Orchestrate AI coding agents in parallel with multi-agent workflows
Data updated Jun 24, 2026 · Traffic data: SimilarWeb (estimated)
Stoneforge allows users to run teams of AI coding agents with automatic merge, dependency-aware dispatch, and a real-time web dashboard.
stoneforge is an AI tool tracked by Relve in the AI Engineering Tools category. It uses a Paid pricing model and runs on the web at stoneforge.ai.
The Relve catalog tracks 500+ live tools in AI Engineering Tools. stoneforge is part of the editorial tracking surface, with a Domain Rating of 9 on Ahrefs' authority scale.
Closest alternatives: Abyss Hub, ACE Studio, Actionbook, Action Sync, Adaapt.AI. Compare stoneforge head-to-head with any of these on the /compare surface — same feature axes, pricing tiers, and traffic side-by-side.
Best for: teams looking for ai engineering tools-class capabilities with a paid entry point. The Relve editorial team refreshes traffic, ranking, and feature data for stoneforge on a rolling 24-hour cycle (last updated Jun 24, 2026), so the numbers above reflect the most recent snapshot of where the tool sits in the market. Traffic figures are SimilarWeb estimates.
Multi-agent workflows
Run teams of AI coding agents in parallel with automatic merge and dependency-aware dispatch. This allows for efficient task management and reduces the chances of duplicated work or conflicts between agents. Users can monitor the entire process through a real-time web dashboard.
Real-time dashboard for everything
See every agent's live output, task progress on a kanban board, merge status, and performance metrics — all in one web dashboard. This feature provides visibility into the orchestration process, allowing users to track the status of tasks and agents effectively.
Dependency-aware task dispatch
The dispatch daemon tracks task priorities and dependencies, automatically assigning ready tasks to idle workers. This ensures that tasks are completed efficiently without duplication or blocked starts, optimizing the workflow.
Automatic merge review
The Steward agent runs tests, squash-merges on pass, and creates fix tasks on failure. This feature automates the review process, ensuring that code quality is maintained without manual intervention.
Manage and track agent task assignments
Users can create, assign, and track tasks for AI agents, allowing for organized management of workflows. This feature includes options for sorting and filtering tasks based on their status, priority, and assignee.
Create and manage workflows
Users can create workflow templates that instantiate into resumable task sequences with durable state. This allows for structured management of complex tasks and ensures that workflows can be resumed from where they left off.
Evergreen documentation
Versioned document libraries with full-text and semantic search provide up-to-date context for users. This feature ensures that all team members have access to the latest documentation, improving collaboration and knowledge sharing.
Multi-provider support
Stoneforge works with multiple AI coding agents, including Claude Code, OpenCode, and OpenAI Codex, ensuring users are not locked into a single provider. This flexibility allows teams to choose the best tools for their needs.
Bidirectional sync with issue trackers
When an agent fixes a bug, the linked GitHub Issue or Linear ticket is updated automatically with a summary of the fix, a link to the merge request, and which tests were added. This feature streamlines communication between development and issue tracking.
Regression tests with every fix
Every AI bug fixing result comes with a regression test. The agent writes a test that fails without the fix and passes with it, ensuring that the same bug doesn't reappear. This feature enhances code reliability and quality.
Automated test generation
AI test generation with Stoneforge creates tests across your codebase in parallel. Multiple automated testing AI agents work simultaneously, each targeting different modules to boost coverage quickly. This feature significantly reduces the time spent on manual testing.
Native integrations· 3
Parallel AI Development
For: Engineering Team
AI Bug Fixing & Automated Triage
For: Engineering Team
AI Test Generation at Scale
For: Engineering Team
Automated Code Review AI
For: Engineering Team
AI Framework Migration
For: Engineering Team
AI Code Refactoring at Scale
For: Engineering Team
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Traffic data: SimilarWeb (estimated) · updated Jun 24, 2026
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