We enable your AI transformation, by delivering ad-hoc productive AI solutions valuable for your business.
Are you new to Artificial Intelligence?
Endless possibilities seem to be available... But what are the right ones for your company? Statwolf can help you answer that and guide you in starting adopting AI solutions suitable for your business
Quick and effective Machine Learning Environment assessment. Our approach:
The ‘AIdea’: by working with domain and business experts, we validate your AI-related ideas and identify new case studies and potentials that Ai can unlock.
Problem Statement: we formulate goals and requirements value together with customer’s domain experts and end-users.
Data assessment: we identify relevant data sources with the help of the customer’s domain experts and IT team.
Proof-of-concept: we design and evaluate tailor-made ML algorithms and provide reliable assessment in terms of business metrics.
Demo and Solution 1.0: thanks to the Statwolf technology, we can release a working prototype quickly, so you can try the solution before moving to production.
Do you need data experts consultancy?
Statwolf with his data science team and academic advisors can verify or improve your models increasing accuracy, robustness or interpretability. Moreover, thanks to Statwolf Machine Learning Environment-oriented data platform, AI models can smoothly translate into productive solutions integrated in your systems
Fast and reliable MLE productive release: Statwolf Machine Learning Environment modules enable fast roll-out thanks to the pipelinebased development approach.
StatwolfMLE modules allow you to follow a pipeline-based development approach, so code is reproducible and easy to maintain; MLOps features help you to manage the industrialization of Machine/Deep learning algorithms lifecycle.
How do you manage your solution in productive environment?
Thanks to StawolfMLE your data scientists will finally have an environment where both development and deployment of AI can be performed! See more details on StatwolfMLE.
MLOps features make it easy to monitor and maintain productive MLE solutions. MLOps (a compound of “machine learning environment” and “operations”) is a practice for collaboration and communication between data scientists and operations professionals to helpmanage production MLE lifecycle. Similar to the DevOps orDataOps approaches, MLOps looks to increase automation andimprove the quality of production MLE, while also focusing onbusiness and regulatory requirements.
