Dublin Core
Title
Radesso: Connecting Clients and Specialists Platform
Abstract
Radesso is a location-aware job-seeking platform that enables clients to publish on-site or online orders and allows workers to discover, filter, and apply to them with high geographic precision. The platform addresses the persistent struggle of finding a suitable specialist “for any life scenario” within a single environment by combining modern web UX with a rigorously engineered geospatial backend.
The front end is built with React and Leaflet (Leaflet.draw over OpenStreetMap tiles), allowing workers to define one or more work areas by drawing circles, rectangles, and polygons. On the server, a NestJS, TypeORM, PostgreSQL/PostGIS stack normalizes incoming GeoJSON to SRID 4326 (WGS84) and consolidates all shapes into a canonical MultiPolygon with GiST indexing for efficient spatial queries [1].
Security is managed through a production-grade authentication subsystem, including OTP email verification, Google OAuth, and short-lived JWT access tokens (RS256/ES256) carrying a kid header mapped to a database Keystore and Signing Key tables. Refresh tokens are device-scoped, hashed, and rotated on use, while a public JWKS route exposes verification keys for third-party consumers. Role-scoped access is enforced via modular guards, with session-based authentication planned for first-party web sessions.
The matching system blends relevance and fairness by combining distance containment, price fit, category/competency match, listing freshness, and Bayesian worker rating into a configurable score. The query builder pre-filters by geometry and competencies before ranking, targeting sub-500 ms feed latency under spatial
indexing. A focused test suite with Jest unit tests validates token/key rotation, keystore lifecycle, query-builder filters, and geospatial utilities.
Operational deployment is packaged for Dokploy (API, database, secrets) with optional Tailscale access, while OpenAPI/Swagger documentation ensures discoverability.
Radesso contributes a cohesive blueprint—and a working core—for a localized job-seeking platform where workers proactively seek orders. The near-term roadmap includes reviews and appeals, enhanced admin moderation, and telemetry, positioning Radesso to evolve into a trusted, geospatially precise hub for local work.
The front end is built with React and Leaflet (Leaflet.draw over OpenStreetMap tiles), allowing workers to define one or more work areas by drawing circles, rectangles, and polygons. On the server, a NestJS, TypeORM, PostgreSQL/PostGIS stack normalizes incoming GeoJSON to SRID 4326 (WGS84) and consolidates all shapes into a canonical MultiPolygon with GiST indexing for efficient spatial queries [1].
Security is managed through a production-grade authentication subsystem, including OTP email verification, Google OAuth, and short-lived JWT access tokens (RS256/ES256) carrying a kid header mapped to a database Keystore and Signing Key tables. Refresh tokens are device-scoped, hashed, and rotated on use, while a public JWKS route exposes verification keys for third-party consumers. Role-scoped access is enforced via modular guards, with session-based authentication planned for first-party web sessions.
The matching system blends relevance and fairness by combining distance containment, price fit, category/competency match, listing freshness, and Bayesian worker rating into a configurable score. The query builder pre-filters by geometry and competencies before ranking, targeting sub-500 ms feed latency under spatial
indexing. A focused test suite with Jest unit tests validates token/key rotation, keystore lifecycle, query-builder filters, and geospatial utilities.
Operational deployment is packaged for Dokploy (API, database, secrets) with optional Tailscale access, while OpenAPI/Swagger documentation ensures discoverability.
Radesso contributes a cohesive blueprint—and a working core—for a localized job-seeking platform where workers proactively seek orders. The near-term roadmap includes reviews and appeals, enhanced admin moderation, and telemetry, positioning Radesso to evolve into a trusted, geospatially precise hub for local work.
Keywords
Nest, PostgresQL, PostGIS, JWKS, React, Leaflet, job-seeking platform