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AI powered Software RAM Prediction

  • AI powered Software RAM Prediction

Requs.ai

Software Downtime Prediction

Predict Error Budget, Software Failure Rate and Site Reliability

Accurate, easy, early

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Traditionally, software teams wait until the later stages of development to measure key metrics like test hours, downtime incidents, site reliability and software failure rate. Prior to then they depend on guestimates for establishing an error budget. By this point, addressing the root causes of downtime or mission loss is often too late or too expensive. This reactive approach can lead to costly delays and poor software performance.
The cost of guessing error budgets
  • Guessing error budgets doesn't work

    It's proven to be off by 5 orders of magnitude

  • Software is a bigger component than you think

    Take a look at everything around you. Hardware has been replaced by software.

  • System uptime and site reliability goals are being missed because of the software failure rate

    You can wait until acceptance to find out that the error budget and therefore site reliability objective can't be met because of the software failure rate or you can be proactive and use Requs AI Predict.

Requs AI Solution
  • Data driven predictions

    You can't defend a SME guess but you can defend a software failure rate prediction and error budget based on the world's largest benchmarking study

  • Sanity checking

    RAM engineers aren't comfortable with software failure rate predictions. Requs.AI illustrates the high low ranges for your software so you gain confidence.

  • No need for failure data

    Predict the software failure rate, downtime, site reliability early using data driven methods before you commit to an error budget you can't meet

How it works

From Q&A to error budgets

Answer some questions

About the product, development practices and environment. As you know more, the accuracy improves.. just like it does with hardware.

AI Analysis

Requs.ai predicts defect density and risk level from AI model

RAM metrics are established

Requs. ai predicts escaped defects, defect discovery times, software failure rates, downtime, site reliability, availability using industry standard methods

Software failure rate forecasted for Agile Development

In agile world, the software is never done. Requs.ai forecasts each program increment so you can spot RAM problems such as increasing software failure rate or downtime.

The only ML software failure rate prediction tool that doesn't require software failure data

  • Confidence

    The more questions you answer (accurately) the better the confidence in the prediction

  • AI-Powered

    Built from the world's largest software reliability bmechmarking study. More than 600 factors measured against actual escaped defects on mission and safety critical systems. Predict defect density with AI from actual historical data from mission and safety critical systems.

  • Established

    Rome Laboratory TR-92-52, Keene Cole Model were developed when Ada and Waterfall were standard practices. Tools/models that don't consider Agile, MBSE, modern tools aren't accurate.

  • Easy

    If you don't know an input, it's not considered in the prediction.

software failure rate prediction

Flexible purchasing options

  • Integrated product suite

    Requs AI Predicts covers the software failure rate, site reliability and error budget while Requs AI Software FMEA generates an effective software FMEA.

  • Integrated workflow and API

    .Requs AI Software FMEA has an API and open architecture. So, you can integrate the predictions with other RAM tools.

  • Licensing options

    Dedicated or floating licenses. Yearly subscriptions or perpetual plans. Cloud or Desktop solution.

  • Tiered editions

    Feature tiers allow you to purchase only the features you need.

  • Standards

    IEEE 1633

  • Air gapped support

    Requs.ai runs on air gapped systems