Niteshift

Connect a repository and Niteshift reads its documentation, scripts, CI configuration and Docker files to work out how the stack actually boots, rather than asking you to describe it. Trigger a task from the web UI, by commenting on a GitHub pull request or issue, by mentioning the bot in Slack, or by assigning a Linear issue to it. The agent gets a full environment: Docker services, a branched database it can migrate without touching anything shared, a dev server with a preview URL, and a real browser. It makes its change, runs the application, exercises it in the browser and captures screenshots. When it opens a pull request, the test results, browser checks, logs and CI evaluations come attached as verification evidence rather than a claim that the work is done. A workspace view exposes the live preview, diffs, terminal, logs and a chat interface while the task runs. Dozens of isolated environments run in parallel, and webhook or schedule triggers start tasks with no human in the loop.

• •Auto-detected Environments - Reads repository docs, scripts, CI config and Docker files to configure the full stack without a bespoke setup file
• •Agent Agnostic - Runs Claude Code, Codex, OpenCode and Pi inside the same environment definition
• •Trigger From Anywhere - Web UI, GitHub pull request and issue comments, Slack mentions, and Linear issues assigned to the bot
• •Live Browser Verification - Boots a dev server with a preview URL and a real browser, capturing screenshots as evidence
• •Evidence On The Pull Request - Test results, browser checks, logs and CI evaluations attached to the PR it opens
• •Branched Databases - Agents make schema changes in isolation without touching shared data
• •Parallel Environments - Dozens of isolated environments running at once for extended periods
• •MCP Integrations - Connects to GitHub, Linear, Slack, Sentry, Datadog, AWS and Vercel over Model Context Protocol
• •Automations - Webhook and schedule triggered tasks that run without a human trigger

Teams that have adopted coding agents and discovered the review queue is now the constraint. If your engineers are spending their time pulling agent branches locally just to confirm the app still boots, this is the specific work being automated. It suits teams with non trivial stacks, because the value scales with how painful the environment is to reproduce: a static site gains little, a service with a database, workers and auth gains a lot. The agent agnostic stance means adopting it does not commit you to one vendor model. Two caveats: this is a thin and heavily contested layer that frontier labs are absorbing into their own hosted agent products, and cloud sandbox vendors are pushing up into the same workflow from below. At $250 per month for a team plus per minute credits, it also has to clear a real budget line against agent runners that ship free.