PD Face Recognition
Next-generation biometric identity verification solutions designed to prevent impersonation in digital transactions. High-speed, AI-driven liveness detection that ensures the person on the other side is real and authorized.
THE PROBLEM
Where Identity Checks Get Fooled
Photo & Screen Spoofing
Printed photos, replayed videos, and digital screens can fool identity checks that don't test for liveness.
Duplicate & Synthetic Identities
Without large-scale matching, the same person — or a fabricated identity — can open multiple accounts undetected.
Slow, Friction-Heavy Verification
Manual or overly complex verification steps drive users to abandon onboarding before they finish.
OBJECTIVE & FEATURES
Core Verification Features
The objective: a multi-layered verification barrier that combines passive and active analysis to make spoofing impractical.
Passive Liveness
AI depth and texture analysis to distinguish real human skin from paper or digital screens without user movement.
Active Liveness
Challenge-response instructions requiring users to blink, nod, or move their mouth to verify real-time interaction.
1:1 Matching
Seamless comparison between live facial data and government-issued National ID or Dip Chip verification photos.
1:N Matching
Large-scale database identification to detect duplicate identities or cross-reference against global blacklists.
HOW WE BUILT IT
Technical Approach
Passive + Active Liveness Stack
Combines depth/texture analysis with challenge-response prompts so spoofing is caught without adding user friction.
1:1 and 1:N Matching Pipeline
Runs both document-to-face comparison and large-scale database search within the same verification flow.
Optimized Neural Inference
Matching models tuned for sub-200ms response times, keeping verification fast enough not to lose users mid-flow.
OUR PROCESS
Development Methodology
The same disciplined delivery process behind every Pandasoft product and service, from first requirement to ongoing support.
Discovery & Requirements
Understand business goals, users, and constraints before a single line of code is written.
UX & System Design
Wireframes, architecture, and API contracts are locked down before development starts.
Agile Development Sprints
Iterative 1–2 week sprints with continuous client visibility into progress.
QA & Testing
Manual and automated testing across functional, security, and performance dimensions.
Deployment & Launch
A staged rollout with monitoring in place from day one, minimizing launch-day risk.
Support & Iteration
Ongoing maintenance, monitoring, and feature iteration after launch.
WHERE THIS FITS
Deployed in Production Identity Checks
PD Face Recognition is already running inside live banking and energy-sector platforms — see the Partnerships section on the homepage for the full client list.
TMBThanachart Bank (TTB)
Onboarding Individual & Juristic + e-KYC Integrated Suite
Powers the Onboarding Individual and Juristic flow and e-KYC Integrated Suite for retail account opening.
Bangkok Bank (BBL)
PD Liveness
Backs the PD Liveness check, adding a spoofing-resistant layer to core account verification.
PTG Energy
PTG Liveness and Face Recognition
Runs the Liveness and Face Recognition solution across PTG's loyalty and identity platform.
Contact
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