84% of enterprises see big data analytics changing their
industries' competitive landscapes by 2015.
Accenture/GE
89% believe in the risk of loss of share if no serious
action is taken.
Accenture/GE
By 2016, 70% of the most profitable companies will manage
business processes using real-time predictive analytics or extreme collaboration.
Gartner
Average accuracy
last quarter
Daily forecasted energy consumption
Predicting models
in production
Customers trusting Predictive Layer
every day
Unique combinations of machine learning algorithms and artificial intelligence are used to automatically correlate :
Predictive Layer provides accurate forecasts of your key business indicators, so that you will leapfrog competition by taking the right market action earlier.
Profiling and targeting customers at risk, and customer future intents to enable churn reduction, cross sell, upsell.
Machine learning will learn from all your big data and identify direct opportunities for new revenue or cost reductions
Connect and learn from market available exogenous data of your industry and anticipate the trends with targeted actions
Just focus your team on your business; the Predictive Layer platform has automated the mathematics and the IT systems required for predictive analytics.
Based on your business requirements, Predictive Layer platforms can be deployed in your private IT context (on premises) or in a secured cloud based infrastructure (in the cloud).
Predictive Layer services provide automated prediction
analytics.
Without requiring mathematical expertise, our clients can build their own models to forecast their
core business indicators.
The platform also gives access to the open data of the relevant industry sector so that the 'machine learning' learns from all the main market dynamics to further develop the best action plans.
Automated Prediction platform with unique machine learning algorithm to predict time series. Crystal learns from your signals and from exogenous data influencing them to predict their short evolution in time.
Modeling platform for Financial Markets. By learning from financial and economic open data sources, Genius automatically forecasts supply, demand, transformation and the market trend impact on key financial indicators.
Real-time forecast of retail business, customers, inventories by correlating historical business records with influencing open-data to optimize resources allocations, inventory and logistics for each product category.
On December 13th at IDC's conference in Paris on Big Data and Analytics, Predictive Layer, a Silver Sponsor of the event, will present an overview of how to use your company's own Big Data enriched with external data sources to improve short-term forecasts or improve the company's pricing approach.
This will include examples of how to move rapidly from a Proof of Concept (PoC) to deployment at industrial scale, which key success factors to consider and what type of results might be expected.
The presentation will be illustrated by real-life customer examples that demonstrate specific benefits and lessons learned.
Come and join us at the event on Thursday, December 13th, at the Capital 8, Paris 8ème.
Sign-up for free.
On December 11-12th at the Supply Chain Event 2018, Predictive Layer will join an expert panel to discuss how innovations such as AI & Machine Learning are revolutionizing the supply chain by using companies' own data enriched with external data sources to improve short-term forecasts and improve operational efficiency.
Please stop by our booth D29 to discuss how Predictive Layer might help improve your forecasting and purchasing process, to hear about some of our other clients’ experiences or simply to exchange ideas on predictive analytics and Machine Learning.
We hope to see you at the event on December 11-12th, at Porte de Versaille, Paris.
On October 18th at IDC's conference in Paris on Artificial Intelligence and Machine Learning, Predictive Layer will present an overview of how to use your company's own data enriched with external data sources to improve short-term forecasts or improve the company's pricing approach.
This will include examples of how to move rapidly from a Proof of Concept (PoC) to deployment at industrial scale, which key success factors to consider and what type of results might be expected.
The presentation will be illustrated by real-life customer examples that demonstrate specific benefits and lessons learned.
Come and join us at the event on Thursday, October 18th, at the Aéroclub de France, Paris 16ème.
Sign-up for free.
On October 9-11th at the annual Canalys Channels Conference EMEA in Barcelona, Spain, Predictive Layer will share how to use a company's own data enriched with external data sources to improve short-term forecasts and improve the company's pricing approach.
We will discuss how to deploy AI/ML solutions at industrial scale, key factors to consider during implementation and what results clients can expect.
This new, AI/ML-based approach to dynamic pricing is particularly relevant for many of the distributors and technology vendors who will be attending the event, but applies equally well to companies across many industries with B2B sales teams.
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