--- title: Decagon slug: decagon-1d18b url: /detay/decagon-1d18b type: article language: English entity: primary: Decagon type: article disambiguation: AI-powered customer support solutions by Decagon. Automates customer service, improves efficiency & scalability. categories: - name: Software And Artificial Intelligence slug: yazilim-ve-yapay-zeka url: /kategori/yazilim-ve-yapay-zeka tags: - customer experience lifecycle - Agent Operating Procedures - AI-powered customer support - Decagon - Automation author: Ömer Said Aydın created_at: 2025-05-11T16:25:00.706493+03:00 updated_at: 2025-05-12T11:47:44.457577+03:00 image: https://cdn.t3pedia.org/media/uploads/2025/05/11/hdUTmH9PADW5YnTMns4OveQazugTAJhI.webp --- # Decagon ## KURE Information Cards ### KURE Information Card: Decagon ![kI0QjgP3MaKLRvUu8TaCGNM1g7T5CDTb.webp](https://cdn.t3pedia.org/media/uploads/2025/05/11/NXyTIhJ28Z0WYNJImDEtMhBCh7Sjuq37.webp) | Field | Value | |-------|-------| | Website(s) | https://decagon.ai/ | | Founded(Text) | 2023 | | Founder(s) | Jesse Zhang Ashwin Viswanath | | Location | San Francisco California USA | ## Article Content **Decagon** is a San Francisco-based technology company that develops [AI](/en/detay/artificial-intelligence-tools-ai-tools-a3e1f/llms.txt)-powered customer support solutions. The company builds software designed to help large-scale enterprises automate their customer service processes and manage personalized [interactions](/en/detay/interactions-dfcae/llms.txt) more efficiently. [Decagon](/en/detay/decagon-9c0d3/llms.txt)’s technology enables businesses to deliver faster, more flexible, and scalable customer experiences. ### **Founding and Founders** Decagon was founded by Jesse Zhang and Ashwin Viswanath. Jesse Zhang serves as the company’s CEO. The founders aimed to address operational inefficiencies in customer service by designing a system that merges the coding expertise of technical teams with the operational insights of customer experience teams. The company’s core mission is to automate repetitive tasks without entirely removing the human workforce, allowing support teams to take on more strategic roles. ### **Funding and Financial Developments** As of 2025, Decagon has raised a total of $100 million in funding. The company’s $65 million Series B round was led by Bain Capital Ventures, with participation from Elad Gil, A\*, Accel, BOND Capital, and ACME Capital. The funds are being used for product development, engineering team expansion, industry diversification, and support for additional communication channels such as voice. ### **Technological Infrastructure** The cornerstone of Decagon’s technology is its Agent Operating Procedures (AOPs) system. AOPs is a proprietary framework that defines how [AI agents](/en/detay/artificial-intelligence-agent-6f889/llms.txt) operate within customer support workflows. It combines the flexibility of natural language with the precision of code, allowing both technical and non-technical teams to effectively configure AI agents. AOPs replaces rigid and hierarchical decision trees found in traditional customer service automation systems. Instead of predefining every scenario, AOPs enables multi-step, conditional, and context-aware workflows. This flexibility allows the system to handle unexpected cases and adapt in real time. The system operates similarly to human-used Standard Operating Procedures (SOPs). AI agents follow rules defined in AOPs files to complete tasks step-by-step. For instance, when handling a return request, the agent might first verify the user’s identity, then query order history, and finally escalate the case to a department if needed — all following the sequence defined in the AOP file. Definitions in AOPs can be written in natural language and enhanced with code where more precise control is needed. This design empowers technical teams to maintain control while allowing operations teams to actively contribute. AOPs also comes with version control, test environments, analytics tools, and alert systems, enabling continuous improvement and observability of agent behavior. This infrastructure ensures that customer service quality can be sustainably optimized. Through this approach, Decagon enables businesses to build AI agents that are customizable to their internal protocols and brand voice — moving beyond generic chatbot responses. ### **Use Cases and Clients** Decagon’s solutions are used across sectors such as fintech, SaaS, e-commerce, and media. Clients include Duolingo, [Notion](/en/detay/notion-93b3a/llms.txt), Rippling, Eventbrite, Bilt, Hertz, Webflow, Raise, Flashfood, Curology, and Substack. At these companies, AI agents handle the majority of customer inquiries, managing tasks such as identity verification, refunds, account updates, and ticket resolution. ### **Workforce Transformation and Efficiency** Decagon views AI not as a replacement for human labor but as a complementary tool. By offloading repetitive tasks to AI agents, human support staff can be reassigned to strategic and analytical roles. This transition aims to reduce operational costs while increasing customer satisfaction. ### **Transparency, Auditability, and Security** Decagon prioritizes transparency and auditability in customer service automation. The AOP infrastructure makes each decision traceable, and critical steps, such as authentication, include dedicated safeguards. Features like audit logs, access controls, and quality assurance monitoring are integral to the platform’s design. ### **Recognition and Awards** In 2025, Decagon was included in Forbes’ "AI 50" list, which highlights the most innovative private AI companies in North America. This recognition reflects Decagon’s technological contributions to customer service automation. ### **Future Outlook** Decagon envisions a future where AI agents take on a central role in customer support. Human representatives will shift toward roles focused on configuring, training, and supervising AI agents. The company plans to expand its capabilities in voice-based communication, multilingual support, and industry-specific agent configurations. Its long-term goal is to redefine the entire customer experience lifecycle through AI infrastructure and scale this transformation across a wide range of sectors. ## Academic Sources and References 1. "About Decagon Products." Decagon. Accessed May 6, 2025. https://decagon.ai/product/overview."ACME Venture Capital." ACME VC. Accessed May 6, 2025. https://www.acme.vc/."Agent Assist." Decagon. Accessed May 6, 2025. https://decagon.ai/product/agent-assist."AOP (Automated Operations Platform)." Decagon. Accessed May 6, 2025. https://decagon.ai/product/aop."Case Studies." Decagon. Accessed May 6, 2025. https://decagon.ai/case-studies."Chat." Decagon. Accessed May 6, 2025. https://decagon.ai/product/chat."Decagon Company Profile." LinkedIn. Accessed May 6, 2025. https://www.linkedin.com/company/decagon-ai/."Decagon Named to 2025 Forbes AI 50 List of Top Artificial Intelligence Companies." Business Wire. Accessed May 6, 2025. https://www.businesswire.com/news/home/20250411812238/en/Decagon-Named-to-2025-Forbes-AI-50-List-of-Top-Artificial-Intelligence-Companies."Decagon Raises $100M to Date to Build AI Agents That Change How Work Is Done." Business Wire. Accessed May 6, 2025. https://www.businesswire.com/news/home/20241015912157/en/Decagon-Raises-%24100M-To-date-to-Build-AI-Agents-That-Change-How-Work-Is-Done."Email." Decagon. Accessed May 6, 2025. https://decagon.ai/product/email."Resources." Decagon. Accessed May 6, 2025. https://decagon.ai/resources."Voice." Decagon. Accessed May 6, 2025. https://decagon.ai/product/voice."Watchtower." Decagon. Accessed May 6, 2025. https://decagon.ai/product/watchtower.