$3M Fundraised - AI Travel Agent

$3M Fundraised - AI Travel Agent$3M Fundraised - AI Travel Agent

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Julia Kononchuk

• Feb 1

$3M Fundraised - AI Travel Agent

Flutter Development AI Development Web Development Flutter Node.js React

Abdelhafidh Bouzgart

• Jul 14

SpaceGate: SaaS Platform for Centralized Coworking Space Booking

Project Overview & Market Positioning SpaceGate is a SaaS platform built to solve a key fragmentation problem in the coworking industry. Rather than users searching across dozens of individual coworking sites, SpaceGate acts as a centralized marketplace, onboarding coworking space providers onto a single subscription-based platform where users can discover, compare in real time, and book the space that fits their needs in just a few clicks.

Development Approach & Architecture To support a scalable, multi-tenant SaaS model, I designed a mobile-first architecture paired with a high-performance backend. Flutter powers a fluid, native mobile experience across iOS and Android, giving both space providers and end users a consistent interface. The backend runs on FastAPI, selected for its speed and its ability to handle real-time availability data across multiple coworking partners simultaneously — a core requirement for a multi-vendor SaaS product.

The platform's key differentiator is its built-in AI layer via MCP (Model Context Protocol): an agent that understands user requirements, intelligently compares listed spaces across the marketplace, recommends the best-fit options, and generates a direct link to confirm the booking — reducing friction between discovery and conversion.

Technical Stack

Mobile Application: Flutter (cross-platform iOS/Android UI)

Backend Infrastructure: FastAPI (high-performance Python API, multi-tenant ready)

Artificial Intelligence: MCP integration (AI agent for comparison and recommendation)

Business Model: SaaS marketplace connecting coworking providers with end users

Key Platform Highlights

Marketplace Centralization: Aggregates multiple coworking providers into one SaaS platform, replacing scattered, single-provider booking flows.

Real-Time Comparison: Live availability and pricing across all listed spaces.

AI-Powered Agent (MCP): Understands client needs, compares options across providers, and delivers a direct booking link.

Scalable Multi-Vendor Architecture: Built to onboard new coworking partners and scale across cities/regions without re-engineering the core system.

Frictionless Booking Flow: From search to comparison to confirmation, minimal steps for the end user.

View the Project Status: Currently in development (not yet published on app stores).

Flutter Development Flutterflow Development Full Stack Development FastAPI Flutter Python

Christine Straub

• Jul 14

Check it out

Next.js Node.js Vercel

Bakar Qureshi

• Jul 14

I built an AI system that detects solar panel faults from a single image — and deployed it with a live demo. Here's what it does: 𝟲 𝗳𝗮𝘂𝗹𝘁 𝗰𝗹𝗮𝘀𝘀𝗲𝘀: Bird-drop, Dusty, Snow-Covered, Electrical Damage, Physical Damage, Clean • ResNet101 fine-tuned on solar panel imagery • 96.3% training accuracy with strong per-class F1 • REST API deployed on Hugging Face Spaces (Docker + Flask) • React frontend with real-time confidence scores 𝗪𝗵𝘆 𝘁𝗵𝗶𝘀 𝗺𝗮𝘁𝘁𝗲𝗿𝘀: According to Raptor Maps' 2025 Global Solar Report, equipment-driven underperformance has increased 214% since 2019 — resulting in $10 billion in lost energy value in 2024 alone. The average solar site loses 5.77% of its power output annually, costing ~$5,720 per MWdc. The use cases that excite me most: • Drone inspection over utility-scale farms • Ground robotics for close-up panel analysis • Direct integration into SCADA systems via REST API 𝗕𝘂𝗶𝗹𝘁 𝘄𝗶𝘁𝗵: PyTorch · ResNet101 · Flask · Docker · HuggingFace Spaces · React + Vite