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MIP is the intelligence layer for biological research. It connects a domain-specialized AI reasoning engine to real-time access to 40+ authoritative databases, a live scientific literature index, third-party analytical tools, and a containerized compute environment capable of running autonomous multi-step pipelines. Whether you’re interpreting variants, analyzing RNA-seq data, exploring protein structures, identifying drug targets, or navigating a new research area — MIP gives you the reasoning depth that has historically required an entire lab.

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What you can do with MIP

Research intelligence

Ask questions in natural language across the full depth of biology. Genes, variants, pathways, protein function, disease mechanisms, drug interactions, literature — MIP reasons across all of it simultaneously, pulling from authoritative sources in real time.

Multi-omics analysis

Bring your genomics, transcriptomics, proteomics, metabolomics, or single-cell data. MIP interprets results, surfaces patterns, cross-references databases, and generates hypotheses — without requiring you to switch tools or write pipeline code from scratch.

Variant interpretation

Upload VCF files and work through variant classification with AI-assisted ACMG/AMP evidence review. Evidence is pulled live from ClinVar, gnomAD, PubMed, functional data sources, and population databases. Findings are exportable as structured reports.

Drug target and pathway exploration

Query across ChEMBL, Open Targets, KEGG, UniProt, AlphaFold, and PDB. Identify targets, map pathways, explore protein structure, and surface relevant compounds — in a single conversation.

Literature synthesis

Search and reason across PubMed and preprint sources. Ask MIP to summarize a field, identify contradictions in the literature, extract key findings from a set of papers, or surface the most relevant recent work for your hypothesis.

Code execution

Write and run Python or R directly in the platform. Pre-installed scientific libraries include pandas, NumPy, Biopython, scanpy, pydeseq2, matplotlib, and 15+ others. Results stream back inline.

Autonomous pipelines

Kick off long-running computational tasks — MD simulations, RNA-seq pipelines, multi-step analyses — and let MIP run them in the background. Jobs are tracked, resumable, and results are available when complete.

Reports and exports

Generate structured outputs from any analysis: variant interpretation reports, findings summaries, pathway maps, literature briefs, or custom formats ready for review, sharing, or export.

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Explore the docs

Quickstart

Up and running in under 5 minutes.

Platform overview

How MIP’s architecture works: databases, agents, reasoning layer, and compute.

Key concepts

Research sessions, agents, tool calls, jobs, and artifacts explained.

Guides

Step-by-step documentation for every major workflow.

Code execution

Running Python and R, available libraries, and compute limits.

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Get started

Access MIP at mip.purna.ai from any modern browser. Sign in and you’re ready. New here? Start with the Quickstart guide.

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We’d like to hear from you

MIP is shipping fast. New capabilities, new databases, and better models go out every week — and what we build next is shaped directly by what researchers tell us they need. If something is missing, broken, or not working the way it should — or if you have a database to add, a workflow to support, or a question about fit for your research — reach out. We read everything.

General

contact@purna.ai

Sid (Founder)

sid@purna.ai

Gitanjali (Founder)

gitanjali@purna.ai