N NONENED.IO High-load systems, DevOps, AI Request an audit
Services

Architecture, infrastructure, and AI layers for real products.

We take ownership of the technical surfaces that usually become fragile first: high-load backend systems, servers, release flow, observability, video delivery, and AI integration inside engineering and product workflows.

What we deliver

Main service areas

We can solve a specific operational or architectural pain point, or take on a connected set of work when the system needs broader reinforcement.

High-load platform engineering

  • API and internal service architecture built for traffic and product growth.
  • Caching, background queues, balancing, resilience, and failure handling.
  • Query optimization, data flow cleanup, and elimination of backend bottlenecks.

Servers, DevOps, release engineering

  • Linux servers, containers, reverse proxies, SSL, DNS, and networking.
  • CI/CD, secrets, rollback paths, logging, alerting, and safer delivery.
  • Release flows that do not depend on manual steps and one-off shell magic.

AI integration and automation

  • RAG systems, assistants, knowledge tools, and internal copilot-style workflows.
  • Automation for support, moderation, search, knowledge retrieval, and triage.
  • LLM integration inside existing services, admin panels, and delivery processes.

Video delivery and player stack

  • Origin, CDN, secure links, player embeds, and JW Player integration work.
  • Surrounding infrastructure for access control, analytics, logs, and stable playback.
  • Media delivery architecture designed for growing view counts and heavier traffic.
Formats

How we can plug in

  • Audit and action plan. When you need to see exactly what blocks scale, speed, or stability.
  • Implementation sprint. When you need a tight series of practical changes in code and infrastructure.
  • Delivery partnership. When the platform needs a technical partner across several stages of growth.
Stack

The tools we work with

TypeScript Python Go PostgreSQL Redis Docker Swarm Nginx Traefik GitHub Actions Prometheus Grafana OpenAI Claude Embeddings Vector DBs
Outcome

What the business gets

Not just technical language. The outcome should show up in release confidence, graphs, logs, performance under load, and day-to-day team speed.

Predictable production behavior

Better observability, fewer manual steps, clearer incident causes, and more stable runtime behavior under load.

Faster change cycles

CI/CD, standardized environments, and cleaner delivery paths shorten the distance from task to production.

Less technical chaos

The system becomes less dependent on one person who knows the server history by memory and more reproducible for the team.

AI as actual leverage

Automation and intelligence layers save time for the team instead of becoming another experimental side service.

Start point

You can start with the most painful layer

High-load backend, infrastructure audit, AI integration, or a video and media delivery buildout are all valid starting points.

Discuss a project See the team