NemesisNet engineers AI-powered platforms, backend systems, and automation infrastructure — from self-hosted AI pipelines and agent integrations to production-grade full-stack systems.
Lightweight MCP bridge that lets AI agents read, update, and manage WordPress content securely via a local-first server.
A self‑hosted AI text‑to‑speech web service built on top of the open‑source Kokoro TTS engine — enabling natural‑sounding speech synthesis via a user-friendly web interface.
A full-stack car rental platform with Vue.js frontend and Java Spring Boot backend, featuring user bookings, rental history management, and admin dashboards for fleet management, user roles, analytics, and content control, with secure JWT and Google OAuth2 authentication.
Client-facing static portal built with HTML5, Bootstrap, and Dockerized Nginx—designed, shipped, and deployed in under 48 hours.
Static Java code analysis tool designed to detect quality issues and improve maintainability.
A fully-featured, production-ready personal portfolio management system with dynamic project tracking, skill management, PDF export, and backup & restore capabilities.
An experimental AI‑powered coding/typing assistant — offering voice or smart‑typing support, to speed up coding and writing workflows.
A local homestyle takeaway and food‑service spot based in Ferness Estate — showcasing local flavour and simple ordering for busy families.
NemesisNet builds real AI infrastructure — not API wrappers. Our work includes self-hosted AI runtimes, text-to-speech pipelines, MCP integrations, agent automation backends, and production-grade full-stack platforms.
Most studios offering "AI services" are connecting third-party APIs and calling it integration. We architect, deploy, and operate the underlying systems: local AI runtimes, agent pipelines, automation infrastructure, and cloud-neutral deployments running on hardware we control.
Every system ships to production standards — clean architecture, automated testing, Dockerized deployment, and continuous delivery. We handle the full stack from database schema to DNS.
A structured process keeps delivery predictable, technical risk visible, and decisions aligned before engineering time is burned.
Without proper scoping, projects usually drift into scope creep, deadline slips, and expensive rework.
Requirements, constraints, and outcomes are mapped first so success is measurable before implementation starts.
Architecture, milestones, and technical boundaries are defined early to protect timelines and reduce risk.
Build starts with testing and CI/CD from day one, with regular checkpoints to keep delivery aligned with scope.
Production rollout includes hardening, monitoring, and optional support retainers for stability after launch.
Most projects begin with a short discovery call to clarify scope, architecture, and timelines.
Transparent starting-from pricing to help with planning. Final quotes are confirmed after a short discovery call and technical scoping session.
Fast-tracked static portals, MVPs, and Dockerized deployments built to be production-ready from day one.
Typically 1-4 weeks depending on scope
End-to-end product builds with Vue 3 frontend, Spring Boot backend, secure auth, dashboards, and infrastructure.
Typically 6-14 weeks depending on scope
Self-hosted AI systems for real workloads, including TTS pipelines, agent workflows, and LLM integrations.
Typically 8-16 weeks, scoped after technical discovery
Custom MCP servers that connect AI agents to CMS, CRM, databases, and internal tooling.
Typically 3-6 weeks per integration
Two ongoing support levels so you can match budget to operational needs.
Half-day to full-day working sessions for teams making serious AI or platform decisions.
Half-day or full-day sessions, booked in advance
Note: prices are starting-from benchmarks for South Africa/Cape Town market context. Final pricing depends on scope, delivery timeline, integrations, and support requirements.