Implemented product system / Integrated evidence
VantaBlade DeepScan
A paid, point-in-time identity-intelligence workflow that turns multi-source evidence into structured risk analysis, remediation guidance, persisted reports, and delivery.
System overview
DeepScan connects verified purchase intake, provider orchestration, identity normalization, deterministic scoring and remediation, bounded AI-assisted interpretation, background execution, storage, and customer delivery.
Product problem
Exposure sources differ in schema, identifiers, coverage, and failure modes. A paid workflow must unify those inputs without treating every result as equivalent or allowing a generative model to become the sole authority over risk.
Engineering scope
- Backend-created PayPal orders, verified capture, one-scan entitlements, and expiring intake capabilities
- Email, username, phone, IP, and domain normalization across provider boundaries
- HIBP and DeHashed retrieval with explicit partial and degraded result states
- Deterministic impact, risk, driver, and remediation logic
- AI-assisted interpretation and reporting inside application-controlled boundaries
- Background execution, persisted results, PDF storage, and email delivery
High-level architecture
From product input to durable outcome.
- Backend-created order
- Verified PayPal capture
- Expiring intake token
- Validated one-time intake
- Background execution
- Provider boundaries
- Normalize and deduplicate
- Risk and remediation
- Structured report
- Persistence and delivery
Important system boundaries
- Buyer, scan target, and delivery identity are distinct concepts even when their values overlap.
- Provider responses are evidence mapped to typed findings before scoring or presentation.
- A missing provider result is not silently treated as universal absence.
- DeepScan is a one-time analysis product, not ongoing monitoring.
Capabilities demonstrated
- Heterogeneous provider data fusion across several identifier types
- Explicit successful, partial, degraded, and failed result vocabulary
- Deterministic scoring and remediation with bounded AI narrative support
- Backend-authoritative commerce intake and one-time tokenized post-purchase workflow
- Persisted document assembly, storage references, and delivery workflow
Reliability, authority, and privacy
- Provider isolation allows partial or degraded results instead of false clean states.
- Important risk and remediation outcomes remain deterministic application logic.
- Intake tokens expire and retain one-time consumption state.
- Persistence, rendering, storage, and delivery remain distinct operational boundaries.
Transferable engineering patterns
- Assessment, enrichment, and multi-provider data products
- Deterministic analysis augmented by controlled AI interpretation
- Verified webhook and tokenized paid-intake workflows
- Background document generation and artifact delivery
- Due-diligence, research, compliance, and reporting systems
Related focused public proofs
Inspect selected patterns independently.
These repositories demonstrate related patterns. They do not reproduce the complete product or imply code identity.
Engineering / Next action
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