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Putting the Data in Science Applications as an International Corporation

SaaS that lets you actually do the work you need to — and machine learning that does the work you shouldn't have to.

SaaS, MLaaS, and ML SaaS for R&D corporations, Federal/SLED/Industrial/Enterprise contractors, and scientific research alike.

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How it's sourced

Built in house, partnered, and combined

1
In house. Software we build ourselves — with machine learning built into the product where it pays off.
2
Through partnerships. Established software from our partners, provided and supported under DSAIC.
3
Derivatives. Our machine learning and partner software, combined into offerings neither delivers alone.

The work you need to do

Software that gets out of your way and lets your team do its real job — proven, conventional SaaS for the work a model can't help with, provided and supported by DSAIC.

The work you shouldn't have to

Machine learning, built into the product, handles the repetitive, high-volume calls — forecasting, scoring, flagging anomalies — so your team gets the result without grinding through it by hand.

Machine learning where it improves the result, proven software everywhere else — every offering built or sourced, provided, and supported by DSAIC.