
Copilot in Microsoft Fabric
Generative AI assistant that enhances data analytics in Microsoft Fabric.

Accelerating scientific discovery through purpose-built AI and scientific computing solutions.

Enthought provides enterprise-grade scientific software and AI solutions tailored for research and development. They specialize in helping organizations leverage AI and machine learning to accelerate discovery and innovation. Their offerings include scientific software development, legacy software modernization, UI/UX design, predictive modeling, custom simulations, and web applications. Enthought's core strengths lie in data engineering, process engineering, data pipelining, workflow automation, and scientific data management systems. They offer strategic guidance for R&D AI transformation, digital transformation, and data system design. The platform's architecture is built to handle complex data and workflow needs, integrating machine learning, deep learning, and generative AI techniques. Enthought enables scientists and engineers to leverage advanced modeling and simulation for property prediction, formulation optimization, and materials discovery.
Enthought provides enterprise-grade scientific software and AI solutions tailored for research and development.
Explore all tools that specialize in automate research workflows. This domain focus ensures Enthought delivers optimized results for this specific requirement.
Explore all tools that specialize in ai recommendation systems. This domain focus ensures Enthought delivers optimized results for this specific requirement.
Utilizes generative adversarial networks (GANs) to create novel material structures with desired properties.
Employs multi-agent systems to simulate and optimize complex processes in R&D workflows.
Integrates diverse data sources, including text, images, and experimental data, into a unified knowledge graph.
Offers a structured approach to designing and implementing AI-driven R&D workflows.
Creates computationally efficient approximations of complex simulations.
Initial consultation to assess R&D needs and data landscape.
Data audit and preparation to ensure compatibility with AI models.
Custom model development and deployment using machine learning frameworks.
Integration with existing R&D systems and workflows.
Technical training for scientists and engineers on new AI tools and processes.
Ongoing support and optimization of AI models to maximize performance.
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"Enthought is praised for its expertise in scientific computing and AI, delivering significant value to R&D organizations."
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