HireFlow AI

Assignment 3 · Architecture proposal

Attendance at Scale Without Smartphones

A resilient, auditable attendance design for a distributed workforce where personal smartphones cannot be assumed.

Design boundary: this page is an architecture proposal only. It does not introduce attendance APIs, database tables or production workflows into HireFlow.
1

Problem

One thousand employees work across 100 offices with uneven connectivity and no guarantee that every employee owns, carries or can use a smartphone at work. Attendance must remain available during network outages while preventing buddy punching, location spoofing and silent record changes.

The solution therefore needs trusted shared hardware at each office, an offline path, a controlled exception path and one central source of truth for payroll and HR.

1,000

Employees

100

Offices

Offline

Capable

Audited

End to end

2

Proposed architecture

100 locations

RFID kiosk

RFID card plus employee PIN or biometric verification.

Every office

Local edge queue

Encrypted durable queue keeps check-ins available offline.

Source of truth

Central backend

Validates events, applies policy and writes the audit history.

Fallback channel

Registered landline + Hunar

Accepts voice attendance only from a known office number.

Human control

Manager approval

Reviews voice and other exceptional attendance events.

Accountability

Immutable audit trail

Preserves submission, verification, decision and correction history.

3

Normal check-in flow

01

Identify

Tap RFID card at the office kiosk.

02

Verify

Enter a PIN or use the biometric reader.

03

Queue locally

Create a signed, timestamped edge event.

04

Synchronize

Central backend validates and stores the event.

05

Calculate

Rules engine updates the attendance record.

4

Network outage flow

01

Detect outage

Kiosk continues without central connectivity.

02

Persist safely

Encrypted events remain in the local edge queue.

03

Reconnect

Queue resumes with ordered, idempotent delivery.

04

Reconcile

Backend deduplicates and records original event time.

The kiosk displays a local receipt immediately. Original device timestamps and monotonic sequence numbers are retained; reconnecting never changes when the employee checked in.

5

Voice fallback flow

01

Call office line

Employee uses the registered location landline.

02

Hunar verifies

Voice agent collects identity, PIN and attendance intent.

03

Route exception

Manager reviews the exceptional attendance request.

04

Record decision

Approval or rejection enters the immutable audit trail.

Caller ID from the registered office landline is a location signal, not sufficient proof by itself. The voice request remains exceptional until manager approval.

6

Fraud prevention

  • Bind every RFID card to one active employee and require a second factor.
  • Use liveness-capable biometric readers where policy and consent allow.
  • Sign kiosk events with device credentials and rotate keys centrally.
  • Allow voice fallback only from registered office landlines.
  • Flag duplicate, impossible or unusual check-in patterns for review.
  • Require manager approval for exceptions; never overwrite the original event.
7

LLM versus deterministic-code responsibilities

LLM assists
  • Natural-language daily summaries
  • Anomaly explanations for reviewers
  • HR questions over authorized data
  • Readable management reports
Code decides
  • Final present, late or absent status
  • Shift, grace-period and overtime rules
  • Deduplication and event ordering
  • Payroll-ready attendance totals

The LLM may explain a result, but deterministic, versioned rules always calculate it.

8

Scaling for 1,000 employees across 100 offices

  • Provision one independently identifiable edge device per office, with a spare-device process.
  • Partition inbound events by office and preserve ordering within each device stream.
  • Use idempotency keys so reconnects and retries cannot double-count attendance.
  • Process check-ins asynchronously while keeping central reads strongly consistent.
  • Monitor queue depth, last synchronization, device health and clock drift per location.
  • Keep stateless backend instances horizontally scalable behind a load balancer.
9

Privacy and employee consent

  • Offer PIN as a non-biometric alternative wherever legally or operationally required.
  • Collect explicit, informed consent before biometric enrollment.
  • Store biometric templates—not raw images—and isolate them from attendance records.
  • Limit HR, manager and operator access by role and office scope.
  • Publish retention periods, correction rights and the purpose of every data field.
  • Never use attendance data or LLM outputs for undisclosed employee monitoring.