Scigantic: Life Sciences Notebooks & Model Fine-Tuning on AWS

Scigantic gives computational biologists and bioinformatics teams a managed scientific-computing platform that runs bring-your-own-compute on AWS. Researchers launch AI-powered notebooks preloaded with domain tooling for genomics, proteomics, and drug discovery, then explore and traverse their Amazon S3 object storage directly from the notebook.

Built-in tools browse buckets, inspect schemas and file layouts, and compare your private S3 data side by side with public AWS Open Data archives and other storage sources, so finding and understanding the right dataset takes minutes instead of days.Beyond exploration, Scigantic fine-tunes biological foundation models (protein, DNA, and small-molecule backbones) on Amazon SageMaker, writing evaluation reports and trained weights back to your own S3.

An in-notebook AI agent, powered by your own Amazon Bedrock models, reads your data in context to write code, run analyses, and explain results. Because notebooks, training jobs, model weights, and LLM inference all execute in your AWS account, your proprietary genomic and research data never leaves your environment. Scigantic operates the control plane as a managed service while every workload runs in your AWS account through a single cross-account role you connect with a guided CloudFormation deployment.

You pay per seat through AWS Marketplace and pay for compute, storage, and Bedrock inference at your own negotiated AWS rates, drawing down committed AWS spend with no vendor compute markup, purchased through your existing AWS agreement.