Your AI should know your architecture before it writes a line of code.

DevNitro is the Intelligent Engineering Platform. It scaffolds production-grade projects, hands AI agents your architecture, and keeps every commit true to your patterns.

Your architecture. Your patterns. Your standards. Automatic.

Your developers have AI. Your organization doesn't.

Your developers already have coding assistants, chat tools, and coding agents. But leadership still sees the same problems:

Backlog keeps growing

More tools haven't meant more shipped software.

Context gets lost

Every session starts from scratch. Every handoff costs hours.

AI fights your architecture

Coding agents guess your patterns. Developers spend half their time correcting AI output.

Senior engineers become coordinators

Your most expensive people explain instead of build.

The problem was never AI access. The problem is turning AI into an engineering system that knows how your team builds software.

This is Intelligent Engineering.

Intelligent Engineering is the operating model for engineering organizations in the AI era. DevNitro is the platform that puts it to work: opinionated blueprints, context continuity, backlog-driven execution, and provider independence.

AI-Assisted Coding

Improves what one developer can do in a session.

Intelligent Engineering

Improves what your entire engineering organization can ship in a quarter.

See it work.

Not a chat window. DevNitro runs multiple agents against your real codebase at once, clearing issues from your backlog and verifying their own work.

One run, many workers, one view. Capacity you set, not an accident of who opened which chat.
One blueprint, applied. A real production-grade solution, structured the way your team builds.
Each worker builds in its own worktree. Work merges back only after the build and test gates pass.

Your architecture, inherited. Not guessed.

DevNitro is an operating model, not a code generator. Blueprints are how your architecture gets in: production-grade scaffolding that carries your conventions, your patterns, and your AI instructions, so agents inherit your decisions before they write a line.

Start on a built-in blueprint

A production-grade foundation you can ship on today. Real auth, data access, testing, and conventions already wired, so the AI follows your standards from the first file.

See what's inside a blueprint
Or bring your own architecture

Have your own best code encoded into a company blueprint, so every project and every agent inherits the decisions your senior engineers already made.

Encoded by GlobalCove, our blueprint partner

Coding assistants guess. DevNitro knows.

What DevNitro does.

Opinionated Scaffolding

Start every project with production-grade blueprints. Full stack. Real patterns. AI-ready from the first file.

Context Continuity

Conversations persist across sessions and contributors. Resume where you left off.

Backlog-Driven Execution

Work starts from epics and issues, not blank prompts. DevNitro coordinates across issue trees.

Parallel Execution

Seats and workstreams make parallel AI work explicit and controllable.

Browser-to-CLI Relay

Coordinate in the browser. Execute against your real codebase through a local CLI listener.

Provider Independence

Run on Claude, Copilot, Codex, or Ollama. Switch providers when the market shifts.

What DevNitro is not.

If you are picturing another AI chat tool, you have the wrong picture.

Not another chat interface

The value isn't a better conversation with an AI. It's a better system for how work gets started, executed, and verified.

Not a low-code platform

The output is real, production-grade code that follows your team's actual engineering patterns.

Not replacing developers

It removes the drag, context loss, AI correction, and coordination overhead, so developers go back to engineering.

How it works.

1
Scaffold

DevNitro generates a production-grade project from an opinionated blueprint. Every layer follows established patterns.

2
Execute

Define work as epics and issues. DevNitro claims issues, spins up workstreams, and executes against your codebase.

3
Verify & Ship

Visual verification confirms results. Context is preserved. Your team reviews and ships with full continuity.

The math is simple.

A mid-level developer costs roughly $15,000–$20,000 per month fully loaded.

Two of the biggest drains on that investment are:

  • Context rebuilding: re-explaining architecture, recovering state, re-reading code
  • AI correction: fixing generated code that doesn't follow your patterns

If DevNitro helps a single mid-level developer recover just 15% of their execution capacity, that's $2,250–$3,000 in recovered value per month.

$1,000/month per builder seat
~5–7% pays for itself

You only need to reclaim about 5–7% of a developer's time for a seat to pay for itself. Everything above that is upside.

No vendor lock-in. Ever.

Model vendors change. Capabilities shift. Pricing moves. DevNitro keeps your work separate from any one provider.

Claude Code
Anthropic
GitHub Copilot
Microsoft
OpenAI Codex
OpenAI
Ollama
Local / Self-hosted

Built for engineering leaders.

DevNitro is strongest in software organizations with 20–200 developers where:

Backlog grows faster than execution capacity

Senior engineers spend too much time coordinating

AI adoption lacks consistency across teams

Multiple teams need shared architectural patterns

Want your team onboarded with proof?

You can start self-serve today. If you would rather see it installed on your own backlog with a measured before and after, GlobalCove runs the Intelligent Engineering Sprint: a six-week engagement that puts DevNitro to work alongside your team and compares throughput against your own history.

Explore the Sprint Opens GlobalCove, our delivery partner

Stop correcting your AI. Start building with it.

DevNitro is the Intelligent Engineering Platform. Software your team can trust, support, and scale.

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