Reason Machines
Reason Machines provides an autonomous software engineering platform that handles tasks end-to-end, from reading a GitHub issue to opening a verified, review-ready pull request. The system reproduces bugs in isolated workspaces, implements fixes grounded in repo memory, and runs tests, types, and builds before merging. It also operates in continuous mode to triage operational alerts and close incidents with verified fixes.
- Developer Tools
- AI Agents
- Artificial Intelligence
- Software Only
- Enterprise Software
Funding
Raised to date
$500KRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Founder details are not available yet.
Product
Problem
Engineering teams lose significant time to context switching, manual code review loops, and repetitive maintenance tasks that pull developers away from high-value work. Modern AI coding tools often produce unverified patches that require multiple iteration cycles, and operational alerts frequently trigger unnecessary manual triage, slowing down both feature development and incident response.
Solution
Reason Machines provides an autonomous software engineer that owns tasks end-to-end from issue to pull request. The platform reads a GitHub issue, reproduces the problem in an isolated workspace, implements a fix grounded in repo memory built from past runs, then verifies changes by running tests, types, and builds in the same workspace before opening a review-ready pull request. Reason also operates in continuous mode, watching live operational signals, running runbook playbooks in isolated environments, and closing incidents with verified fixes. All work is visible in a single threaded session where users can follow progress, steer the work, inspect diffs, and request additional passes before accepting changes. The harness is built around a minimal set of general-purpose tools with parallel tool execution, reducing token usage and cost compared to call-per-tool alternatives.
Target Audience
Primary customers are software engineering teams and platform operations groups at startups and enterprises that want to offload routine bug fixes, feature implementation, and incident response to an autonomous agent while retaining human review of all changes.
Features
- Autonomous agent that reproduces bugs in isolated workspaces before writing any code
- Repo memory built from prior runs so patches match project conventions rather than generic defaults
- Verification pipeline that runs tests, types, and builds in the same isolated workspace, sending incomplete work back to implementation automatically
- Operations automation that triages alerts, dedupes incidents by blast radius, executes runbooks, and ships fixes as pull requests with updated runbook memory
- Parallel tool execution via a codemode tool that runs JavaScript calling other tools, enabling search, file reads, and test runs in a single model call
- Cross-platform availability via web, macOS desktop app, and mobile browser with session continuity across devices
- Enterprise security with zero data retention by default, SOC 2 Type II and GDPR compliance in progress, access controls, audit-log management, and penetration testing within the last 12 months
- Plugin and skills system for connecting custom APIs, reusable skills, and internal tools so the agent can test and run a team's own product