Contact person: AI Meta-Search Engine MVP

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Location: Patna, India

Budget: Recommended by industry experts

Time to start: As soon as possible

Project description:
"Project: Zarves – AI-Powered Meta Search Hub for Flights, Hotels, Rides, E-commerce & Local Deals
Overview:
Zarves will be an AI-driven meta search hub that aggregates flights, hotels, rides, e-commerce products, and local store deals into a single, intelligent interface. The first milestone is a web-based MVP centred around a conversational AI chatbot, designed to deliver instant, ranked results and personalized recommendations.
Core Focus for this Build:
Entire experience is conversational: users ask questions like “Show me the cheapest flight to Berlin next month” and get aggregated, ranked offers in seconds.
Flights comparison with real-time price alerts, consolidated user reviews, and ratings pulled from partner APIs.
Seamless multi-vertical handling: flight inquiries, hotel suggestions, ride options, e-commerce search, and even post-purchase order tracking, enabling smooth expansion into future verticals.
AI-driven personalization: intent detection, user preference learning, and dynamic ranking to ensure relevant results every time.
Future-ready architecture: scalable for integration with mobile apps, push notifications, and advanced analytics.
What the Finished MVP Should Deliver:
Responsive Front-End: Clean search UI + persistent chat drawer (React, Vue, or similar).
Back-End Aggregation: Integrates at least three live flight APIs, normalizes results, and caches for speed.
Microservices: Monitor fare changes and trigger email/push notifications for price drops.
Review & Ratings Ingestion: Enrich each offer with trusted user feedback.
AI Layer: OpenAI / LangChain / equivalent for dialogue, query understanding, and multi-vertical response handling.
User Management: Basic auth, profiles, and alert subscriptions.
Documentation: Clear README and architecture doc so investors or future developers can run or extend the demo into a mobile app.
Analytics Dashboard (Added for Vision): Track user searches, top deals, click-throughs, and engagement metrics to improve AI recommendations over time.
Acceptance Criteria:
Typical flight query returns ranked offers from multiple providers in <3 seconds.
Price alerts trigger automatically when tracked routes drop below thresholds.
Sample conversations run smoothly without fallback to manual flows.
AI learns user preferences over time, offering more relevant recommendations in repeat queries. (Added for vision)
System should be scalable to add future verticals (rides, retail, local services) without major refactoring. (Added for vision)
Next Steps / Deliverables:
Concise blueprint with API endpoints, data contracts, and UI wireframes ready for sharing once the approach is agreed.
Demo-ready MVP showcasing web conversational interface for investors and stakeholders.
Scalable architecture blueprint for mobile app expansion and future funding rounds. (Added for vision)
Notes on Additions for Vision Alignment:
Added AI-driven personalization & learning → makes MVP future-proof and attractive for investors.
Added Analytics Dashboard → shows user engagement and future AI improvement possibilities.
Highlighted multi-vertical scalability → clarifies roadmap beyond flights/hotels.
Highlighted funding/demo potential → signals professional planning to investors." (client-provided description)