InstaDeep's BioAI Team Streamlines Experiment Management with Neptune

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InstaDeep's BioAI team was faced with the challenge of managing numerous experiments for their DeepChain™ platform, a complex software for protein design. The team was dealing with scattered experiment logs, difficulty in sharing experiment results, and the burden of handling infrastructure and operations. The team needed a solution that was easy to use, could connect to TensorFlow and PyTorch logs, and was cost-effective. The challenge was to find a tool that could streamline their experiment management process, improve visibility of experiment logs, and facilitate collaboration among researchers and engineers.

InstaDeep is an EMEA leader in delivering decision-making AI products. They have developed collaborations with global leaders in the AI ecosystem, such as Google DeepMind, NVIDIA, and Intel. The company is part of Intel’s AI Builders program and is one of only 2 NVIDIA Elite Service Delivery Partners across EMEA. The InstaDeep team is made up of approximately 155 people working across its network of offices in London, Paris, Tunis, Lagos, Dubai, and Cape Town. The BioAI team at InstaDeep is where Biology meets Artificial intelligence. They are currently building DeepChain™, their platform for protein design, and are working with their customers in the bio sector to tackle the most challenging problems with the help of bioinformatics and machine learning.

The BioAI team adopted Neptune, a tool that some of the engineers were already using for their projects. Neptune was chosen because it met the team's requirements for an experiment management solution. It was accessible, provided more visibility for experiment logs, enabled straightforward collaboration between researchers and engineers, and eliminated the need for operations and infrastructure configuration. Neptune centralized all experiment runs, indexed, and organized them, making it easier for the team to track logs. It also provided a password-protected and easily shareable link to experiment results, facilitating collaboration. Moreover, Neptune eliminated the need for configuring infrastructure to log experiment results by providing a fully-managed solution.

• The adoption of Neptune by the BioAI team has significantly improved their workflow. It has saved a lot of research time and improved the team’s productivity. The team no longer has to deal with scattered experiment logs or difficulties in sharing experiment results. Neptune has also eliminated the need for the researchers to spend time configuring infrastructure and handling operations, allowing them to focus more on their research work.

• The BioAI team has been using Neptune for about 2 years

• Neptune has centralized all experiment runs, indexing, and organizing them