Websites are legally required in many countries to work for people who use screen readers, can't see well, or can't use a mouse — things like proper color contrast, image descriptions, and keyboard navigation. Checking for all of that by hand is slow and easy to miss, and getting it wrong can mean lawsuits or fines under laws like the ADA in the US or the European Accessibility Act. DevAlly automates that checking: it scans a site, flags exactly what's broken, and suggests the code to fix it, instead of leaving a team to interpret a long compliance checklist on its own. DevAlly is an AI-powered accessibility compliance platform that plugs into GitHub and CI/CD pipelines, catching accessibility regressions before they ship rather than after a site goes live. It automates WCAG 2.2 AA/AAA checks, flags issues like low color contrast, missing alt text, keyboard traps and unlabeled form controls, and generates code-level fixes plus legal-grade documentation such as VPAT/ACR compliance reports. The company, based in Ireland, has been covered by TechCrunch and Fortune and was a KPMG Global Tech Innovator 2026 finalist. It offers a free tier (5 audits/week, 1 product, 3 seats) and custom-priced Growth and Compliance tiers, the latter including a manual expert audit and dedicated support.
| # | Tool | Best for | Price |
|---|---|---|---|
| 1 | Développeurs et équipes utilisant des agents de codage IA (Cursor, Claude Code) ayant besoin d'un backend géré sans le maintenir eux-mêmes | — | |
| 2 | Équipes plateforme/entreprise qui doivent faire passer des agents IA du pilote à la production en environnement régulé | — | |
| 3 | Developers running long or complex background jobs, batch processing or AI agents | — | |
| 4 | Backend and full-stack teams needing reliable background jobs, workflows or AI-agent orchestration | — | |
| 5 | Fortune 500 enterprises | Government agencies | Banks, airlines, healthcare with mainframe systems | — | |
| 6 | Développeurs et équipes ML cherchant du compute GPU à bas coût pour l'entraînement ou l'inférence | — | |
| 7 | Entreprises européennes et internationales cherchant une alternative crédible aux hyperscalers US pour du compute IA | — | |
| 8 | AI/ML and infrastructure teams managing Kubernetes/Slurm clusters and multi-cloud GPU costs | — | |
| 9 | Enterprises deploying compute and AI inference at physically distributed edge locations (manufacturing, logistics, retail, energy) | — | |
| 10 | Engineering and platform/DevOps teams wanting continuous, automated CI/CD and incident monitoring | — | |
| 11 | Teams building and deploying autonomous multi-agent AI systems at scale | — | |
| 12 | Engineering leaders, CTOs, platform engineering and SRE teams at large organizations needing service-quality visibility across many teams | — |
A full backend a coding AI can spin up and copy for itself — instead of a human wiring up a database, login system, and file storage by hand, an AI coding agent asks InsForge for a complete backend, and can clone an isolated copy of the whole thing to exp
Most companies can get an AI agent working in a demo; CreateOS is built for the much harder next step — running it safely in production with governance, kill-switches and audit trails a security team will actually approve.
An open-source platform for writing long-running background jobs and AI-agent workflows in TypeScript or Python, with automatic retries, queuing and scaling — and no timeouts, so tasks can run as long as they need.
A platform for running reliable background jobs, scheduled tasks and multi-step workflows — it automatically retries failures and remembers where each job left off, so long-running processes don't silently break.
AI platform (Imogen) that rewrites legacy mainframe systems — COBOL, CICS, DB2 — into modern cloud code by replicating exact behavior, not just translating syntax.
A marketplace where anyone with a spare gaming or server GPU can rent it out, so AI developers get GPU compute at a fraction of the price big cloud providers charge — like Airbnb, but for graphics cards instead of spare rooms.
A European, publicly-traded cloud built specifically for AI workloads — GPU clusters, training, inference — for companies that want serious AI compute without depending on a US hyperscaler.
Open-source tool that automatically finds and runs your AI training jobs on whichever cloud or cluster has the cheapest available GPUs.
Edge orchestration platform that remotely manages, secures and updates AI inference and applications across thousands of distributed edge devices.
AI DevOps agent that watches your CI/CD pipeline, investigates failures, reviews code and triages incidents around the clock.
Cloud infrastructure for running autonomous AI agents at scale, with millisecond sandbox startup and near-zero idle cost.
Internal developer platform that auto-maps a company's services into a catalog and uses scorecards to track production readiness, compliance and AI-adoption impact.
