For Life Sciences Teams
Multi-agent meeting intelligence that knows your tools. The system tracks 71 tools across 13 categories, from AWS cloud services to RDKit and GROMACS, and recommends them in real time during your team meetings. Three specialist agents (infrastructure, data science, cheminformatics) run in parallel for domain-specific analysis. Capture whiteboard sketches and get structured architectural analysis.
Real-time transcription with tool recommendations. The AI agent listens to your discussion and suggests tools from the catalog based on what your team is working on.
71 tools across 13 categories: AWS services, cheminformatics, proteomics, genomics, data engineering, molecular dynamics, visualization, and lab informatics.
Photograph whiteboard diagrams during meetings. Vision AI identifies architecture patterns, data flows, and tool references, then maps them to catalog recommendations.
Three domain-specific AI agents analyze your meeting in parallel, each bringing a different lens to the discussion. Their insights appear in the meeting sidebar and are included in post-meeting summaries.
Open a meeting with the informatics context. The system loads the full tool catalog and activates specialist agents.
Talk about infrastructure, pipelines, tools, and analysis. The AI transcribes and analyzes every 20 seconds.
Tool suggestions appear in real time as the discussion references relevant domains. Snap whiteboard photos for instant analysis.
Post-meeting summary includes action items, key decisions, and a prioritized list of recommended tools tied to discussion points.
71 tools across 13 categories. The meeting agent draws from this catalog for real-time recommendations.
21 services across compute, storage, ML, data, and orchestration. These form the foundation for cloud-native scientific computing.
Managed batch processing at scale. Runs containerized jobs on EC2 or Fargate with automatic provisioning.
Open-source cluster management for HPC on AWS. Provisions Slurm or AWS Batch-backed clusters with shared filesystems.
Serverless compute for event-driven functions. Runs code without provisioning servers.
Serverless containers on ECS or EKS. No cluster management needed.
Virtual servers in the cloud. Wide range of instance types including GPU, HPC, and memory-optimized.
Visual workflow orchestration service. Coordinates Lambda, Batch, ECS, and other AWS services.
Object storage with virtually unlimited scale. The standard for scientific data lakes.
High-performance parallel filesystem. Integrates with S3 for transparent data access from HPC clusters.
Managed NFS filesystem. Elastic capacity, shared across instances and containers.
End-to-end ML platform. Training, tuning, hosting, feature store, and experiment tracking.
Managed foundation model service. Access Claude, Titan, Llama, and other LLMs via API with guardrails and RAG.
Purpose-built for genomics. Managed storage (sequence, variant, annotation stores) plus workflow execution (WDL, Nextflow, CWL).
Serverless SQL query engine over S3. Supports Parquet, CSV, JSON, and Iceberg tables.
Managed ETL and data catalog. Crawlers auto-discover schema; Spark and Python shell jobs for transformation.
Fine-grained access control for data lakes. Column-level and row-level security over S3 data.
Cloud data warehouse. Serverless option available. Columnar storage optimized for analytics.
Managed JupyterLab environment on AWS. Integrated with SageMaker for training, experiments, and model registry.
Managed container registry. Stores Docker images for ECS, EKS, Batch, and Lambda.
Container orchestration service. Runs Docker containers on EC2 or Fargate.
Managed Kubernetes. Run K8s workloads on AWS with managed control plane.
Open-source cheminformatics toolkit. Molecular manipulation, fingerprints, descriptors, substructure search, reaction handling.
Integrated computational chemistry platform. Molecular modeling, FEP+, Glide docking, Maestro GUI, LiveDesign collaboration.
AWS: Available on AWS Marketplace. Runs on EC2 GPU instances or ParallelCluster for FEP+ campaigns.
Shape-based molecular design and modeling. ROCS, OMEGA, SZYBKI, and Orion cloud platform.
AWS: Orion platform runs natively on AWS.
Visual workflow platform for data science. Strong cheminformatics nodes (RDKit, CDK). Server edition for production.
Ultra-fast molecular fingerprint similarity search using HDF5 databases. Billions of compounds in seconds.
Free desktop tool for chemical data visualization and analysis. SAR tables, property plots, clustering.
AI protein structure prediction. AlphaFold 3 extends to complexes: protein-ligand, protein-nucleic acid, and multimers.
AWS: Can run on EC2 GPU instances. AWS HealthOmics has AlphaFold workflow templates.
Open-source reimplementation of AlphaFold2 in PyTorch. Enables custom training and fine-tuning.
AWS: Train on SageMaker or EC2 P5/P4 instances.
Quantitative proteomics from mass spectrometry data. Label-free and TMT/SILAC quantification, Andromeda search engine.
Commercial proteomics software from Thermo Fisher. Integrated with Orbitrap instruments. Consensus and processing workflows.
Data-independent acquisition (DIA) proteomics analysis. Neural network-based spectral library-free search.
Industry-standard variant calling pipeline from the Broad Institute. HaplotypeCaller, Mutect2, and best-practice workflows.
AWS: Run via AWS HealthOmics workflows or AWS Batch with Cromwell.
Short-read aligner for DNA sequencing. BWA-MEM2 is the SIMD-optimized successor.
Spliced Transcripts Alignment to a Reference. The standard RNA-seq aligner.
Differential gene expression analysis from RNA-seq count data. R/Bioconductor package.
Processing pipeline for 10x Chromium single-cell and spatial data. Alignment, UMI counting, clustering.
AWS: Runs on EC2 or AWS Batch. AWS HealthOmics has Cell Ranger workflow templates.
R toolkit for single-cell RNA-seq analysis. Clustering, differential expression, integration, spatial analysis.
Python toolkit for single-cell analysis. AnnData format, preprocessing, clustering, trajectory inference.
Community-curated Nextflow pipelines for bioinformatics. Standardized, tested, and production-ready.
Fast transcript quantification for RNA-seq. Quasi-mapping approach, no alignment step needed.
Utilities for manipulating alignments in SAM/BAM/CRAM format. Sort, index, merge, statistics.
Cloud platform for biomedical research built on Google Cloud. AnVIL (Analysis Visualization and Informatics Lab-space) hosts NHGRI datasets and workflows.
Open-source variant annotation and visualization platform. Modular annotator system with 150+ annotation sources and a web-based results viewer.
Commercial desktop platform for molecular biology and sequence analysis. Sanger assembly, cloning design, primer design, phylogenetics, and NGS analysis in a GUI.
Next-generation short-read aligner, successor to BWA-MEM. 2-3x faster than original BWA with identical output, leveraging SIMD vectorization.
High-performance molecular dynamics simulation. Widely used for biomolecular systems.
AWS: Runs on ParallelCluster with EFA networking. GPU instances (P4/P5) for acceleration.
Assisted Model Building with Energy Refinement. Suite of biomolecular simulation programs and force fields.
AWS: GPU-accelerated on EC2 P4/P5 instances. ParallelCluster for multi-node.
Python-friendly MD engine. Extensible via custom forces and integrators. GPU-accelerated.
Workflow manager for computational pipelines. Groovy DSL, native Docker/Singularity support, multi-cloud execution.
AWS: Native AWS Batch executor. Runs on AWS HealthOmics. Seqera Platform (Tower) for enterprise.
Python-based workflow manager. Make-like syntax with Python integration. Supports cloud execution.
AWS: Runs on EC2 or AWS Batch via Snakemake executor plugins.
Programmatic workflow orchestration. DAGs in Python. AWS MWAA is the managed version.
AWS: Amazon MWAA (Managed Workflows for Apache Airflow) is fully managed.
Molecular visualization system. Publication-quality structure rendering. Python-scriptable.
Next-gen molecular visualization from UCSF. Handles large complexes, cryo-EM maps, VR support.
Python viewer for multi-dimensional images. Plugin ecosystem for bioimage analysis.
Interactive visualization library and dashboard framework. Python, R, and JavaScript.
Python framework for rapid data apps. Script-based, auto-reactive UI.
Open-source software for measuring and analyzing cell images. Automated image analysis pipelines.
Desktop and web-based genome browser for interactive exploration of genomic data. Supports BAM, VCF, BED, bigWig, and dozens of other formats.
Managed JupyterLab environment on AWS. Integrated with SageMaker for training, experiments, and model registry.
Multi-user Jupyter notebook server. Deployable on Kubernetes (Zero to JupyterHub) or bare metal.
AWS: Deploy on EKS with Zero to JupyterHub Helm chart. Can use EC2 or Fargate.
Cloud-native R&D platform. ELN, LIMS, registry, molecular biology tools, and API.
Scientific informatics platform. Combines ELN (Studies Notebook), registration, assay data, and analytics.
Code hosting and collaboration. CI/CD via Actions, code review, project management.
Team wiki and documentation platform from Atlassian. Spaces, pages, templates.
Spreadsheets remain the most common analytical surface in life sciences. Custom Excel formulas bridge the gap between structured data APIs and analysts who build models, trackers, and diligence sheets in Excel every day.
No context-switching
Trial data, pipeline comparisons, and AI answers flow into the cell where the analyst is already working.
Live formulas
Recalculate to refresh. Build competitive landscape tables and enrollment trackers that update themselves.
Custom add-ins
Use the pre-built Clari for Excel add-in, or generate your own with custom formulas from Code Studio.
On the blog
Tool catalog curated as of April 2026. AWS services reflect the latest generally available features. Open-source tool descriptions are based on current documentation. Pricing models and availability may change.