Companies that use Decagon AI

Analyzed and validated by Henley Wing Chiu
All conversational AI Decagon AI

Decagon AI We detected 477 companies using Decagon AI and 106 customers with upcoming renewal in the next 3 months. The most common industry is Software Development (22%) and the most common company size is 10,001+ employees (27%). We find new customers by discovering URLs with known URL patterns through web crawling or modifications to subprocessor lists.

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Company Employees Industry Country Region Usage Start Date
Manulife 10,001+ Insurance
CA Canada
North America 2026-04-29
Thirdlove 51–200 Retail Apparel and Fashion
US United States
North America 2026-04-26
Turkcell 5,001–10,000 Telecommunications
TR Turkey
Europe 2026-04-25
Domino's 10,001+ Restaurants
US United States
North America 2026-04-24
Cardless 11–50 Technology, Information and Internet
US United States
North America 2026-04-24
Zwift 501–1,000 Technology, Information and Internet
US United States
North America 2026-04-23
Vetcove 51–200 Veterinary Services
US United States
North America 2026-04-23
OpenGov Inc. 501–1,000 Software Development
US United States
North America 2026-04-21
WorkWhile 51–200 Technology, Information and Internet
US United States
North America 2026-04-19
Fiverr 501–1,000 Software Development
US United States
North America 2026-04-15
Kinetic 10,001+ Telecommunications
US United States
North America 2026-04-10
Truework 51–200 Financial Services
US United States
North America 2026-04-04
KeyBank 10,001+ Banking
US United States
North America 2026-04-03
FIGS 201–500 Retail Apparel and Fashion
US United States
North America 2026-04-02
Contabo 201–500 Software Development
DE Germany
Europe 2026-03-28
Careem 1,001–5,000 Software Development
AE UAE
Europe 2026-03-28
Telna 51–200 Telecommunications
CA Canada
North America 2026-03-27
Ennismore 10,001+ Hospitality
GB United Kingdom
Europe 2026-03-26
UPC Chello 5,001–10,000 Business Consulting and Services
NL Netherlands
Europe 2026-03-24
Showing 1-20

Market Insights

🏢 Top Industries

Software Development 102 (22%)
Financial Services 69 (15%)
Technology, Information and Internet 30 (7%)
IT Services and IT Consulting 19 (4%)
Retail 19 (4%)

📏 Company Size Distribution

10,001+ employees 122 (27%)
1,001-5,000 employees 98 (21%)
501-1,000 employees 79 (17%)
201-500 employees 65 (14%)
51-200 employees 55 (12%)

👥 What types of companies use Decagon AI?

Source: Analysis of Linkedin bios of 477 companies that use Decagon AI

Company Characteristics
i
Trait
Likelihood
Funding Stage: Series F
1175.7x
Funding Stage: Series E
685.3x
Funding Stage: Secondary market
480.6x
Company Size: 10,001+
83.8x
Company Size: 5,001-10,000
33.7x
Industry: Banking
25.6x
I analyzed these companies and found that Decagon AI's customers span an incredibly diverse range of sectors, but they share a common thread: they're all dealing with high volumes of customer interactions. These aren't just B2B software companies. I'm seeing financial services providers like MoneyGram and Zolve, retailers like Nike and Poshmark, insurance companies like Travelers and Humana, telecommunications giants like Xfinity and Vodacom, and even fitness studios like Barry's. What unites them is that they all have large customer bases requiring support at scale.

Looking at company maturity, I'm seeing a strong bias toward established, scaled businesses. Most have employee counts in the thousands or tens of thousands. Many are publicly traded or have gone through multiple funding rounds. Even the smaller companies like Givebutter or sploot have substantial funding and are clearly in growth mode. These aren't garage startups testing product-market fit. They're companies with real revenue, real customers, and real support volume challenges.

🔧 What other technologies do Decagon AI customers also use?

Source: Analysis of tech stacks from 477 companies that use Decagon AI

Commonly Paired Technologies
i
Technology
Likelihood
6579.7x
3638.5x
3458.6x
3279.8x
2780.1x
1030.0x
I noticed that Decagon AI attracts companies obsessed with operational excellence and employee experience, particularly in the growth stage where efficiency becomes critical. The presence of tools like Impact, Glean, and DX tells me these are organizations investing heavily in internal knowledge management and partnership operations. This isn't your typical sales-heavy startup stack. These companies are building sophisticated operational infrastructure.

The pairing of Decagon AI with Glean is particularly revealing. Glean helps employees search across all internal tools and documents, while Decagon handles AI-powered customer support. Together, they suggest companies dealing with complex knowledge bases who want both their employees and customers to access information quickly. The high correlation with Tines, a workflow automation platform, reinforces this. These companies are automating repetitive processes across their operations, not just in customer service. Adding Qualtrics to the mix shows they're measuring experience quality obsessively, whether that's customer satisfaction or employee feedback.

The full picture reveals companies in a specific growth phase. They're past the scrappy startup stage but racing to scale efficiently. They're likely product-led or hybrid motion companies because they're investing in self-service infrastructure and knowledge management rather than just throwing more salespeople at growth. The presence of ZipHQ, an HR tool, alongside customer experience platforms suggests they're growing headcount rapidly and need systems to manage that complexity. These aren't massive enterprises yet, but they're building enterprise-grade operations.

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