StableBrowse

Competitive Intelligence & Product Roadmap

Semantic browser runtime for AI agents.

Company Overview

StableBrowse is a browser-agent runtime that maps websites into semantic graphs for reliable authenticated automation. It serves agent builders working across insurance, healthcare, mortgage, and shopping workflows; named customers are not public.

Latest Intel

Zeitgeist tracks private signals to determine where the company is heading strategically.

New Intel: StableBrowse is packaging semantic site graphs and authenticated browser sessions as custom APIs. That turns portal-heavy workflows in insurance, healthcare, mortgage, and commerce into an agent infrastructure market.

What They're Building

The company's public product roadmap & what they're committed to building.

Semantic Knowledge Graphs

StableBrowse maps website states into reusable graphs so agents can navigate, extract, and act without reasoning over raw screens or full DOMs.

Authenticated Sessions

The product handles cookies, SSO, per-user secrets, and persistent sessions for workflows inside logged-in portals.

Custom Schema APIs

Enterprise workflows can be exposed as REST and WebSocket APIs, turning brittle browser actions into structured endpoints.

Managed Browser Clusters

StableBrowse packages headless browser capacity, rotating residential proxies, session persistence, and anti-detection infrastructure.

Vertical Workflow Demos

The company shows insurance, healthcare, mortgage, and shopping flows where agents need to operate across portal-heavy systems.

Founder and Key Execs

Sarthak Awasthi

Co-Founder (YC-listed founder; public background details are limited)

Jay Mehta

Co-Founder (Purdue University)

Deepit Shah

Co-Founder (UIUC CS; Amazon AI Infrastructure)

Somansh Shah

Co-Founder (Purdue University; public post cites sub-300ms LLM inference work)

Founder Force Multiplier

Deepit Shah's Amazon AI Infrastructure background and Somansh Shah's low-latency LLM work fit the core problem: agents need reliable, low-cost browser execution. Public detail on Sarthak Awasthi and Jay Mehta is limited.

Funding History

2025 | LinkedIn lists company founded
2026 | YC Spring 2026 participant; no additional public financing found

Competitors

Browserbase:

Provides cloud browser infrastructure and Stagehand primitives, while StableBrowse centers on reusable semantic site graphs for agent workflows.

Browser Use:

Builds open-source browser-agent tooling, while StableBrowse is packaging an enterprise runtime for authenticated portal automation.

Skyvern:

Automates browser workflows with LLMs and computer vision, while StableBrowse claims a graph-first execution model.

Integuru:

Turns platforms into APIs without RPA or browsers, while StableBrowse accepts browser execution and tries to make it stable.

Parse:

Builds APIs from underlying network requests, while StableBrowse targets workflows where authenticated browser state remains necessary.

StableBrowse

's Moat:

Candidate moat is workflow switching costs: maintained site graphs and schema APIs can become sticky if customers wire agents into them.

How They're Leveraging AI

Semantic Site Graphs for Agent Browsing

StableBrowse turns live websites into semantic graphs that AI agents can use to navigate, extract, and transact inside authenticated portals. The user is the developer or enterprise team building agents that need web apps to behave like stable APIs.

Schema-Constrained Web Extraction

StableBrowse exposes messy portal workflows as custom REST and WebSocket schema APIs, so agents can request structured outcomes instead of scraping raw pages. This turns websites into typed tools for agent builders.

Reliability Scoring for Web Actions

StableBrowse appears to score the reliability of page nodes and actions over repeated executions, then uses those scores to route agents toward safer interaction paths. The use case is production QA for browser agents operating across unstable web interfaces.

AI Use Overview:

StableBrowse uses LLMs for intent parsing, then routes execution through semantic site graphs and reliability-scored nodes rather than screenshot-first browser control.

Agent Infrastructure

Tasklet

Runs cloud AI agents for recurring knowledge-work workflows.

Firebase-grade infra founders are attacking workflow automation as LLMs start to operate software, with early ARR and USV as both customer and investor.

Decagon

AI agents that autonomously handle enterprise customer support across chat, email, voice, and SMS.

Agentic AI for customer support is one of the few GenAI categories with clean ROI math, and Decagon has locked in the blue-chip logo sweep that compounds into category default status.

Manus

Autonomous AI agent platform that executes multi-step business workflows end-to-end

A model-agnostic orchestration layer with real browser and shell execution captured viral enterprise demand faster than any US agent startup, a thesis validated by Meta's $2B acquisition.

Bubble Lab

Gives ops teams an AI super-employee in Slack that automates cross-platform workflows.

Zapier and Make require users to think in workflows. Bubble Lab's Pearl lives in Slack and runs multi-step operations (Jira, Stripe, Notion) from plain English, which means ops teams adopt it without learning a new tool.

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