Companies that use RunLayer

Analyzed and validated by Henley Wing Chiu ยท Updated
All โ€บ machine learning and LLM development โ€บ RunLayer

RunLayer We detected 44 companies using RunLayer and 1 companies that churned. The most common industry is Software Development (40%) and the most common company size is 1,001-5,000 employees (36%). We find new customers by discovering URLs with known URL patterns through web crawling or certificate transparency logs.

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Company Employees Industry Country Region Usage Start Date
Wenrix source 51โ€“200 Technology, Information and Internet
Israel
Europe 2026-08-08
Canva source 1,001โ€“5,000 Software Development
Australia
Oceania 2026-08-07
Bain Capital source 1,001โ€“5,000 Financial Services
United States
North America 2026-07-27
Goldman Sachs source 10,001+ Financial Services
United States
North America
Casey's source 10,001+ Food and Beverage Services
United States
North America
Netflix source 10,001+ Entertainment Providers
United States
North America
Databricks source 5,001โ€“10,000 Software Development
United States
North America
Nubank source 5,001โ€“10,000 Financial Services
Brazil
South America
Notion source 501โ€“1,000 Software Development
United States
North America
Anthropic source 501โ€“1,000 Research Services N/A North America
Gusto source 1,001โ€“5,000 Software Development
United States
North America
Navan source 1,001โ€“5,000 Artificial Intelligence
United States
North America
ServiceTitan source 1,001โ€“5,000 Software Development
United States
North America
Affirm source 1,001โ€“5,000 Financial Services
United States
North America
Klaviyo source 1,001โ€“5,000 Marketing Services
United States
North America
Poshmark source 501โ€“1,000 Retail Apparel and Fashion
United States
North America
Plaid source 501โ€“1,000 Software Development
United States
North America
PagerDuty source 1,001โ€“5,000 Software Development
United States
North America
Stoneridge source 1,001โ€“5,000 Motor Vehicle Parts Manufacturing
United States
North America
UserTesting source 501โ€“1,000 Software Development
United States
North America
Showing 1-20

Market Insights

๐Ÿข Top Industries

Software Development 17 (40%)
Financial Services 9 (21%)
Technology, Information and Internet 2 (5%)
Advertising Services 1 (2%)
Artificial Intelligence 1 (2%)

๐Ÿ“ Company Size Distribution

1,001-5,000 employees 15 (36%)
501-1,000 employees 12 (29%)
201-500 employees 6 (14%)
10,001+ employees 3 (7%)
51-200 employees 3 (7%)

๐Ÿ‘ฅ What types of companies use RunLayer?

Source: Analysis of Linkedin bios of 44 companies that use RunLayer

Company Characteristics
i
Trait
Likelihood
Company Size: 1,001-5,000
66.6x
Industry: Software Development
49.8x
Country: United States
10.4x
I noticed RunLayer's customers span a remarkably wide range, but they share a common thread: they're building or operating complex digital platforms at significant scale. These aren't just tech companies. They include financial services infrastructure (Goldman Sachs, Nubank, IntraFi), developer platforms (Databricks, Vercel, Benchling), marketplaces (Poshmark, Opendoor), and specialized B2B software (ServiceTitan, Klaviyo, PagerDuty). What unites them is that they're all running mission-critical systems where performance, reliability, and user experience directly impact their business model.

These are predominantly growth-stage to mature companies. The majority are either publicly traded (Goldman Sachs, Databricks raised $1B Series J, PagerDuty, AppLovin) or well-funded late-stage companies with hundreds to thousands of employees. The smallest company listed has 275 employees. Most fall in the 500 to 5,000 employee range. They're past the scrappy startup phase and operating at a scale where infrastructure decisions carry serious weight.

๐Ÿ”ง What other technologies do RunLayer customers also use?

Source: Analysis of tech stacks from 44 companies that use RunLayer

Commonly Paired Technologies
i
Technology
Likelihood
17593.8x
16741.6x
15803.2x
13227.9x
I noticed that RunLayer users are building AI-first, enterprise-ready companies with a strong focus on internal operations and team collaboration. The appearance of tools like Decagon AI, Sana AI, and Anecdotes.ai tells me these companies are deeply invested in leveraging AI across their operations, not just in their product. They're using AI to power customer support, knowledge management, and internal processes while also building AI products themselves.

The pairing of Slack Enterprise Grid with these AI tools is particularly revealing. Companies aren't just using basic Slack, they're paying for the enterprise version, which suggests they have significant team sizes and need advanced security and compliance features. When I see this combined with DX, a tool for measuring developer productivity, it tells me these are engineering-heavy organizations that care deeply about team efficiency and performance metrics. ZipHQ's presence further reinforces this, as it's designed for managing procurement and vendor relationships at scale.

My analysis shows these companies are likely in growth stage, past the scrappy startup phase but not yet massive enterprises. They're product-led organizations with substantial engineering teams that need sophisticated coordination tools. The combination of enterprise Slack, developer productivity tracking, and AI-powered knowledge management suggests they're scaling quickly and need systems to maintain velocity without chaos. They're investing in operational excellence early, which indicates venture-backed companies with resources to spend on best-in-class tooling.

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