Datatron Blog

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sales funnel

Automating and Streamlining the Sales Lead Funnel

Did you know 40% of your sales team time is spent on bad leads?

What typically happens is they often divert or deviate from their ideal productivity zone and this happens for many reasons. Because today there is no data-driven way to course-correct their path in real-time. Some companies do this by employing a dedicated team of data scientist/business analysts.

Datatron has automated this process and is available for a fraction of the cost.

For example, we have a case study from a customer based here in San Francisco.

Prior to Datatron their sales reps were all over the place, they didn’t have answers to what leads to focus on they didn’t have answers to what leads will likely go dead.

They gave equal priority to every lead that comes into the funnel. So, the amount of time spent on a dead lead was more than the time they spent on a quality lead.

Early results show 10% increase in revenue.

Here at Datatron, we offer a platform to govern and manage all of your Machine Learning, Artificial Intelligence, and Data Science Models in Production. Additionally, we help you automate, optimize, and accelerate your ML models to ensure they are running smoothly and efficiently in production — To learn more about our services be sure to Request a Demo.

whitepaper

5 Reasons Your AI/ML Models are Stuck in the Lab

AI/ML Executive need more ROI from AI/ML? Data Scientist want to get more models into production? ML DevOps Engineer/IT want an easier way to manage multiple models. Learn how enterprises with mature AI/ML programs overcome obstacles to operationalize more models with greater ease and less manpower.

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whitepaper

Life Cycle of Machine Learning Models

Production-grade machine-learning models require strong deployment framework in order to reduce the time it takes to iterate a model faster, deploy new features quickly, and train on incoming data faster.

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Unique Challenges Of Machine Learning Models In Production

Production-grade machine-learning models require strong deployment framework in order to reduce the time it takes to iterate a model faster, deploy new features quickly, and train on incoming data faster.

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Model Deployment

Production-grade machine-learning models require strong deployment framework in order to reduce the time it takes to iterate a model faster, deploy new features quickly, and train on incoming data faster.

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whitepaper

Model Monitoring

Production-grade machine-learning models require strong deployment framework in order to reduce the time it takes to iterate a model faster, deploy new features quickly, and train on incoming data faster.

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whitepaper

Model Governance & Management

Production-grade machine-learning models require strong deployment framework in order to reduce the time it takes to iterate a model faster, deploy new features quickly, and train on incoming data faster.

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Our Latest Event

Datatron Website Re-branding Launch

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Ta-da! You are now experiencing the new Datatron web experience, including our new logo. Enjoy!

We Just Launched!