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Dataslab AI Platform
An extension of Enterprise DataHub that provides tools for developing, deploying, and scaling AI and ML solutions in an enterprise environment.
Dataslab AI Platform brings together services for Data Science, MLOps, and AIOps, ensuring development and implementation of modern AI use cases in an enterprise environment. The platform offers secure environment for LLMs, chatbots, intelligent search, document analysis and classification, as well as creation of digital assistants.
The solution can operate on top of Dataslab Enterprise DataHub, providing models with access to centralised data, supporting scalability, and allowing deployment both in the cloud and on-premise, ensuring full control over data and model behaviour.
AI-powered search across corporate documents.
Generation of reports, summaries, and analytical materials.
Support for teams and daily operations.
Tools for automating customer interactions.
Data analysis and decision-making support.
AI-powered search across corporate documents.
Generation of reports, summaries, and analytical materials.
Support for teams and daily operations.
Tools for automating customer interactions.
Data analysis and decision-making support.
Built on top of Dataslab Enterprise DataHub, it provides models with access to high-quality, centralised data for analytics and AI use cases.
Supports growing workloads and allows launching more models and services without impacting performance.
Works both in the cloud and on-premise, depending on security, infrastructure, and policy requirements.
Combines tools for Data Science, MLOps, and AIOps: modelling, training, testing, and production deployment.
Enables work with LLMs, chatbots, intelligent search, document analysis, and AI agents.
Allows the use of modern AI/ML tools within a fully controlled enterprise environment.
Built on top of Dataslab Enterprise DataHub, it provides models with access to high-quality, centralised data for analytics and AI use cases.
Supports growing workloads and allows launching more models and services without impacting performance.
Works both in the cloud and on-premise, depending on security, infrastructure, and policy requirements.
Combines tools for Data Science, MLOps, and AIOps: modelling, training, testing, and production deployment.
Enables work with LLMs, chatbots, intelligent search, document analysis, and AI agents.
Allows the use of modern AI/ML tools within a fully controlled enterprise environment.
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