DISTILL™
AI-Powered Single-Cell Omics Platform for Multi-Omics Integration and Insights
Context
From Data to Discovery — Simplify Single-Cell Analysis with DISTILL™
We help you transform single-cell and multi-omics data into actionable insights. DISTILL™ combines AI reasoning, analytical precision, and scientific context to help you uncover mechanisms, validate hypotheses, and accelerate discovery.
Why DISTILL™
DisTILLing Complex Biology in the Single-Cell and Agentic AI Era
Single-cell data offers unmatched depth into cellular behavior, but its complexity can limit discovery. DISTILL™ helps you navigate this complexity with an AI-powered framework that integrates, analyzes, and interprets multi-omics data, providing a holistic understanding of disease mechanisms, treatment response, and biological variability.
Whether you’re a researcher exploring cellular heterogeneity or a clinician seeking translational insights, DISTILL™ adapts to your scientific questions.
Features
Core Analytical Capabilities
We provide a comprehensive suite of analysis modules — from quality control to pathway enrichment — to help you extract meaningful patterns.
Enhanced with Agentic AI
Our integrated LLM assistant helps you navigate complex biological questions through conversational exploration, literature context, and curated data insights — guiding you from raw data to discovery.
Customizable Workflows
You can configure analysis pathways, integrate your own references, and collaborate with our experts to tailor every pipeline to your study needs.
Spatial Omics Integration
We assist you in performing spatial omics analyses across platforms such as Xenium, Visium, CosMx, and others — integrating spatial context with transcriptomic data for a more complete understanding of cellular organization.
Tumor and Immune Profiling
We enable advanced analyses focused on the Tumor Microenvironment (TME), immune landscape profiling, biomarker discovery, pathway enrichment, and response-to-therapy prediction — helping you uncover drivers of disease progression and treatment response.
Virtual Cell Modeling
We help you train and interpret virtual cell models that simulate cellular behavior, predict perturbation outcomes, and reveal regulatory mechanisms — using diverse datasets such as single-cell RNA-seq, spatial transcriptomics, proteomics, or perturb-seq.
Case studies
Agentic AI
A multi-agentic AI platform designed for autonomous discovery
- Generate hypotheses from massive single-cell datasets
- Reason across multi-omics layers to connect molecular mechanisms with clinical and market impact
- Surface insights conversationally, enabling researchers to query their data in natural language
- Accelerate translation from lab bench to patient bedside by turning large datasets into testable scientific hypotheses
Partner with Us
At Aganitha, we believe in collaboration-led discovery. Our team works closely with you at every step — from data preprocessing to interpretation — ensuring that your findings are robust, reproducible, and meaningful.