SiriusOne:

Comprehensive UX Audit and Optimization for Intelligent Trip Tracking Platform

Improving onboarding trust, reducing trip classification friction, and accelerating report generation through structured UX transformation.

Client & Project Overview

A mobility technology company developing an intelligent trip-tracking platform approached SiriusOne to improve the user experience of its mileage classification application.

The product already had strong technical capabilities for automatic trip capture. However, early product analytics and user feedback revealed critical friction points during onboarding, trip classification, and report generation.

Users struggled to understand system status, required excessive manual effort to classify trips, and often lost time preparing reports.

The objective of the engagement was to transform research insights into a structured UX improvement roadmap that would increase user confidence, accelerate daily workflows, and improve overall platform adoption.

Key goals included:

  • increasing trust during first-time setup
  • reducing friction in trip classification
  • improving reporting reliability
  • preventing common user errors
  • aligning the product with modern UX standards seen in competing platforms

Business Problem

Low Trust During Initial Setup — Users were unsure whether tracking was functioning correctly. Permission requests appeared technical and legalistic, without explaining why the data was required. This uncertainty slowed onboarding and reduced early engagement.

Trip Management Was Not the Primary Interface — The home screen focused primarily on calendar navigation. However, users typically wanted to see their most recent trips immediately and take quick actions. This caused friction when trying to classify trips efficiently.

Limited Visibility Into Progress — Users could not easily see daily mileage totals, estimated reimbursements, classification progress, or report readiness. Without visible feedback, the product's value remained hidden until the reporting stage.

Risk of User Errors — Duplicate trips occasionally appeared during imports. Account deletion lacked safeguards. Primary actions were not always visually prioritised. These issues reduced user confidence in the platform.

Reporting Workflow Friction — Preparing reports required too many manual steps. Users expected faster export flows, expense capture, flexible reporting formats, and better tracking visibility.

Tech Stack

Evaluation Framework: Nielsen's 10 Usability Heuristics

Research Methods: Heuristic Evaluation · Competitor Analysis · Benchmark Analysis

Deliverables: UX Audit Report · Improvement Roadmap · Benchmarking Matrix · Competitive Analysis

Target Platform: Mobile application (iOS · Android)

#UXAudit

#ProductDesign

#MobilityTech

#UXResearch

Comprehensive UX Audit and Optimization for Intelligent Trip Tracking Platform Case Image

Project Timeline

blick 1

The audit delivered a structured set of outputs, not only an improvement roadmap. Key deliverables included:

  • Overview of the project, core problems, and recommendations
  • Structural UX architecture and content review
  • Detailed list of usability issues with remediation recommendations and expected impact on key metrics
  • Priority map separating quick wins from strategic long-term improvements
  • Consolidated synthesis of research and competitive benchmarking
  • Heuristic evaluation scorecard based on Nielsen's 10 principles
  • Benchmarking matrix
  • Competitor analysis presentation

The improvement roadmap was structured into three development horizons:

Duration

12+ weeks

Effort

3-phase roadmap

Phase 1 — Immediate Improvements

0–6 weeks

Simplified permission explanations, onboarding progress indicators, chronological trip timeline, swipe-based classification, inline editing, multi-select with undo, post-trip value summaries

Phase 2 — Structural UX Improvements

6–12 weeks

Redesigned navigation structure, centralised system status visibility, reporting preview dashboards, duplicate detection, account deletion safeguards, automated classification rules

Phase 3 — Advanced Product Capabilities

12+ weeks

Expense tracking hub, receipt capture with OCR, fuel and maintenance tracking, Bluetooth trigger-based tracking, scheduled reporting, advanced classification rules

Team involved

Lead UX Designer team member 1

Lead UX Designer

Product Strategy Consultant team member 1

Product Strategy Consultant

Mobile UX Specialist team member 1

Mobile UX Specialist

Data Analytics Specialist team member 1

Data Analytics Specialist

Solution Overview

Trust From the First Interaction

The audit revealed that permission screens were a primary drop-off point during onboarding. Users encountered technical, legalistic language without context for why location data was needed. The recommended solution redesigned permission requests to clearly explain the purpose and benefit of each data type. A live system status widget was introduced to provide continuous feedback on tracking health, GPS or Bluetooth status, and synchronization state.

Trips as the Central Product Object

Heuristic evaluation identified that the calendar-first home screen created cognitive friction. The audit recommended redesigning the interface around a rich chronological trip timeline. Each trip card displays route map, start time, distance, classification status, vehicle and purpose, and synchronization state — enabling fast classification decisions without multi-screen navigation.

Visible Progress and Value

Benchmarking against competing platforms revealed that leading products surface key metrics directly on the home screen. The solution surfaces daily and monthly summaries, estimated reimbursements, classification progress, and report readiness directly on the home screen.

Error Prevention and Recovery

The audit identified duplicate trip imports and unprotected account deletion as significant trust risks. Recommended solutions include automated duplicate detection, re-authentication requirements before critical actions, a recovery window after deletion, and visual prioritization of primary actions throughout the interface.

Results

Activation

Faster onboarding and shorter time to first valid trip classification.

Engagement

Reduced time required to classify trips and lower backlog of unclassified trips.

Reporting Efficiency

Higher share of reports generated successfully on the first attempt.

Trust and Reliability

Lower duplicate trip creation rate and fewer support requests related to tracking status.

blick 2

Similar

implemented cases:

AI-Powered Customer Support Automation

SiriusOne designed and deployed a multi-channel AI agent system combining voice AI, text automation, and a real-time agent copilot — reducing average handling time by 52%, increasing first-contact resolution to 89%, and enabling the existing team to process 3.4x more interactions per agent per day.
Tech Stack: Cloud: AWS, AI/ML: GPT-4o · RAG · Voice AI · intent classification, Voice: Twilio · WebRTC, Backend: Python · FastAPI · PostgreSQL · Redis, Security: PII masking · RBAC · audit logging
Read more about case

Enterprise Azure Data Warehouse Modernization

SiriusOne modernized a fragmented reporting infrastructure for an international healthcare organization, replacing manual 800-CSV pipelines with an automated, scalable Azure-based Data Warehouse.
Tech Stack: Cloud: Azure, Ingestion: Azure Data Factory, Storage: ADLS, Database: Azure SQL / Synapse Serverless, Security: Azure Key Vault, Analytics: Power BI, Governance: GDPR-aligned framework
Read more about case

AI-Powered Credit Risk Analytics & Vintage Analysis Platform with Chatbot Interface

SiriusOne delivered an enterprise-grade AI platform that transforms how financial institutions analyze credit risk, monitor portfolio quality, and evaluate customer segments through automated vintage analytics and a natural-language chatbot interface.
Tech Stack: AI: GPT-based assistant, Predictive segmentation, NLP pipelines. Data: Daily ETL, Vintage Engine, Antifraud graph. Frontend: Web dashboard, Custom filtering. Infra: AWS, API Gateway.
Read more about case

AI-Powered Credit Risk Analytics Platform

SiriusOne delivered an AI-powered credit risk analytics platform combining vintage analysis, portfolio segmentation and a chatbot interface that allows stakeholders to explore risk indicators using natural language.
Tech Stack: Cloud: AWS, Data Processing: SQL-based analytics pipelines, Analytics: Vintage analysis engine, AI Layer: Natural language query processing, Visualization: Interactive dashboards, Integrations: Core banking data sources
Read more about case

Comprehensive UX Audit and Optimization for Intelligent Trip Tracking Platform

SiriusOne conducted a comprehensive UX audit for a mobility technology company — identifying critical friction points across onboarding, trip classification, and reporting, and delivering a prioritised improvement roadmap across three development horizons.
Tech Stack: Methodology: Heuristic Evaluation · Competitor Analysis · Benchmark Analysis, Deliverables: UX Audit Report · Improvement Roadmap · Benchmarking Matrix
Read more about case

AI-Powered Loan Application Automation

SiriusOne developed an AI system that automated loan application processing using document analysis and decision models. The solution significantly reduced manual review time and improved processing accuracy — enabling the client to handle higher application volumes without scaling headcount.
Tech Stack: AWS, OpenSearch, OpenAI, LLM, RAG, Python
Read more about case
AI-Powered Loan Application Automation - Mobile View

AI Bot for Customer Support in Retail

SiriusOne developed an AI-driven customer support bot for a retailer in Western Europe. The solution streamlined business processes, integrated with the call center, and enhanced customer satisfaction.
Tech Stack: AWS, Anthropic, Python, RAG, Agents, WhatsApp API Integration, Zendesk
Read more about case
AI Bot for Customer Support in Retail - Mobile View

AI-Powered OCR Automation for Financial Document Processing

SiriusOne developed an AI-driven OCR solution for a financial services firm to automate key data extraction from structured and unstructured PDFs, significantly improving accuracy, processing efficiency, and compliance in financial decision-making.
Tech Stack: Azure Form Recognizer, Custom AI Models
Read more about case
AI-Powered OCR Automation for Financial Document Processing - Mobile View

AI-Powered Image Redaction for Privacy Protection in Aerial Imagery

SiriusOne developed an AI-driven image redaction system to remove sensitive data from aerial images while preserving quality. The model accurately detects and masks private areas like people and vehicles ensuring compliance with strict data protection regulations.
Tech Stack: Python, TensorFlow, OpenCV, YOLO
Read more about case
AI-Powered Image Redaction for Privacy Protection in Aerial Imagery - Mobile View

AI Bot for a Governmental Organization

SiriusOne developed an AI solution to enhance search and user experience for a MENA governmental knowledge base, improving accessibility, streamlining interactions, and ensuring data security.
Tech Stack: AWS, Anthropic, Python, RAG, Agents, WhatsApp API Integration, Zendesk
Read more about case
AI Bot for a Governmental Organization - Mobile View

AI Bot for HR & Recruitment Departments

SiriusOne developed an AI-driven solution to enhance recruitment and HR processes for a leading Saudi corporation, streamlining talent acquisition and improving candidate experience.
Tech Stack: Python, RAG, Gemini, Google VertexAI, GCP, SAP SuccessFactors
Read more about case
AI Bot for HR & Recruitment Departments - Mobile View

Machine Learning Model for Optimal and Cost-Effective Predictions

SiriusOne developed a cost-efficient ML model to deliver precise, real-world predictions tailored to client requirements. The solution optimized data processing, resource utilization, and accuracy, enabling better decision-making while reducing operational costs.
Tech Stack: AWS SageMaker, Glue, API Gateway, S3, Lambda, CloudWatch
Read more about case
Machine Learning Model for Optimal and Cost-Effective Predictions - Mobile View

Machine Learning-Enhanced Travel Booking Platform

SiriusOne built an AI-powered travel booking platform that analyzes user behavior and delivers personalized recommendations. The solution enhanced user engagement, increased conversion rates, and streamlined the booking experience with intelligent automation.
Tech Stack: Python, TensorFlow, Keras, AWS (SageMaker, Lambda, S3), React Native, MySQL
Read more about case
Machine Learning-Enhanced Travel Booking Platform - Mobile View

AI-Powered Real Estate Valuation Platform

SiriusOne developed an AI-driven property valuation system that provides real-time price estimations based on historical data, property attributes, and market trends. The solution improved valuation accuracy, enhanced user trust, and adapted to dynamic market fluctuations.
Tech Stack: Python, TensorFlow, Scikit-Learn, AWS (SageMaker, Lambda, S3), PostgreSQL
Read more about case
AI-Powered Real Estate Valuation Platform - Mobile View

AI-Driven Anti-Money Laundering (AML) System

SiriusOne implemented an AI-powered AML detection system that enhances fraud detection by analyzing transaction patterns, risk factors, and anomalies. The solution significantly reduced false positives, improved regulatory compliance, and increased operational efficiency.
Tech Stack: Python, TensorFlow, Scikit-Learn, Apache Spark, AWS (S3, Lambda, SageMaker), PostgreSQL
Read more about case
AI-Driven Anti-Money Laundering (AML) System - Mobile View
View all cases
Get a personal assessment of your taskFill out a simple form and we will contact you within 1 business day