Build or buy? Navigating AI support agents
April 29, 2025
Written by Breuer Bass
Enterprise organizations increasingly rely on artificial intelligence (AI) to enhance customer support through voice, chat, and email channels. With 70% of customer experience leaders planning to incorporate generative AI within two years, the strategic decision to build custom AI agents internally or purchase an enterprise-ready solution has become crucial. This decision profoundly impacts speed to market, cost, customization, and scalability.
The strategic dilemma: build vs. buy
When deciding whether to build or buy AI customer support agents, enterprises must weigh strategic objectives against resource availability and risk appetite.
Time to value: Building AI internally requires extensive planning, hiring, and development, often taking months before deployment. Conversely, off-the-shelf solutions can be operational within weeks, enabling rapid value realization.
Cost implications: Initial costs for in-house development are significant, encompassing infrastructure, specialized engineers, and ongoing maintenance. Purchased solutions typically operate under predictable, subscription-based models, shifting expenses to operational rather than capital expenditures.
Customization vs. control: In-house development allows total control, essential for organizations with unique processes or sensitive data requirements. However, platforms like Decagon offer substantial customization through innovative Agent Operating Procedures (AOPs), blending ease of use with tailored flexibility and extensibility, allowing businesses to maintain control without extensive internal development.
Risk and expertise: Internally developed AI entails considerable risk, including model inaccuracies and operational failures. Leveraging established vendors such as Decagon mitigates these risks by providing pre-tested technology, dedicated expertise, and built-in safeguards against AI hallucinations.
Decagon’s unique approach: Agent Operating Procedures (AOPs)
Decagon differentiates itself through its unique approach with Agent Operating Procedures (AOPs). AOPs empower enterprises to define complex workflows once and seamlessly apply them across voice, chat, and email channels, enabling AI agents to perform context-aware actions consistently on behalf of users. Unlike traditional AI solutions, Decagon’s AOPs are designed to scale alongside engineering teams, offering powerful yet simple tools to configure and extend AI agent capabilities without extensive coding or infrastructure overhead.
By managing all communication channels through a single set of AOPs, enterprises achieve significant infrastructure and time savings, eliminating the need for separate solutions, redundant processes, and duplicated engineering efforts.
Integrating with your existing infrastructure
Decagon understands the value of existing internal investments and ensures these efforts aren't discarded. Through dedicated Agent Product Managers (APMs) and forward-deployed engineers (FDEs), Decagon seamlessly integrates with your existing technology stack and processes.
APMs collaborate closely with internal stakeholders to clearly define integration strategies, aligning Decagon’s capabilities with your existing workflows. FDEs embed directly within client teams, quickly bridging existing internal systems and Decagon’s innovative AOP framework, significantly accelerating the deployment process and amplifying internal systems rather than duplicating or disrupting them.
This approach ensures maximum return on past investments and enables rapid enhancement and scaling of current solutions without major infrastructure overhauls.
Addressing multi-channel challenges with Decagon
Today's customers expect seamless support across voice, chat, and email, each presenting unique AI integration challenges that Decagon effectively addresses.
Voice support: Decagon simplifies complex real-time speech recognition and nuanced language understanding, seamlessly integrating with existing telephony infrastructure, significantly reducing complexity for enterprise teams.
Chat support: Decagon's AOPs enable effective management of sophisticated multi-turn conversations, maintaining context across interactions. This significantly enhances customer satisfaction, outperforming traditional DIY solutions.
Email automation: Decagon’s AI parses nuanced, detailed email communications accurately, integrating robust intent detection and actionable workflows via easily configured AOPs.
Operational overhead and scalability with Decagon
Scaling AI customer support efficiently is central to Decagon’s design philosophy, simplifying operational efforts for enterprises.
Continuous training and updates: Decagon automates regular data refreshes and training updates through seamless integrations, significantly reducing internal resource demands.
Content management: Decagon’s intuitive interface allows non-technical teams to quickly update content, reducing dependency on continuous developer intervention.
Monitoring and quality assurance: Decagon provides robust built-in monitoring tools, automating quality assurance processes and reducing oversight requirements for internal teams.
Infrastructure and maintenance: Decagon ensures scalability through robust, reliable cloud infrastructure, guaranteeing uptime and optimal performance via comprehensive Service Level Agreements (SLAs).
A hybrid approach with Decagon
Many enterprises benefit from a hybrid strategy, combining Decagon's robust platform with internal enhancements. By leveraging Decagon’s foundational AOPs and the expertise of APMs and FDEs, enterprises can rapidly integrate custom workflows and unique actions, standing on the shoulders of existing internal solutions rather than replacing them. This strategy maintains competitive agility without discarding valuable prior work.
Conclusion: Strategic alignment and customer impact
The decision to build or buy AI support agents must align closely with organizational goals, capabilities, and strategic vision. Enterprises looking for extensive customization without heavy internal burdens find Decagon’s AOP-driven platform, enhanced by specialized integration support from APMs and FDEs, an ideal solution. Ultimately, prioritizing seamless customer experiences across all channels ensures strategic success, leveraging Decagon’s innovative AI approach to enhance satisfaction and operational excellence.
Build or buy? Navigating AI support agents across voice, chat, and email
How to scale AI customer experience faster, smarter, and with less overhead.
Enterprise organizations increasingly rely on artificial intelligence (AI) to enhance customer support through voice, chat, and email channels. With 70% of customer experience leaders planning to incorporate generative AI within two years, the strategic decision to build custom AI agents internally or purchase an enterprise-ready solution has become crucial. This decision profoundly impacts speed to market, cost, customization, and scalability.
The strategic dilemma: build vs. buy
When deciding whether to build or buy AI customer support agents, enterprises must weigh strategic objectives against resource availability and risk appetite.
Time to value: Building AI internally requires extensive planning, hiring, and development, often taking months before deployment. Conversely, off-the-shelf solutions can be operational within weeks, enabling rapid value realization.
Cost implications: Initial costs for in-house development are significant, encompassing infrastructure, specialized engineers, and ongoing maintenance. Purchased solutions typically operate under predictable, subscription-based models, shifting expenses to operational rather than capital expenditures.
Customization vs. control: In-house development allows total control, essential for organizations with unique processes or sensitive data requirements. However, platforms like Decagon offer substantial customization through innovative Agent Operating Procedures (AOPs), blending ease of use with tailored flexibility and extensibility, allowing businesses to maintain control without extensive internal development.
Risk and expertise: Internally developed AI entails considerable risk, including model inaccuracies and operational failures. Leveraging established vendors such as Decagon mitigates these risks by providing pre-tested technology, dedicated expertise, and built-in safeguards against AI hallucinations.
Decagon’s unique approach: Agent Operating Procedures (AOPs)
Decagon differentiates itself through its unique approach with Agent Operating Procedures (AOPs). AOPs empower enterprises to define complex workflows once and seamlessly apply them across voice, chat, and email channels, enabling AI agents to perform context-aware actions consistently on behalf of users. Unlike traditional AI solutions, Decagon’s AOPs are designed to scale alongside engineering teams, offering powerful yet simple tools to configure and extend AI agent capabilities without extensive coding or infrastructure overhead.
By managing all communication channels through a single set of AOPs, enterprises achieve significant infrastructure and time savings, eliminating the need for separate solutions, redundant processes, and duplicated engineering efforts.
Integrating with your existing infrastructure
Decagon understands the value of existing internal investments and ensures these efforts aren't discarded. Through dedicated Agent Product Managers (APMs) and forward-deployed engineers (FDEs), Decagon seamlessly integrates with your existing technology stack and processes.
APMs collaborate closely with internal stakeholders to clearly define integration strategies, aligning Decagon’s capabilities with your existing workflows. FDEs embed directly within client teams, quickly bridging existing internal systems and Decagon’s innovative AOP framework, significantly accelerating the deployment process and amplifying internal systems rather than duplicating or disrupting them.
This approach ensures maximum return on past investments and enables rapid enhancement and scaling of current solutions without major infrastructure overhauls.
Addressing multi-channel challenges with Decagon
Today's customers expect seamless support across voice, chat, and email, each presenting unique AI integration challenges that Decagon effectively addresses.
Voice support: Decagon simplifies complex real-time speech recognition and nuanced language understanding, seamlessly integrating with existing telephony infrastructure, significantly reducing complexity for enterprise teams.
Chat support: Decagon's AOPs enable effective management of sophisticated multi-turn conversations, maintaining context across interactions. This significantly enhances customer satisfaction, outperforming traditional DIY solutions.
Email automation: Decagon’s AI parses nuanced, detailed email communications accurately, integrating robust intent detection and actionable workflows via easily configured AOPs.
Operational overhead and scalability with Decagon
Scaling AI customer support efficiently is central to Decagon’s design philosophy, simplifying operational efforts for enterprises.
Continuous training and updates: Decagon automates regular data refreshes and training updates through seamless integrations, significantly reducing internal resource demands.
Content management: Decagon’s intuitive interface allows non-technical teams to quickly update content, reducing dependency on continuous developer intervention.
Monitoring and quality assurance: Decagon provides robust built-in monitoring tools, automating quality assurance processes and reducing oversight requirements for internal teams.
Infrastructure and maintenance: Decagon ensures scalability through robust, reliable cloud infrastructure, guaranteeing uptime and optimal performance via comprehensive Service Level Agreements (SLAs).
A hybrid approach with Decagon
Many enterprises benefit from a hybrid strategy, combining Decagon's robust platform with internal enhancements. By leveraging Decagon’s foundational AOPs and the expertise of APMs and FDEs, enterprises can rapidly integrate custom workflows and unique actions, standing on the shoulders of existing internal solutions rather than replacing them. This strategy maintains competitive agility without discarding valuable prior work.
Conclusion: Strategic alignment and customer impact
The decision to build or buy AI support agents must align closely with organizational goals, capabilities, and strategic vision. Enterprises looking for extensive customization without heavy internal burdens find Decagon’s AOP-driven platform, enhanced by specialized integration support from APMs and FDEs, an ideal solution. Ultimately, prioritizing seamless customer experiences across all channels ensures strategic success, leveraging Decagon’s innovative AI approach to enhance satisfaction and operational excellence.
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