Imagine a company wants dozens of AI coding assistants working at once — reviewing pull requests, fixing bugs, investigating issues — instead of each engineer running one assistant alone on their laptop. Ellipsis is the infrastructure that makes that possible: it hosts the sandboxes where the agents run, hands out temporary credentials so they can only touch what they need, tracks exactly how much each session costs, and keeps a full audit trail of what every agent did. It's a bit like managing a fleet of very capable interns — useful work gets done in parallel, but a manager is always watching the budget and the paper trail, so nothing runs unsupervised or out of control. Technically, teams define agent behavior as config-as-code: a single YAML file per repository where a commit deploys the configuration, a pull request proposes a change, and a revert rolls it back. Agents can be triggered by cron schedules, GitHub events, Linear issues, Sentry alerts, Slack mentions, or direct REST/CLI calls, and dozens of sessions can run in parallel. Each session gets scoped credentials and runs in an isolated sandbox that is torn down afterward, with hierarchical spend caps enforced at the account, agent, session, and developer level over rolling windows. Every step is logged with its individual cost, transcript retention is configurable from 7 to 365 days, and no source code is retained once a session ends.
| # | Tool | Best for | Price |
|---|---|---|---|
| 1 | Équipes dev utilisant des agents IA pour générer du code et ayant besoin d'une vérification CI rapide et fiable | — | |
| 2 | Équipes d'ingénierie qui veulent exécuter des agents de code IA à l'échelle sans gérer leur propre infra de sandboxing | — | |
| 3 | Développeurs et équipes ayant besoin de collecte de données web à grande échelle | — | |
| 4 | Équipes d'ingénierie et départements R&D de moyennes/grandes entreprises tech voulant automatiser tout le cycle de livraison logicielle | — | |
| 5 | Équipes QA et ingénierie construisant des pipelines CI/CD avec des flux d'inscription/vérification par email | — | |
| 6 | Développeurs, designers, entrepreneurs et fondateurs non-techniques voulant coder avec un agent IA sans machine locale | — | |
| 7 | Développeurs et petites équipes voulant déployer et gérer des applications sans expertise DevOps approfondie (Docker, Kubernetes) | — | |
| 8 | Équipes utilisant déjà un agent de code IA (Claude Code, Copilot) et voulant lui donner accès au contexte de production réel pour corriger les bugs | — | |
| 9 | Grandes organisations d'ingénierie avec un besoin de conformité fort (banque, santé, entreprise réglementée) voulant automatiser la maintenance et la sécurité du code | — | |
| 10 | Développeurs et équipes qui déploient et gèrent des APIs en production et veulent regrouper déploiement, clés API et observabilité | — | |
| 11 | Équipes produit qui déploient souvent des changements d'UI et veulent une couverture de tests bout-en-bout sans écrire ni maintenir de suite Playwright/Cypress | — | |
| 12 | Développeurs individuels, petites et moyennes équipes, entreprises voulant simplicité de déploiement avec contrôle d'infrastructure et sans dépendance fournisseur. | — |
Runs your GitHub Actions workflow on your own laptop in an isolated, disposable virtual machine that boots in under 200 milliseconds — so you can see if a change actually passes CI in seconds, without pushing a commit and waiting for a runner.
A cloud API that runs AI coding agents (Claude Code, Codex, OpenCode) on demand in isolated sandboxes, billed by the second, so you don't have to host the infrastructure yourself.
Browser infrastructure for web scraping at scale — thousands of concurrent sessions with fingerprints that pass major bot-detection tests, so you don't have to build and maintain anti-detect infrastructure yourself.
Agentic platform that takes a backlog of tickets through to reviewed pull requests autonomously, with real-time visibility and human oversight.
Gives your automated tests a real, working email inbox to sign up with — so a Playwright or Cypress test can grab the actual OTP code or confirmation link instead of getting stuck at a login screen.
A cloud environment where you get a real Linux machine with SSH and a browser terminal, pre-wired to run Claude Code and OpenAI Codex, so you can code with an AI agent from any device without setting up a local machine.
A deployment platform where you can tell an AI agent what you want in plain language — 'deploy this repo and set up a Postgres database' — and it handles the server work, instead of you configuring Docker and Kubernetes by hand.
A bridge between your AI coding assistant and what's actually happening in production, so tools like Claude Code or Copilot can see the real error and fix it, instead of guessing from a bug report alone.
A fleet of AI software engineers that fix bugs, patch security holes, and modernize old code on their own, running inside your company's private cloud with a full audit trail of what they did.
One place to deploy an API, issue and revoke API keys for it, rate-limit it, and watch its logs — instead of stitching together four separate services to do each job.
An AI that clicks through your app like a real user would, on every pull request, to catch broken buttons and broken flows that your unit tests never touch.
Deploy your app the way you would on Vercel or Heroku — push and it's live — except it runs on a server you own, so there's no per-request bill or platform lock-in.
