Master Integration in the Age of AI
Cadence.CI runs your CI/CD, data and AI pipelines on machines it starts in your own cloud account, and shows you every step as it runs.
Checked before anything runs, on infrastructure you already own.
Steps run on machines started in your own cloud account, at your provider's rates, and stopped as soon as the job ends.
Types, connections and parameters of the whole pipeline are validated in about a second, before any machine starts.
Live logs, debug events replayed on the pipeline graph, and the exact program and parameters of every run.
Each step gets the smallest machine that fits what it declares, no runner sits idle, and every run shows what it requested.
How Cadence.CI Works
Your pipeline is a program. Cadence.CI checks it, runs it in your cloud account, and shows you everything it did.
Write or migrate
Start from a template, or have an AI assistant write your pipeline or convert your GitHub Actions and GitLab CI workflows, with the Mélodium MCP server and skills. You get a pipeline program that lives in your repository.
QuickstartCheck and launch
The whole pipeline, types, connections and parameters, is checked in about a second. Then launch it from your laptop, from GitHub Actions or from GitLab CI.
Where it runsRun and observe
Machines start in your own cloud account and stop when the job ends. Follow each run live: pipeline graph, logs, debug events, resources.
View results
Run From Local
Build and try locally, distribute compute from your machine if needed, enjoy smooth development.
Register Cloud Project
Connect your cloud accounts and go from local runs to production infrastructure in minutes.
Observe Pipelines
Follow every run live, inspect logs and debug events, and reproduce failures without guesswork.
Manage Compute Resources
Track the machines started in each cloud account, and what every run requested.
Why is my build failing? I changed nothing!
— A Developer
It's so slooow, what is the cache doing?
— An Annoyed Colleague
Who left sixteen cores running all weekend?
— The Finance Department
Flaky, flaky, flaky… So much instability…
— Someone in Charge of Something Else
Changing CI provider means rewriting every pipeline.
— A Platform Engineer
Wait, who printed the token in the logs?
— A Security Officer
The agent pushed fifteen commits to fix the pipeline.
— Someone Reviewing the History
Find the Mistake Before the Runner Does
The same mistake in both pipelines: a step wired to the wrong input.
Usual CI
- Push
- Queue, runner setup
- Steps run until the broken one
- Red X
Read logs, guess, push again
Cadence.CI
- Check: error shown, no runner started
- Fix, check again, run
Illustrative durations. The check itself takes about a second.
Most CI pipelines fail on the runner, minutes in, after you already paid for it. Cadence.CI checks the whole pipeline before anything is provisioned, and runs it on infrastructure you already own.
A broken pipeline usually means push, wait ten minutes, read a red X, guess, push again. Cadence.CI checks the whole pipeline in about a second, before any of that.
A New Paradigm for Problems That Won't Go Away
AI writes more code faster than ever, but your pipelines, infrastructure, and workflows weren't built for this pace. Costs keep rising, projects slow down, and the old step-by-step approach can't keep up. It's time for something that actually helps developers ship.
With Github and GitLab
Your AI assistant converts GitHub Actions or GitLab CI workflows, with the Mélodium MCP server and skills.
Migrate with AIYour Next Competitive Edge
The organizations that adopt these capabilities first will set the pace others follow. Get notified when they launch and be ready to move before your competition does.
GPU management
See exactly how hard your GPUs are working. GPU-equipped machines already spawn for accelerated workloads, next up is visibility into their load: utilization and performance data for every GPU powering your pipelines.
Specific spawn procedures
Write a few lines of logic and let them pick your infrastructure for you. Small decision scripts choose the right machine or image for each spawn request from your Mélodium program, based on tags, available resources, compute price, and more.
Job hosting
Host the job itself on Cadence.CI, not just the runners that execute it, and trigger it straight from a webhook. No Mélodium program needs to be running elsewhere first to kick things off.
View and render panel
A green checkmark doesn't tell you much. Define how your job results are shown, a dedicated panel in the dashboard rendering exactly what matters for your project, images, documents, structured data, instead of the generic pass/fail status.
Integration Is Your Biggest Hidden Cost
Infrastructure is the visible part of integration costs. The larger part is developer time: waiting for results, investigating failures, maintaining pipelines. Developers report spending as much time waiting for builds and tests as writing new code.
For a 10-minute CI run a developer waits for, 99% of the cost is human time: €5.82 of developer time against €0.05 of runner compute.
Sources
- Runner: GitHub-hosted Linux 2-core x64 at $0.006 per minute (GitHub Actions runner pricing).
- Developer time: €34.9 per hour, average EU hourly labour cost in 2025, all sectors (Eurostat).
- Waiting as long as writing code: GitHub survey of 500 developers in the United States (2023).
- Conversion: 1.1181 US dollars per euro, ECB reference rate of 12 October 2026.
Beyond Waiting Time
AI agents and tokens
$13
per developer and active day spent on a coding agent, on average across enterprise deployments
An agent that can only test a pipeline by pushing waits for CI, then reads the logs again. After five minutes, the default prompt cache lifetime, it reprocesses its whole context. The check answers in about a second, before anything is pushed.
Claude Code documentation: Manage costs effectivelyIdle infrastructure
29%
of cloud spend is wasted, by the estimate of more than 750 cloud decision-makers
A machine Cadence.CI starts exists only while its step runs, and stops with it: no runner waits idle between jobs.
Flexera: 2026 State of the Cloud ReportOversized machines
< 25%
of the CPU they request is used by most container workloads, and less than half of the memory
Each step declares what it needs and gets the smallest instance that fits, ARM or x86. Every run shows what each of its parts requested.
Datadog: 2025 State of Containers and ServerlessPartners
Want to know more?
Every project is unique, and Cadence.CI will not have the same impact on each of them. If you need some guidance or information, feel free to reach us.