LexMount
Lexmount builds browsers and cloud infrastructure for AI agents so they can access, understand, and interact with real web pages. Its platform provides cloud browser sessions, structured web extraction, automation protocols, remote observation and related tooling for agent workflows.
At a Glance
- AI developers and agent builders
- Software companies
- Automation teams
- Enterprise developers
- +1 more
AI Tools by LexMount
(1)
Moli
Open Source Headless Browser for AI Agents
Discussions
No discussions yet
Be the first to start a discussion about LexMount
Latest News
ACE Protocol: Redesigning Browser Interaction for AI Agents
Moli: Redesigning the Browser for AI
Moli repository latest commit added opaque self-signed certificate primitives
PitchBook lists a completed Lexmount seed round
Products & Services
On-demand isolated cloud browser sessions controlled through browser SDKs/CDP, with Playwright automation, persistent contexts on eligible plans, extensions, proxies, downloads, remote observation and replay for Chromium sessions.
A bounded HTTP extraction API that fetches public pages and returns structured content such as titles, text, links and reusable DOM snapshots.
Lexmount's open-source, Rust-built headless browser engine for AI agents; it emphasizes structure-first browsing, on-demand rendering, low resource use and native CDP, WebDriver Classic and WebDriver BiDi support.
A browser-native protocol implemented inside Chromium that exposes page semantics, readiness, native actions and observed effects to AI agents through CDP.
Market Position
Lexmount positions its managed Cloud Browser/Web Fetch platform as enterprise-grade infrastructure for scalable agent browsing, while positioning Moli as an open-source, structure-first alternative to conventional Chromium-style headless deployments. In Lexmount's published benchmark, Moli is compared with Chrome Headless, Lightpanda and Obscura and reports substantially lower resident memory than Chrome; the company also compares ACE Protocol with Browser Use and agent-browser for agent workflow efficiency.
Founding Story
Lexmount says that operating browser tasks for AI agents in the cloud exposed a mismatch between traditional, human-oriented browsers and agent workloads: continuous rendering and unnecessary resource loading created avoidable overhead. It therefore set out to rethink the browser and provide cloud infrastructure that preserves web compatibility while making loading, rendering and execution better suited to agents.
Business Model
Revenue Model
Digital software-as-a-service access sold as one-month, non-auto-renewing Cloud Browser and Web Fetch plan purchases, plus one-time Web Fetch request packs and official proxy-traffic packs; Preqin also describes licensing of the AI cloud-browser technology and related integration/support services.
Pricing Tiers
10 browser hours/month, 1,000 Web Fetch requests/month, 3 concurrent browsers, 100 MB official proxy traffic.
100 browser hours/month, 1,000 Web Fetch requests/month, 25 concurrent browsers, 100 CAPTCHA uses/period and 1 GB official proxy traffic.
500 browser hours/month, 10,000 Web Fetch requests/month, 100 concurrent browsers, 500 CAPTCHA uses/period and 1 GB official proxy traffic.
1,500 browser hours/month, 10,000 Web Fetch requests/month, 250 concurrent browsers, 1,500 CAPTCHA uses/period and 1 GB official proxy traffic.
Target Markets
- AI developers and agent builders
- Software companies
- Automation teams
- Enterprise developers
- Organizations running cloud browser clusters, web extraction and browser-based workflows
- AI-agent web browsing and browser-use automation
- Structured web content extraction and RAG pipelines
- Large-scale web crawling and scraping
- RL post-training and agent workload infrastructure
- Form-heavy enterprise applications and administrative workflows
- Website QA, diagnostics and replayable evidence