Contact person: Taxi booking app with Customer, Driver , and admin - AI Based

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Location: Ahmedabad, India

Budget: Recommended by industry experts

Time to start: As soon as possible

Project description:
"1. Introduction
APP is envisioned as a next-generation ride-hailing platform comparable to Uber and Bolt but
differentiated by its proprietary AI assistant, Chika. The goal is not only to provide standard ride-
hailing services but to redefine the rider, driver, and operator experience through AI-driven interactions,intelligent job allocation, and continuous learning systems.
This proposal outlines:
- How Chika (AI assistant) will operate.
- Detailed AI workflows for Riders, Drivers, and Admins.
- Platform architecture and roadmap.
- Key competitive advantages for GIRO.


2. Core AI Component: Chika
Chika will serve as the AI brain of the ecosystem. Its roles:
Conversational AI → Riders & drivers can ask natural questions.
Intelligent Job Allocation → Optimizing assignment, reassignments, enroute matching, and back-to-back jobs.
Predictive Analytics → For admins to monitor demand, peak times, and fleet optimization.
Voice Interface → Hands-free communication for drivers.
Continuous Learning → Improving accuracy and recommendations over time.

3. Detailed AI Workflows
3.1 Rider AI Workflow
Example Query: 'Chika, what time shall we get to my destination?'
Step Process:
Input Recognition – Voice or text captured.
NLP Layer – Detects intent: ETA query.
Data Integration – Retrieves GPS, navigation API, and traffic.
AI Computation – Refines ETA using driver profile, road closures, and past data.
Response Generation – Conversational output.
Output Delivery – Voice + text displayed.

Other Scenarios: Fare estimation, driver location, return trip booking.
Onboarding & Profile
Signup/Login (Phone, Email, Google, Apple, Facebook, OTP, etc.)
KYC/ID verification (if required by regulation)
Manage profile (photo, name, contact info)
Emergency contact setup
Booking System
Instant booking (pickup & drop-off selection)
Ride scheduling (book for future date/time)
Multi-stop booking
Ride type selection (e.g., Economy, XL, Premium, Bike, Auto, etc.)
Fare estimator (real-time fare calculation)
Ride Experience
Live driver tracking (ETA, route progress)
Driver details (name, rating, vehicle info)
Safety features (share ride, SOS alert, emergency button)
In-app calling/masking numbers
In-app chat (text/voice via Chika AI assistant)
Payments & Wallet
Multiple payment modes: card, wallet, UPI, PayPal, cash
Split fare with co-riders
Wallet top-up & auto-recharge
Ride receipts & invoice download
AI Assistant (Chika)
Voice/NLP queries: “Chika, when will I reach?” / “What’s my fare?”
Smart routing suggestions
Trip status & delay explanations
Contextual help (FAQs, app support)
History & Feedback
Ride history & receipts
Rating system (driver & rider both ways)
Feedback & issue reporting

3.2 Driver AI Workflow
Example Query: 'Chika, do I have another job nearby?'
Step Process:
1. Voice Input – Driver speaks hands-free.
2. NLP Layer – Detects intent: Job availability.
3. Assignment Engine – Searches auto, enroute, back-to-back jobs.
4. Optimization Model – Prioritizes shortest pickup, fare, rider wait.
5. Response – Conversational result.
6. Driver Acceptance – Via voice command.
Other Scenarios: Earnings summary, safer route suggestion, voice messaging.
Other Features:
Onboarding & Profile
Signup/Login
Driver KYC (license, vehicle RC, insurance, etc.)
Bank account details for payouts
Driver verification workflow (manual/AI-powered) Job Assignment
Auto Assigner – automatic job allocation
Auto Reassign – rejected/unaccepted trips get reallocated
Enroute Assign – jobs matching driver’s preferred route
Back-to-Back Jobs – immediate next job at destination
Manual accept/reject option
Navigation & Trips
Integrated navigation (Google Maps/OpenStreetMap)
Chika voice updates: “Traffic ahead, rerouting suggested”
Ride status updates: Accept → Arrived → Ride Started → Completed
Earnings & Performance
Daily/weekly/monthly earnings breakdown
Incentives & bonuses
Trip history & receipts
Performance metrics (acceptance rate, cancellation rate, ratings)
Messaging & Communication
Pre-set quick replies
Voice-to-text replies (for hands-free use)
In-app chat with rider
Safety & Support
Panic button (alerts admin/support)
AI-powered unsafe route alerts
Rider behavior alerts (fraud detection, safety warnings)
AI Assistant (Chika)
“Chika, how much have I earned today?”
“Any jobs near my route?”
Voice navigation & contextual alerts
3.3 Admin AI Workflow
Example Query: 'Chika, where is demand highest right now?'
Step Process:
1. Input Recognition – Text/voice query from admin dashboard.
2. NLP Layer – Detects intent: Demand forecasting.
3. Data Sources – Live ride requests, historical ride patterns, events.
4. AI Model – Forecasts demand using time-series.
5. Output – Peak demand prediction + driver recommendations.
6. Optional Automation – Sends driver notifications.
Other Scenarios: Cancelled rides analytics, assignment optimization, automated reports.


User Management
Manage riders (profiles, documents, reports, suspensions)
Manage drivers (onboarding, verification, suspension, incentives)
Fleet owners (if multi-vehicle operators exist)
Job Management
Live trip monitoring
Job reassign (manual override)
Enroute/Back-to-Back job settings
Ride history & dispute resolution
AI & Chika Insights
AI-generated recommendations (e.g., “Increase driver availability in Zone A at 6PM”)
NLP query logs & improvements
Route optimization reports
Financials
Fare configuration (per km, surge, waiting charges, etc.)
Commission setup (per ride/percentage)
Driver payouts management
Refund & adjustment handling
Analytics & Reports
Trip analytics (rides/day, earnings, cancellations)
Driver performance analytics
Heatmaps (hotspot areas, demand vs. supply)
Customer engagement insights
Messaging & Notifications
Push notifications (global, segmented)
SMS/email campaigns
AI-driven personalized offers
Safety & Compliance
SOS alerts monitoring
Fraud detection alerts
Regulatory compliance (driver KYC, trip logs, invoices, tax reports)

===============================
Super Admin / Master Control
Access hierarchy: Super Admin, City Admin, Fleet Manager, Support Staff
Audit logs & role-based permissions
System configuration (API keys, payment gateway, AI model tuning)
4. Special AI Features in Detail
1. Auto Assigner (AI) – Balances driver proximity, traffic, rider wait.
2. Auto Reassign – Instant job reassignment.
3. Enroute Assign – Predictive matching for driver’s direction.
4. Back-to-Back Assign – Checks return jobs before trip ends.
5. Text-to-Voice Messaging – Safe communication.
6. Safety AI – Detects unusual patterns.
7. Continuous Learning – Models improve over time.
5. AI Technology Stack (Proposed)
- NLP & Conversational AI → Rasa, OpenAI GPT API.
- Routing & ETA Prediction → Google Maps API/Mapbox.
- Voice AI → Whisper + ElevenLabs/Amazon Polly.
- ML Models → Gradient Boosting, LSTM, Reinforcement Learning, Prophet.
- Backend → Node.js/ Laravel
- Database → PostgreSQL + PostGIS./Mysql
- Mobile Apps → Flutter.
- Cloud Infra → AWS/GCP, Kubernetes, Redis.
6. Development
Figma
MVP : Rider & Driver apps, booking, tracking, payments, auto-assign, Chika basics.
AI Expansion: Enroute assign, advanced Chika, safety monitoring.
Scaling: Predictive demand, multilingual Chika, AI insights, continuous learning.

7. Competitive Advantage
- Conversational AI → Smart mobility assistant.
- Intelligent Job Assignment → Lower wait times, higher utilization.
- Safety & Transparency → AI monitoring + rider-driver trust.
- Continuous Evolution → Chika strengthens market advantage." (client-provided description)