Science is held back by fragmented workflows.
Experimental notes live in one place, code and data in another, and figures somewhere else. Over time, the context behind decisions gets lost across documents, chats, and team members. Researchers spend too much time stitching together tools and too little time focused on discovery.
Co-PI exists to change that.
We are building an AI-native scientific workspace that helps researchers move seamlessly from experiment design to analysis, interpretation, and communication—all in one place. Our goal is to make it much easier for scientists and teams to capture what they did, understand what their data means, and turn that work into the next experiment, report, manuscript, or breakthrough.
“The cake is a lie, but the pi is not.” 🥧
An AI-native integrated workspace for modern scientific research
Co-PI brings experimental context, computational workflows, and scientific reasoning into a single environment — so researchers can record, analyze, and collaborate without switching tools.
Analyze my dose-response data
You
Detected sigmoidal curve with EC50 = 2.4 μM
Co-PI
Which trends stand out?
You
Generating figure and summary...
dose_response_curve.png
0.1 μM
100 μM
Co-PI
Electronic Lab Notebook
Document protocols, experiments, and observations with rich formatting. Organize research with a modern, searchable notebook that keeps your science structured and accessible.
Computational Workspace
Run Python code, analyze data, and create visualizations inline — think Jupyter notebooks, but AI-automated and deeply connected to your experimental context.
AI Research Collaborator
An AI system that understands the context of your projects over time and across multidisciplinary teams — helping interpret results, connect findings, and accelerate decision-making.
A co-primary investigator for real scientific work
At the center of Co-PI is an AI built specifically for science — not just a chatbot, but a system that operates within the context of your experiments, notebooks, analyses, and project history.
Analyze & Visualize Data
Analyze and plot experimental data automatically — from raw numbers to publication-ready figures.
Identify Trends & Anomalies
Surface trends, outliers, and potential quality issues across experiments and datasets.
Generate Hypotheses
Propose hypotheses and suggest logical next steps based on your results and project context.
Troubleshoot Experiments
Diagnose experimental and computational problems with PhD-level scientific reasoning.
Search & Synthesize Literature
Find relevant papers and synthesize findings in the context of your own research.
Draft Scientific Documents
Help write reports, presentations, manuscripts, and grant materials grounded in your actual data.
Connect Findings Over Time
Link results across experiments, projects, and teams — so knowledge compounds rather than disappears.
The aim is to give every scientist a system that helps them think more clearly, work more efficiently, and preserve the reasoning behind their research.
The software around science hasn't kept pace
Scientific research has become increasingly complex, but the software environment around it has not kept pace. Most scientists still work across a patchwork of notebooks, spreadsheets, scripts, slide decks, shared drives, and writing tools.
Important context gets lost. Analyses are hard to reproduce. Knowledge becomes trapped in individual team members instead of compounding across the organization.
We believe the next generation of scientific software should do more than store information. It should actively help researchers work with it.
Co-PI is built on a simple idea: the scientific workspace should be able to understand your work and help advance it.
That means preserving context, making analysis more accessible, improving reproducibility, reducing repetitive work, and helping scientists turn raw data into actionable insight more quickly.
The future of research is AI-native.
In that future, scientists will not have to choose between rigorous documentation, reproducible computation, and fast, intuitive collaboration. These capabilities will live together in one system — and scientific software will participate in the research process in real time.
Our long-term vision is to build the operating system for modern scientific discovery: a workspace where experiments, data, code, literature, and reasoning all connect, and where AI helps researchers and teams move from idea to insight with greater speed, confidence, and depth.
We want Co-PI to make advanced scientific analysis and reasoning accessible to more researchers, while raising the quality, continuity, rigor, reproducibility, and velocity of research across academia and industry.
Built for every scientist who asks hard questions
Co-PI is for any researcher who generates data, needs better ways to track and connect experimental work with analysis and interpretation — across experiments, projects, and teams.
Experimental Scientists
Biologists, chemists, and physicists who generate data and need better ways to document, analyze, and connect their experimental work.
Computational Biologists
Bioinformaticians and computational scientists who need their analytical workflows connected to experimental context and team knowledge.
Translational & Drug Discovery
Teams bridging bench science to clinical application, where traceability, reproducibility, and cross-functional context are critical.
Biotech & Startup R&D
Fast-moving R&D teams that need a shared system of record, automated analysis, and AI-accelerated decision-making.
Academic Labs
Research groups running multiple projects over time, where institutional knowledge needs to persist beyond individual team members.
Cross-functional Teams
Interdisciplinary groups that need a shared workspace where experimental data, code, and scientific reasoning all live together.
Whether you are documenting a single assay, analyzing a dataset, troubleshooting a project, or drafting a manuscript — Co-PI is designed to keep the full scientific workflow connected.
A few core principles guide everything we build
Context matters.
Scientific insight depends on understanding the full history of a project, not just a single file or prompt. Co-PI maintains context across all your experiments, notebooks, and analyses.
Analysis should live with the experiment.
Code, plots, notes, and conclusions should exist together — not across disconnected systems. Co-PI keeps your computational work inseparable from your experimental record.
AI should be useful, not generic.
Researchers need an assistant that can help with real scientific workflows — not just general conversation. Co-PI is built with deep domain knowledge to assist with the work scientists actually do.
Scientific work should compound.
Knowledge from prior experiments, analyses, and literature should become easier to reuse and build on over time. Co-PI is designed to make your prior work more valuable, not less.
Better tools can accelerate discovery.
By reducing friction and making scientific reasoning more accessible, we can help researchers spend more time on high-value thinking and experimentation — and less on administrative overhead.
Built by scientists, for scientists
Co-PI is being built by scientists who understand firsthand how difficult it is to manage modern research across fragmented tools.
Our team brings together experience in experimental biology, computational analysis, and AI-enabled scientific workflows. We are building Co-PI from the perspective of people who have lived the realities of research: designing experiments, generating data, analyzing results, preparing reports, and trying to keep complex projects organized across time and teams.
We believe the best scientific software comes from deep empathy for the research process and a commitment to building tools that are rigorous, practical, and genuinely helpful in day-to-day scientific work.
We're a small, interdisciplinary team of scientists and builders working to create better tools for scientific discovery.
A new kind of scientific software
Co-PI is building a new kind of scientific software: one that does not just help researchers document their work, but helps them think, analyze, and discover.
We believe the future of research will be shaped by tools that combine scientific rigor with AI-native workflows. Our goal is to build infrastructure that helps scientists do their best work — and helps scientific knowledge become more connected, reusable, and actionable over time.
Ready to transform your research?
Join scientists who are moving from fragmented tools to a unified, AI-native workspace.
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