Spotlight

What if AI didn't just assist with experiments, but designed and ran them autonomously?

Quick Pitch: Quadrillion is building Qualia, an agentic researcher for computational experiments. Qualia generates, runs, and analyzes experiments directly inside the digital research workspaces data scientists and quants already use, acting as both a copilot and an autonomous research assistant.

The Problem

• Manual overhead: Researchers spend hours writing boilerplate code for cleaning data, running experiments, and plotting results instead of doing research.

• Tool mismatch: Coding copilots are optimized for software engineers, not researchers working in digital research workspaces.

• Knowledge lock-in: Insights live inside complex notebooks that are hard to interpret, reuse, or share across teams.

• Low AI adoption: At elite quant firms, most engineers use AI coding tools, but fewer than 10% of researchers do.

Snapshot

• Industry: Research tooling, AI for data science

• Headquarters: New York, NY

• Year Founded: 2025

• Traction: Product in demo phase with strong user validation across quant firms and research teams

Founder Profile

• Ethan Chi, Founder: Former Hudson River Trading (top-tier quantitative trading firm) and Google Research; 2,000+ academic citations

Funding

• Current Round: $7M (Seed)

• Lead Investors: Audacious Ventures, Conviction

• Other Backers: Bloomberg Beta, ex/ante

• Notable Angels & Advisors: Leaders from Streamlit, Hex, dbt Labs, Pandas, Microsoft, and frontier research labs

Revenue Engine

• Primary buyer: Quant firms, research focused enterprises, and advanced data science teams

• Model: Enterprise SaaS with seat based pricing and usage based expansion

• Expansion levers: Higher experiment volume, multi agent usage, team wide adoption

• Long term upside: Standardization across research teams once embedded in core workflows

What Users Love

• 10x faster code generation for data cleaning, experimentation, and visualization

• Autonomous experiment design and parallel execution

• Jupyter native experience designed for research workflows

• Collaboration features that make technical work accessible to non technical stakeholders

Playing Field

• Cursor/Claude Code: Built for software engineers in VSCode, not researchers in Jupyter

• Copilot: General coding assistant without research specific workflows

• Traditional Notebooks: Manual, slow, and heavy on boilerplate

Why It Matters

Research productivity has lagged behind software engineering in AI adoption. While VSCode based AI tools created a decacorn, Jupyter remains the dominant environment for billions in research spending across finance, pharma, and tech, without equivalent AI infrastructure.

What Sets Them Apart

• Agentic experimentation: Designs and runs dozens of experiments in parallel, not one prompt at a time.

• Notebook native: Works inside existing digital research workspaces without forcing new tools

• Collaborative by default: Makes complex technical work legible to both technical and non technical teams.

• Research grade output: Produces experiment logic, analysis, and visualization, not just code snippets

Analysis

Bulls Case 📈 

• Clear wedge into a large, underserved user base

• Strong founder-market fit with deep research credibility

• High perceived value among enterprise users

• Natural expansion path across quant, ML, and scientific research

• Advisor network signals strong early validation

Bears Case 📉 

• Reliance on Jupyter ecosystem adoption

• Requires trust in autonomous experimentation

• Defensibility depends on workflow lock in, not just model quality

• Product still in demo phase with no disclosed revenue or user metrics

• Potential competition from general AI platforms expanding into research workflows

Verdict

Quadrillion is aiming to unlock the same productivity shift for research that AI copilots delivered for software engineering. The core insight is distribution, not model performance. By embedding directly into daily research workflows, Qualia has a credible path to becoming default infrastructure. Demand signals are strong. The open question is whether the product can earn sufficient trust to automate high stakes research at scale.

The Startup Pulse

Another happening week in startup funding. Strong activity across AI infrastructure, cybersecurity, biotech, and brain-computer interfaces.

• Skild AI — Raised approximately $1.4B in Series C funding led by SoftBank Vision Fund to scale its general purpose robotics foundation model and expand real world deployment.

• Merge Labs — Secured $252M backed by OpenAI and others to advance brain computer interface technology focused on high bandwidth human and AI interaction.

• Deepgram — Raised $130M in Series C funding to expand its real time speech recognition and audio AI platform for developers and enterprise customers.

Read more

Written by Ashher

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