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At Mynd, I worked on building and scaling a property management platform focused on rental operations and investor services. I developed backend services using Python and Java to support leasing workflows, payments processing, owner reporting, and tenant management. On the frontend, I built responsive user interfaces using React, enabling property owners and residents to manage accounts, view financial data, and interact with the platform seamlessly.
The network for creativity
Join 1.25M professional creatives like you
Connect with clients, get discovered, and run your business 100% commission-free
Creatives on Contra have earned over $150M and we are just getting started
Related posts
I designed and built this real-time orbital situational awareness dashboard for Kessler Watch.
Communicating the density of low Earth orbit debris without sacrificing browser performance required bridging scientific telemetry with optimized WebGL rendering. Simulating over 500 cataloged satellites, spent booster stages, and fragmentation clouds around an interactive globe with dynamic close-approach warnings, scrubbable timeline controls, and altitude distribution graphs turned raw tracking metrics into an urgent, tactile space-surveillance experience.😊
I built The Quiet Chair, a booking experience for a fictional single-chair hair studio in Baner, Pune, run by a solo stylist named Mira.
Mira’s problem is simple: every booking message interrupts an appointment. Checking availability, confirming times, and handling changes take attention away from the customer in her chair.
The app lets customers choose a service, see available times, and receive an immediate booking confirmation. Availability accounts for opening hours, lunch breaks, existing appointments, and cleanup time. Customers can request a quiet appointment and use a secure link to reschedule or cancel, with online changes closing four hours before their appointment.
Mira has a protected owner workspace to view her daily agenda, check customer preferences, manage appointments, and block personal time.
I built it to turn “Can I book with you?” into “You’re booked” without needing a reply from the owner—and to make later changes just as straightforward. The result is fewer messages, fewer manual calendar checks, and more time for Mira to focus on her clients. @Lovable
Agent Evaluation Dashboard — Full-Stack LLM Observability Tool
Teams running AI agents in production need visibility into how those agents actually perform not just whether they respond, but how accurate, fast, and cost-efficient they are. I built a full-stack observability dashboard to solve exactly that: a single place to track accuracy, latency, API cost, and schema compliance across multiple LLM models and agent types.
What I built
A responsive Next.js (App Router) frontend styled with Tailwind CSS — deep purple sidebar, live accuracy/latency charts (Recharts), filterable eval-run tables, and per-model performance comparisons
A Python FastAPI backend serving the dashboard's data layer, with token-based authentication protecting every route
Full session handling: login, protected pages, automatic redirect for unauthenticated users
A fully responsive layout collapsible drawer sidebar on mobile, reflowing grid on tablet/desktop
