Arkwright

Autonomous AI Engineering

This engineer loves backlog, and he never needs to sleep.

Devin is not an autocomplete. It is an autonomous agent for scoped engineering tasks, backlog triage, and legacy codebase modernisation under human review. Arkwright helps you integrate Devin into governed delivery workflows so output improves without losing engineering control.

# eng-backend
PM
Sarah (Product)10:42 AM

@DevinCould you pick up PROJ-402? The checkout timezone bug is affecting EU users. Needs a quick fix before the weekend.

Workspace // PROJ-402
New Task Assigned

Engineering Teams Are
Drowning.

Midmarket engineering is a constant battle between greenfield innovation and technical debt. Devin fundamentally changes the math.

The Endless Backlog

Feature requests and low-priority bugs pile up in Jira because your senior engineers are too busy fighting fires or building core IP.

Impact: Velocity Bottleneck

Legacy Tech Debt

Sprawling, undocumented monoliths that no one wants to touch. Migrations stall because they are too tedious for human engineers to endure.

Risk: Innovation Stalled

The PM Bottleneck

Non-technical stakeholders wait weeks for simple UI tweaks or data pulls because they cannot execute on the codebase themselves.

Dependency: Eng Queues
Agentic Integration

Native to Your Ecosystem.

Devin isn't another tab you have to keep open. It lives where your team works—in Jira, Slack, and GitHub.

Jira / Linear
Ticket Created
Slack
@Devin Assigned
Devin
Agentic Execution
GitHub / GitLab
PR Submitted
Team
Human Review

What Can Devin Do?

From clearing tedious bug queues to rewriting enterprise Java, Devin tackles the work that slows your team down.

Backlog Annihilation

Feature requests pile up while your engineers fight fires. Devin acts as an autonomous contributor that PMs can assign to low-priority or tedious tickets directly from Jira or Linear. It reads the ticket, navigates the repo, and submits PRs while your team sleeps.

Sprint Board (Auto-Assigned)0 Tasks Active
Queue pulled from Jira — your engineers never opened these tickets.
Scroll to explore

The
Semantic Layer.

Devin doesn't just write code; it reads it. With DeepWiki, Devin crawls your entire legacy codebase and documents it in plain English.We configure this as an MCP, allowing any employee to query your technical architecture using just Slack, and allowing your engineers to build upon it with full context using tools like Claude Code, Cursor, and GitHub Copilot.

Raw Source
Legacy Repo
Undocumented Source
Processing
DeepWiki
Semantic Mapping
Final Output
Shared Context
Technical Wiki (English)
"How does the legacy payment routing work?"
Context provided by DeepWiki MCP

Built for
Scale.

Devin belongs in delivery systems with clear scope, human review, and measurable engineering outcomes. We help teams turn autonomous engineering from a vendor demo into a governed operating rhythm.

PRs
Reviewed Delivery

Devin can draft pull requests for scoped work, but the merge still belongs to your engineering review process.

Pilot
Expansion Path

Start with one narrow backlog or maintenance workflow, then expand only when the controls and evidence hold up.

MTTR
Incident Triage

Connect alerts, logs, and runbooks so Devin can investigate incidents quickly while humans approve production changes.

Docs
Codebase Context

DeepWiki turns legacy code into searchable context your engineers can query before Devin starts changing files.

Why Partner with
Arkwright?

Deploying Devin at scale requires more than just an API key. We help you synchronize your entire technical ecosystem onto a single, high-fidelity context layer.

  • Unified Semantic Layer (DeepWiki + MCP)
  • Enterprise-Grade RBAC & AD Integration
  • Cross-Tool Context Sync (Devin to ChatGPT)
  • PM & Engineering Delegation Frameworks

Devin Core

Secured by Arkwright

Deployment Scoping

Ready to clear your
first 100 tickets?

Book a scoping session to identify which parts of your legacy codebase and Jira backlog Devin can start resolving on day one.