Launched this week
CloudKnife
Cut your cloud bill, not your performance
162 followers
Cut your cloud bill, not your performance
162 followers
Cloud cost tools tell you what to cut, then leave the work to you. CloudKnife handles it from A to Z. AI agents learn what every Azure resource is, how it’s really used and what it’s allowed to become. A deterministic core checks every recommendation against hard rules, so your SAP VM only gets SAP-certified options. You approve, CloudKnife executes. Your cloud stays lean and your team gets its time back for innovation.
Exciting! Any insights in realistic cost savings?
@diederik_van_damme1 Thanks, Diederik! As a concrete example, one enterprise Azure deployment saved 27% in three months, with 85% of recommendations executed. Results depend on how optimized the environment already is and its workload constraints, but that gives you a real reference point. Our focus is on savings that actually get implemented and show up on the bill.
@jonas_cloudknife Interesting, thanks for the numbers. Will try it out!
@diederik_van_damme1 Looking forward to hearing your feedback, Diederik. Thanks a lot for the support on today's launch!
Keeping approval with the team while handling the execution sounds like a useful balance. Good luck today, Jonas, Gilles and Thomas!
@yuliia_savchuk Much appreciated Yuliia!
From an after-hours project to a full-time business. Congrats to all three of you! Hope the launch brings some useful conversations.
@marianna_tymchuk Thanks for the support Marianna!!
Hello hunters 👋
Gilles here, co-founder & CEO of CloudKnife.
We’re almost halfway through launch day and the support has been amazing so far. Thank you for every upvote, comment and share. It means the world to us!
If you’re building on Azure, CloudKnife is free to try. Link it to your Azure environment and surface inefficient configuration in minutes. Questions or need help getting started? Drop a comment or reach out, we’re happy to help. We’d love to hear your feedback.
🙏 The second half of the day decides the leaderboard. If you like what we’re building, give us an upvote and help push CloudKnife to the top.
Congratulations
@madalina_barbu Thanks for the support!
The deterministic core checking every recommendation is the part I would want to understand first. Most cost tools stop at a suggestion, and the risky part is always the execution — especially when a workload has constraints that are not obvious from usage graphs alone. How does that check work in practice: does it validate the change against the workload rules before anything runs, and what happens when a savings recommendation conflicts with a rule the team set?