Bubble Lab

Open-source, Typescript-native agentic workflow builder

Winter 2026

artificial-intelligence

developer-tools

workflow-automation

About

Bubble Lab is an open-source Typescript-native workflow automation platform. Unlike tools that use proprietary JSON, you describe a workflow in natural language, and instantly get both a visual flow and fully-typed TypeScript code side-by-side. It offers built-in observability, testability, and scalability out of the box.

Founders

Selina Li

Founder

Cofounder and CEO of Bubble Lab, previously cofounder of gymii.ai | UPenn '23, Cornell Tech MEng '25 | Competitive golfer

Zach Zhong

Founder

Cornell Tech CS'25, UCSD CS'24 Prev co-founded gymii.ai I like to automate everything

AI Research Report

Problem & Solution

Problem

Developers building workflow automations often rely on legacy, JSON‑node based platforms that lack type safety, observability, and easy code export. These limitations make debugging difficult and increase the risk of fragile integrations.

Solution

Bubble Lab provides an AI‑native, TypeScript‑first workflow automation platform. Users describe a workflow in natural language; the AI assistant Pearl converts the description into a visual flow and generates production‑ready, fully typed TypeScript side‑by‑side. Key capabilities include:

Prompt‑to‑workflow generation
End‑to‑end type safety (compile‑time and runtime)
Built‑in traceability, logs, and token/cost tracking
Direct API invocation and managed integrations
Import from existing tools (e.g., n8n) and instant export as TypeScript or managed API
Open‑source self‑hosted option and hosted SaaS tiers

The platform addresses the core pain points of debugging, lack of code ownership, and inflexible deployment models, enabling developers to build, observe, and ship automations quickly and confidently.

Market & Competitors

Market Overview

Bubble Lab operates at the intersection of agentic AI workflow builders, developer tooling, and automation/orchestration platforms. The market is being shaped by rapid generative AI adoption, increasing demand for developer‑centric low‑code solutions, and growth in integration‑platform‑as‑a‑service (iPaaS) and robotic process automation (RPA).

Competitive Landscape

Traditional workflow automation: n8n, Make.com, Zapier
Agentic AI frameworks: LangChain, LlamaIndex, CrewAI, AutoGen
Enterprise orchestration suites: OpenAI Automations, Microsoft Copilot Studio, Retool AI

Differentiators

Open‑source Apache 2.0 licensing
TypeScript‑native workflows with full type safety
Automatic code export and API generation
Comprehensive observability (traceability, logs, cost tracking)
Flexible pricing: free self‑hosted and paid hosted tiers

Total Addressable Market

Quantitative TAM Assessment

Macro AI Spending

IDC forecasts worldwide AI spending to reach $632 B by 2028, with GenAI accounting for $202 B (CAGR 29%). Software is the largest category.
IDC also projects cumulative GenAI product and service spend of $371.6 B from 2024‑2027, with annual GenAI software spend of $151.1 B in 2027.

Enterprise AI Market

Mordor Intelligence estimates the enterprise AI market at $97.2 B in 2025, growing to $229.3 B by 2030 (CAGR 18.9%).

Adjacent Automation Segments

RPA: $3.79 B in 2024 → $30.85 B by 2030 (CAGR 43.9%).
iPaaS: $8.5 B in 2024 (YoY growth 23.4%).
AI Orchestration: $11.02 B in 2025 → $30.23 B by 2030 (CAGR 22.3%).

Venture Insight

Menlo Ventures reports $37 B spent on generative AI in 2025.

TAM Synthesis

By aggregating the enterprise AI software slice ($97 B) with adjacent automation markets (iPaaS ~$8.5 B, RPA ~$5‑6 B, AI orchestration ~$11 B), Bubble Lab’s serviceable TAM for 2025 is estimated in the $110‑125 B range. Growth is expected to accelerate as generative AI platform spend expands, potentially pushing the TAM toward the $200‑250 B envelope by 2030.

Founder Analysis

Founders Background

Selina Li – Cofounder & CEO

Education: University of Pennsylvania (B.A., 2023), Cornell Tech (M.Eng., 2025)
Prior venture: Co‑founder of gymii.ai, an AI‑powered nutrition‑tracking app.
Experience: Former quantitative researcher at JPMorgan.

Zach Zhong – Cofounder & CTO

Education: University of California, San Diego (B.S., Computer Science, 2024), Cornell Tech (M.S., Computer Science, 2025)
Prior venture: Co‑founder and CTO of gymii.ai.

Both founders met while studying at Cornell Tech, built gymii.ai together, and later launched Bubble Lab (YC Winter 2026, founded 2025). The company’s team size is reported as 2‑10 employees.

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