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ML model training

The ENPICOM Platform addresses the core challenges of training ML models, including those related to data preparation, by streamlining data management and accessibility, resulting in greater efficiency and reduced costs. Fragmented and siloed historical data often complicates model training. Data can be accessed directly through our scalable data foundation, or efficiently ingested into a centralized data warehouse, leveraging the power of AWS cloud technologies. Either way, our scalable infrastructure enables quick, organized querying of labeled datasets, automatically generating standardized, ML-ready formats, and eliminating the need for extensive data transformation.

Effortlessly manage and access all data

Instant access to ML-ready data

Querying for labeled datasets is now super simple, enabling data scientists to easily access the relevant data in seconds. This removes the need to search through scattered data sources or manually transform data into structured, ML-ready formats, significantly streamlining the preparation process.

No data migrations required

Our solution eliminates the need for costly and time-consuming data transfers between data storage solutions. By leveraging AWS cloud technologies, data can be directly accessed and used for model training without the need to migrate it, making the process more efficient and reducing operational overhead.

All scientific data seamlesly managed

Historical data from scientists is efficiently managed within a centralized database, eliminating data silos. As data ingestion is a key step in their daily research workflows, it ensures that data entry becomes a natural part of their routine, establishing consistent and accurate data storage, enhancing data availability and integrity.

Real-time model improvement

New experimental data can be easily retrieved and used as it is being generated, for benchmarking model performance or further tuning AI models. This seamless access to any data ensures that models can be continuously refined and improved based on latest data generated in the lab.

Leaders in scientific research choose ENPICOM

genovac
LifeArc logo.
Illumina logo.
KGI Keck Graduate Institute logo.
carterra
memo
Kling Biotherapeutics logo.
Weizmann Institute of Science logo.
University of Michigan logo.
AdAlta logo.
Inno4vac
Erasmus-MC-logo
mabylon
Utrecht-University
aalborg2
ucl
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Power your ML journey with seamless collaboration between data and lab scientists

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