Turn AI into a disciplined engineering partner.
AI makes your team faster. It also makes your repo harder to trust. Devory keeps the speed without the drift.
Bounded tasks, repo-aware execution, and artifacts your team can review.
Execution Flow
One visible path from request to production-ready output.
Most AI tools optimize for output. Devory optimizes for what survives production.
Sound familiar?
You already use AI to write code. The hard part comes after.
The output is fast. But then you spend time cleaning it up, explaining it, or quietly not trusting it. Context disappears between sessions. The same standards issues come up in every review.
This is not a model quality problem. It is a workflow problem.
Problem
AI made code generation cheap. It also made engineering drift cheap.
The code comes faster. Review gets murkier. Scope gets fuzzier. You still have to clean it up.
Product
What Devory actually is
Devory is the missing structure between a prompt and a pull request: tasks, doctrine, repo-aware execution, artifacts, and review.
Structured Tasks
Start from bounded work with acceptance criteria instead of asking AI to infer the problem from a prompt.
Less time reconstructing intent. Less output you cannot explain.
Runs And Artifacts
Each run leaves durable output your team can inspect, not just chat history.
You can read what happened. So can the reviewer.
Doctrine Enforcement
Apply engineering rules, testing expectations, and reusable skills as part of the workflow.
Standards stop being enforced by hand in review.
Human Review Stays Real
Approval, send-back, and blocking stay explicit. Devory moves faster without pretending review is optional.
Engineers stay in control. AI does not decide when work is done.
How It Works
A workflow for controlled AI-assisted engineering
Instead of hoping a prompt is safe, Devory forces the work through the steps your team already needs: define it, execute it, inspect it, review it, ship it.
Why Devory
Not just another AI coding tool
Most AI tools help you produce code. Devory helps you trust what gets reviewed and merged.
Fast suggestions, but no real workflow for scope, review, or doctrine.
Powerful, but easy to over-trust when execution is broad and context is loose.
A disciplined system for turning AI into bounded, reviewable engineering work.
Devory is a system. Not a suggestion engine.
Built for teams and serious solo developers who need to explain what changed and whether it should ship.
Pricing
Core, Pro, and Teams
Start local. Move up when you need more reach, visibility, or shared governance.
For solo developers who want the structured local workflow and bring their own model setup.
Use Core if you want the workflow discipline without a subscription. Keep it local.
- Local repo-first workflow
- Task lifecycle system
- Doctrine and skills
- Bring your own model or API
For developers who want Devory across devices with more operational support than a local setup can give.
Move to Pro when you want cross-device access, notifications, and more built-in templates.
- Everything in Core
- Work across devices
- Factory notifications
- Advanced doctrine capabilities
- More doctrine and skill templates
- Web app access for runs, artifacts, review, and planning
For teams that need shared governance and a cleaner way to run Devory together.
Use Teams when more than one person needs shared doctrine, coordination, and control.
- Up to 5 members
- Team seat management
- Invites and member roles
- Org-level governance
- Shared operational control
- Contact us for larger or controlled-environment deployments
Need a larger team plan or a controlled offline deployment? Contact us.
Delivery
Built for real engineering teams
And for serious solo developers who want a system.
Without Devory, AI adds drift. With Devory, it follows a workflow.
Code generation is not the hard part. Keeping the repo healthy while AI changes it is.
Smaller tasks, explicit standards, durable artifacts, and review controls keep engineers in charge of what ships.
Built for production
Not prompt theater.
Devory is not trying to impress you with autonomy. It is trying to make AI output fit the process you have to live with.
FAQ
Practical answers for technical teams
The product is meant to fit serious software delivery, so the questions tend to be practical too.
What is Devory.AI?
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Devory.AI is a structured AI-assisted development system that turns ideas into small, reviewable, testable units of work inside the workflows engineering teams already trust.
Is the core product really free?
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Core is the local repo-first workflow: workspace initialization, tasks, doctrine, runs, artifacts, and bring-your-own model usage.
What is the difference between Core, Pro, and Teams?
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Core is the local repo-first workflow. Pro adds cross-device access, factory notifications, more doctrine and skill templates, advanced doctrine features, and the hosted web app for runs, artifacts, review, and planning. Teams adds seats, roles, and shared governance for coordinated engineering work.
How is Devory different from Copilot or AI agents?
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Copilots help at the keyboard. Raw agents automate aggressively. Devory adds workflow discipline: bounded tasks, doctrine, repository-aware execution, artifacts, and explicit review.
Does Devory replace developers?
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No. Devory is built to support engineers, not replace them. It helps teams keep human judgment in the loop while reducing prompt chaos and unreviewable output.
Can teams use Devory in existing repos?
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Yes. Devory is designed for existing repositories. It adds structure around work rather than forcing teams into a separate coding environment.
Is Devory good for small teams?
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Yes. Small technical teams tend to feel AI workflow chaos quickly because everyone reviews everyone else's code. Devory gives those teams structure without enterprise overhead.
Will there be larger team plans later?
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Yes. Larger subscriptions and controlled offline or walled-environment deployments are available by contact. If you need broader rollout, more seats, or stricter environment controls, use the contact link and we can route it directly.
Start Here
Give your AI workflow an engineering spine.
Run one workflow with Core and the difference is obvious. Move up when you need it across devices, with more visibility and control.