Best Machine Learning Software for Microsoft 365

BIS, a company that has 35 years of experience in developing and delivering innovative technology, built Grooper from the ground up. Grooper is an intelligent data processing and digital data integration tool that allows organizations to extract meaningful information out of paper/electronic documents, and other unstructured data. The platform combines advanced image processing, capture technology and machine learning with optical character recognition to enrich data and embed human comprehension. Grooper is a foundation for many industry-first solutions, including in healthcare, financial services and education.

CCH Tagetik Corporate Performance Management software is trusted by companies to save time, reduce costs, and reduce risk. Connect data, processes, and people with one trusted source to get a quicker close and more forward-looking planning. CCH Tagetik Finance Transformation Platform powered by the Analytic Information Hub is the unified platform that connects finance & operations and streamlines consolidation & close planning, reporting & analysis, disclosures, and compliance.

TIMi allows companies to use their corporate data to generate new ideas and make crucial business decisions more quickly and easily than ever before. The heart of TIMi’s Integrated Platform. TIMi's ultimate real time AUTO-ML engine. 3D VR segmentation, visualization. Unlimited self service business Intelligence. TIMi is a faster solution than any other to perform the 2 most critical analytical tasks: data cleaning, feature engineering, creation KPIs, and predictive modeling. TIMi is an ethical solution. There is no lock-in, just excellence. We guarantee you work in complete serenity, without unexpected costs. TIMi's unique software infrastructure allows for maximum flexibility during the exploration phase, and high reliability during the production phase. TIMi allows your analysts to test even the most crazy ideas.

SAS technologies combine to provide powerful tools for visual information. You can access, manipulate, analyze, and present information in visual formats. SAS Visual Machine Learning allows you to expand your analytics by using machine learning and deep learning capabilities. This makes it easier to visualize and report better. Visualize and discover relationships in your data. You can create and share interactive dashboards and reports, and use self service analytics to quickly assess possible outcomes to make data-driven, smarter decisions. This solution runs in SAS®, Viya®. It allows you to explore data and create or adjust predictive analytical models. Analysts, statisticians, data scientists, and analysts can work together to refine and refine models for each group or segment, allowing them to make informed decisions. A comprehensive visual interface allows you to solve complex analytical problems. It handles all aspects of the analytics lifecycle.

We offer the highest quality SLA (>95%) even for the most complicated workflows. Our team can assist with everything from the implementation of a solid quality rubric to raising edge case. We are an ethical AI company that has provided economic opportunities to over 52,000 people in underserved and marginalized areas. ML Assisted annotation allowed for efficiency improvements of up to 3-4x per class annotation. We are able to quickly adapt to ramp-ups and focus shifts. Secure work environments are ensured by ISO-certified delivery centers, biometric authentication, 2FA user authentication, and ISO-certified delivery centers. You can quickly re-prioritize tasks, give quality feedback, and monitor production models. All data types are supported. You can do more with less. We combine machine learning with humans to filter data and select images that are relevant to your use cases. Based on your initial guidelines, you will receive sample results. We will work with you to identify and recommend best annotation practices.

Data scientists and developers can collaborate on ML projects by empowering them. Before publishing to end-users, build, load, optimize, and test models and their integrations. Data science workload can be reduced and decision-making improved by sharing and storing ML models throughout the organization. Publish updates to automatically push any changes to production models. ML-powered insights can be instantly provided within any web-based business app to increase efficiency and boost productivity. Our browser extension allows analysts and business users to seamlessly integrate models into any web application using drag-and-drop.

OctoAI is a world-class computing infrastructure that allows you to run and tune models that will impress your users. Model endpoints that are fast and efficient, with the freedom to run any type of model. OctoAI models can be used or you can bring your own. Create ergonomic model endpoints within minutes with just a few lines code. Customize your model for any use case that benefits your users. You can scale from zero users to millions without worrying about hardware, speed or cost overruns. Use our curated list to find the best open-source foundations models. We've optimized them for faster and cheaper performance using our expertise in machine learning compilation and acceleration techniques. OctoAI selects the best hardware target and applies the latest optimization techniques to keep your running models optimized.

MLflow is an open-source platform that manages the ML lifecycle. It includes experimentation, reproducibility and deployment. There is also a central model registry. MLflow currently has four components. Record and query experiments: data, code, config, results. Data science code can be packaged in a format that can be reproduced on any platform. Machine learning models can be deployed in a variety of environments. A central repository can store, annotate and discover models, as well as manage them. The MLflow Tracking component provides an API and UI to log parameters, code versions and metrics. It can also be used to visualize the results later. MLflow Tracking allows you to log and query experiments using Python REST, R API, Java API APIs, and REST. An MLflow Project is a way to package data science code in a reusable, reproducible manner. It is based primarily upon conventions. The Projects component also includes an API and command line tools to run projects.