, TLS 1.3 in transit, and full tokenization mappings — documented end to end.
All raw PII, transaction details, and user identifiers are scrubbed locally within your security perimeter.
Stripped intent payloads are cryptographically tokenized before execution on remote multi-LLM networks.
Deploy on-premise, in local cloud regions, or fully air-gapped environments. Air-gapped deployments use local models; hybrid ones reach global models with tokenised data.
Encryption at rest AES-256-GCM
Transport TLS 1.3 · mTLS between edge nodes
Tokenisation SHA-256 mapping, key material never leaves the perimeter
Key management Customer-held HSM / KMS, BYOK supported
Egress policy Deny-by-default; anonymised intent payloads only
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