Novaflow

We’re Aman and Amulya, and we’re building Novaflow.

TL;DR — Bioinformatics data analysis is a time-consuming and expensive process for scientists. With Novaflow, life scientists can upload experimental data, ask questions in plain English, and get instant, publication-ready plots, giving them results in minutes instead of months.

Intro Video

Our Story

Aman was a computational biologist and saw firsthand how his colleagues struggled to analyze their experimental results quickly due to a growing backlog of data in the lab. Despite spending over $100,000 a year on data analysis, it still wasn’t enough. He realized that using LLMs, this process can be automated away and save researchers time and money. He teamed up with his friend Amulya who was a software engineer at Zoom to bring this product to life.

The problem

Life science labs generate huge datasets, but analysis is slow, expensive, and talent‑constrained:

• Expensive. Small labs routinely spend $100k+/year per analyst; large labs spend millions.
• Talent bottleneck. Many groups run ~5:1 experimentalists to analysts, so researchers wait weeks to months for results.
• Dual expertise required. Useful analysis needs both strong coding skills and deep biological context—most researchers only have one.
• Resource‑intensive + fragmented tooling. Labs often lack scalable compute, standardization, or long‑term data management. Many are stuck with custom scripts and tools that feel 15+ years behind.

Our Solution

We want to put analysis back in the hands of researchers:

• 🧠 LLM‑powered pipelines that plan, generate, and run bioinformatics workflows behind the scenes
• 📊 Instant, publication‑ready plots from raw CSVs, FASTQs, BAMs., and more
• 🔍 Natural‑language querying (“Which genes are most differentially expressed?”)
• 🧪 Exportable Jupyter notebooks & reproducible Python code for auditability and downstream tweaking
• ♻️ Versioned runs & provenance so you can rerun, compare, and share analyses confidently

How it works

1. Upload your data + describe the experiment (e.g., “scRNA‑seq of treated vs. control organoids”).
2. Novaflow infers the right workflow (e.g., QC, normalization, clustering/UMAP for scRNA‑seq; DE for bulk RNA‑seq; peak calling + motif analysis for ATAC‑seq).
3. We spin up the compute, run the pipeline, and return plots, summaries, and a notebook you can keep, rerun, or extend.

Who this is for

• Life scientists blocked by slow or missing bioinformatics support
• Academic labs doing genomics, transcriptomics, proteomics, etc.
• Biotech teams that want to accelerate R&D with leaner headcount
• Clinical/diagnostic groups using high‑throughput assays

Our Ask

• Book a demo if you’re interested in seeing how Novaflow can support your lab!
• Know a research lab, hospital, or biotech company that might benefit from Novaflow? Send us an email - we’d love an introduction! contact@novaflowapp.com