Live prototypeGitHub Issue Fixer workflow

ReiOps makesAI agents safefor businesses.

ReiOps makes AI agentssafe for businesses.

Deploy vetted AI workflows in secure sandboxes with monitoring, approval gates, audit logs, and managed support.

Marketplace workflowsSecure sandboxesApproval gatesAudit logsSLA support

Active agent task

GitHub Issue Fixer

A managed ReiOps workflow that fixes small GitHub issues, runs tests, and asks for approval before opening a PR.

Running
GitHub issue source

#128 auth/login timeout after idle session

Agent branch

fix/login-timeout

Live trace events8 events
10:42GitHub issue #128 assigned to agent
10:43Created branch fix/login-timeout
10:44Edited src/auth/session.ts
10:45Ran tests - 1 failing
10:47Applied fix

Policy blocked a risky agent action

Medium risk

GitHub Issue Fixer wants to open a PR touching authentication logic.

Cost meter

$0.61

session total

Files changed

2

+42 / -11

Tests

Passing

npm test

Lint

1 warning

non-blocking

Managed Marketplace

Deploy curated AI workflows instead of raw agents or random scripts.

Secure Sandboxes

Run every workflow in a controlled environment with scoped permissions.

Approval Gates

Block risky actions before workflows touch customers, code, CRMs, or production.

Managed Support

Add monitoring, audit history, health checks, and SLA-backed support.

Problem

AI agents are becoming capable. Team operations are not.

Coding agents now write code, run tests, open PRs, and touch infrastructure. But their work is still scattered across CLIs, chat threads, logs, and GitHub branches. Teams need visibility, permissions, audit trails, and approval flows before they can trust agents with real engineering work.

No visibility

Teams cannot see what agents are doing in real time.

No control

Agents can touch files, repos, infra, or secrets without clear approval gates.

No audit trail

When something breaks, there is no clean trace of prompts, tools, changes, and decisions.

No cost ownership

Token and model spend becomes invisible across a team.

Core capabilities

A managed operations layer for vetted AI workflows.

Deploy workflows in secure sandboxes, monitor live execution, inspect audit-ready traces, approve risky actions, and ship reviewed outcomes with managed support.

Vetted Workflow Deployment

Launch curated workflows such as GitHub Issue Fixer from one managed workspace.

Monitoring & Traces

Inspect tool calls, terminal commands, file changes, model outputs, and errors.

Human Approval Gates

Require review before workflows modify sensitive systems, open PRs, deploy, or touch secrets.

GitHub Issue Fixer

Turn GitHub issues into sandboxed runs, tested changes, policy approvals, and PRs.

Audit Logs & Cost Tracking

Understand what happened, who approved it, and how much every workflow run costs.

Managed Support

Add support, health checks, and operating procedures around AI workflow adoption.

Workflow

GitHub Issue #128 to PR #341.

GitHub Issue Fixer follows the path every team understands: GitHub Issue #128, secure sandbox, trace, tests, policy approval, and PR #341.

01

Issue

02

Agent branch

03

Live trace

04

Tests

05

Human approval

06

Pull request

07

Review

Agent trace demo

Every workflow run becomes inspectable.

ReiOps records the full execution trail: source issue, sandbox events, tool calls, terminal output, files changed, test results, approval events, and final PR.

Trace timeline
run_2KQ6-FIX-AUTH
[10:42]GitHub issue #128 assigned to agent
[10:43]Created branch fix/login-timeout
[10:44]Edited src/auth/session.ts
[10:45]Ran tests - 1 failing
[10:47]Applied fix
[10:49]Tests passing
[10:50]Approval required before opening PR
[10:52]Pull request #341 opened

Run details

Files changed

2

Commands run

npm test, npm run lint

Cost

$0.61

Risk

Medium

Approval

Required before PR

Security and trust

AI workflows need controls, not blind trust.

ReiOps is designed around secure sandboxes, human approval, scoped credentials, audit logs, and managed support so businesses can adopt AI workflows without uncontrolled side channels.

Approval gates before merge, deploy, secrets, or production changes

Audit logs for every agent action

BYOK for model and workspace credentials

Per-repo and per-agent permissions

Human override for dangerous actions

Prototype proof

Built from Rei, our internal agent operating system.

ReiOps grew out of Rei, an internal Telegram-first agent operating system started in late January 2026. The prototype foundation includes a bot interface, Mini App dashboard, Git-backed workspace, BYOK settings, scheduled workflows, and human-in-the-loop controls.

Telegram-first control interface

Mini App dashboard

Git-backed workspace

BYOK credentials

Human-in-the-loop controls

Scheduled agent workflows

Demo workflow

See ReiOps in action

Deploy a vetted GitHub Issue Fixer workflow, watch the agent run in a secure sandbox, inspect the trace, approve the risky action, and see the final PR.

Early design partners

Building with early design partners.

We are looking for AI-native dev teams and agencies already using coding agents in GitHub workflows.