TECHNICAL RESOURCES

Developer documentation, architecture specs, and FAQs.

Explore the engineering foundations of PalmPass: integration guides, cryptographic schemas, architectural blueprints, and answers to common technical questions.

DOCUMENTATION & BLUEPRINTS

Engineering Architecture Specifications

ARCHITECTURE6 min read

PalmPass Identity Layer Specification

An in-depth review of the layered architecture connecting optical capture devices, vector processing, and third-party enterprise software.

ArchitectureSystem Design
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DEVELOPERS8 min read

REST Authentication API v1 Reference

Complete technical reference for session creation, device token issuance, vector payload formats, and webhook delivery semantics.

APIRESTWebhooks
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SECURITY10 min read

Biometric Protection & Cryptographic Irreversibility

Technical analysis of one-way vector embedding generation, AES-256-GCM template encryption, and ephemeral token lifecycle.

SecurityCryptographyPrivacy
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INTEGRATION5 min read

University SIS & Attendance Integration Blueprint

Standard operating procedures for interfacing PalmPass turnstiles and lecture hall scanners with Banner, Canvas, and custom student databases.

EducationLMSERP
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FREQUENTLY ASKED QUESTIONS

Common questions regarding PalmPass infrastructure.

Clear answers on integration, biometric security, and deployment models.

What is PalmPass and how does it work with our existing software?

PalmPass is an identity and authentication infrastructure layer. It operates between the physical person presenting their palm and your organization's existing software (such as an ERP, LMS, Active Directory, or POS). PalmPass captures the palm biometric signal, verifies liveness, matches it against an encrypted template store, and returns a verified identity token to your software. Your software then executes the authorized action (e.g. logging attendance, unlocking a door, or applying a loyalty discount).

Does PalmPass replace our existing database, HRMS, or student management system?

No. PalmPass is explicitly designed to integrate with the systems you already use. It does not store financial records, grades, employee payroll, or student academic histories. It solely provides the high-assurance identity verification signal to your existing software.

How is biometric privacy protected?

PalmPass enforces privacy by design. Raw photographs of palms are processed in ephemeral memory and permanently discarded immediately after mathematical vectorization. Biometric representations are stored as one-way cryptographic embeddings that cannot be reverse-engineered into palm images.

What hardware is required to run PalmPass?

Our current software prototype operates using standard high-resolution camera sensors on mobile devices for testing. For production deployments, we are engineering dedicated optical capture modules with controlled multi-spectral lighting and fixed geometric constraints to deliver sub-100ms verification consistency.

Can PalmPass be deployed on-premises or in an air-gapped network?

Yes. PalmPass is architected to support both managed cloud deployments and air-gapped on-premises deployments for sensitive institutional, defense, and healthcare environments.

What is the status of PalmPass's third-party certification?

PalmPass has completed internal software validation (~2,000 scans across 10 participants with zero observed false acceptances on our prototype dataset). Formal third-party laboratory certifications (including ISO/IEC 30107 Presentation Attack Detection and SOC 2 audits) are scheduled as part of Stage 03 of our public development roadmap.

DEVELOPMENT LOG

Engineering & Validation Milestones

August 2026

Completed Internal Validation Milestone (~2,000 Prototype Scans)

Conducted extensive multi-angle and multi-lighting test cycles on our core vectorization and liveness pipeline, achieving zero observed false acceptances across the test cohort.

July 2026

Two-Device Demonstrator Architecture Finalized

Successfully implemented client-server protocol separating edge optical scanning from centralized vector verification.

June 2026

Multi-Region Palm Segmentation Algorithms Initialized

Developed proprietary landmark detection segmenting three independent hand zones for composite signal extraction.

Have technical questions about your infrastructure?

Connect with our engineering team or explore an early access pilot evaluation for your organization.