We detected 125 customers using ConfigCat, 2 companies that churned or ended their trial, and 10 customers with estimated renewals in the next 3 months. The most common industry is Software Development (30%) and the most common company size is 51-200 employees (37%). Our methodology involves monitoring new entries and modifications to company DNS records.
Note: Our data specifically only tracks ConfigCat Smart plan users.
About ConfigCat
ConfigCat offers unlimited feature flags and environments for €249 per month, removing capacity restrictions that developers face on lower-tier plans. The Smart plan includes 1 billion config JSON downloads per month, providing scalable infrastructure for growing development teams managing complex feature flag deployments.
🔧 What other technologies do ConfigCat customers also use?
Source: Analysis of tech stacks from 125 companies that use ConfigCat
Commonly Paired Technologies
i
Shows how much more likely ConfigCat customers are to use each tool compared to the general population. For example, 287x means customers are 287 times more likely to use that tool.
I noticed that ConfigCat users are predominantly B2B SaaS companies at growth stage with sophisticated product development practices. The presence of tools like Churnzero (customer success platform), Elastic Enterprise (scalable infrastructure), and VMWare Tanzu CloudHealth (cloud cost management) tells me these are companies managing complex, multi-tenant applications where feature releases need to be carefully controlled and monitored.
The pairing of ConfigCat with Churnzero is particularly revealing. These companies are deeply invested in customer retention and likely use feature flags to roll out capabilities to specific customer segments, test improvements with at-risk accounts, or gradually introduce features based on customer lifecycle stage. The strong correlation with Miro, Figma Organization Plan, and Lucidchart suggests product and engineering teams that prioritize collaborative design and planning. They're mapping out features, user flows, and system architectures before development, indicating a mature product development process where feature flagging fits naturally into a thoughtful release strategy.
The full stack reveals these are product-led organizations with 50-500 employees in their growth phase. They're past the scrappy startup stage but not yet enterprise-scale. The emphasis on collaboration tools and customer success platforms suggests they've achieved product-market fit and are now focused on efficient scaling. They need ConfigCat because they're shipping features frequently to different customer segments while maintaining stability. The cloud infrastructure management tools indicate they're cost-conscious about their technical operations, which aligns with using feature flags to reduce deployment risk and avoid costly rollbacks.
👥 What types of companies is most likely to use ConfigCat?
Source: Analysis of Linkedin bios of 125 companies that use ConfigCat
Company Characteristics
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Shows how much more likely ConfigCat customers are to have each trait compared to all companies. For example, 2.0x means customers are twice as likely to have that characteristic.
Trait
Likelihood
Company Size: 51-200
3.5x
Country: US
1.7x
I noticed ConfigCat's customers span an impressive range, but they share a common thread: they're building digital products that require sophisticated technical infrastructure. These aren't companies selling widgets. They're operating SaaS platforms, fintech applications, e-commerce systems, and cloud-based services where uptime, feature control, and rapid deployment matter deeply. Many are in regulated industries like financial services, healthcare, and government software where compliance and risk management are non-negotiable.
The funding and scale signals reveal a sweet spot: primarily growth-stage companies with 50-500 employees. I see Series A through Series C companies alongside bootstrapped businesses that have reached meaningful scale. There are some larger enterprises (1,000+ employees) but notably fewer true startups or Fortune 500s. Many have private equity backing or have been acquired by larger platforms, suggesting they've proven product-market fit and are scaling operations rather than searching for it.
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