Competitive Comparisons

Decagon vs. Sierra (vs. Alternatives)

Information updated as of December 2025

TL;DR: Decagon and Sierra are autonomous AI platforms that replace human agents with AI. Decagon offers more direct control for tech-savvy teams, while Sierra provides a fully managed service for enterprises. Both focus on cost reduction through automation. Cresta takes a combined approach, unifying AI agents, real-time human agent guidance, and conversation intelligence that analyzes every interaction on a single platform. This may work better for organizations that want automation, augmentation, and deep operational insight together.

If you're evaluating AI agent platforms for your contact center, you've likely come across Decagon and Sierra. Both have generated buzz in the autonomous AI space. But choosing the right platform goes beyond the hype. It affects your workforce strategy, how you implement the technology, and what it will actually cost you in ways that extend far beyond the software itself.

This article compares Decagon and Sierra across how they approach implementation, how they charge you, and which types of customers they work best for.

We also look at Cresta, an alternative which combines AI agents with real-time guidance for human agents on a unified platform. This approach might work better for organizations that want automation and augmentation working together, underpinned by deep insight into every conversation, rather than choosing one or the other.

What is Decagon?

Decagon is an autonomous AI agent platform for customer service that gives CX teams direct control over how AI agents behave without requiring engineering resources. The platform lets CX operators modify agent logic, adjust when calls get escalated, and refine how conversations flow using plain language rather than code.

The technical approach centers on Agent Operating Procedures (AOPs), which combine the power and flexibility of natural language instructions with the precision and rigor of code. This lets customer experience operators build AI agent logic without coding expertise, similar to how organizations teach standard operating procedures to human agents.

The platform connects deeply to backend systems through API integration, so AI agents can take actions on their own.

What is Sierra?

Sierra is an autonomous AI agent platform for customer service that handles the technical complexity of deployment through a fully managed service model. Sierra takes responsibility for coding, integrations, and implementation, which lets enterprise consumer brands without internal AI expertise launch conversational agents quickly.

Sierra's platform helps businesses build conversational AI agents that handle customer interactions across voice, chat, and messaging channels. The underlying infrastructure, called Agent OS, is Sierra's foundational platform for building and managing AI agents. It provides tools to set up workflows, define how your brand sounds, make sure policies get followed, and execute real business actions like account updates, processing returns, and changing subscriptions through integrations with your existing business systems.

Comparing Decagon and Sierra

Both platforms deploy autonomous AI agents, but they take different approaches to implementation, pricing, and target customers. These differences determine which platform actually fits your organization's technical capabilities, budget structure, and strategic priorities.

Feature	Decagon	Sierra
Implementation model	Self-service. CX teams control AI workflows through AOPs without engineering help.	Managed service with self-service options. Vendor handles core implementation, but customers can configure through no-code tools or developer SDK.
Pricing structure	Offers per-conversation and per-resolution models. Exact rates not publicly disclosed.	Primarily per-resolution, paying only when AI solves customer issues. Other pricing options available.
Target customer	Tech-savvy teams in fintech and SaaS	Enterprise consumer brands
Technical requirements	Requires technical comfort within CX teams. Common in tech companies.	Minimal internal technical demands. Longer sales cycles and higher upfront investment.

The choice between Decagon and Sierra really comes down to control versus convenience.

Decagon gives you direct control over how the AI behaves but requires technical capability within your CX organization. Sierra removes all the technical complexity, but it means depending on their timelines when you want to make changes.

Your organization's technical maturity and how much control you prefer should drive this decision more than comparing features side by side.

When to reconsider Decagon and Sierra

Both Decagon and Sierra replace human agents with AI, which works well for certain use cases but creates challenges for others. Organizations that implement autonomous platforms need to consider several factors:

Managing workforce transitions and communicating changes to your team
Explaining service model changes to customers who might prefer talking to humans
Handling complex issues that need human judgment beyond simple transactions
Operating in regulated environments where laws require human oversight
Keeping brand relationships strong when they're built on personal service rather than just efficiency

These factors affect different organizations in different ways. High-volume transactional contact centers with straightforward workflows might find autonomous platforms work well, while organizations that compete on customer experience or operate under strict compliance requirements might see stronger results with augmentation.

An alternative approach: Cresta

Cresta is an enterprise AI platform for contact centers built on three pillars that work together: conversation intelligence that analyzes every interaction, AI agents that automate customer conversations, and real-time guidance that makes human agents more effective. The insight from analyzing 100% of conversations underpins both automation and augmentation, helping organizations identify which interactions to automate, which behaviors drive outcomes, and where human judgment matters most.

Forrester named Cresta a Leader in The Forrester Wave™: Conversation Intelligence Solutions for Contact Centers, Q2 2025.

How Cresta works

Cresta's AI-native platform was built specifically for contact center environments and delivers high transcription accuracy across industry-specific terminology. The platform delivers three core capabilities that work together during live customer conversations.

Agent Assist provides real-time guidance while agents talk with customers. The system delivers behavioral hints, compliance reminders, and step-by-step instructions based on what's happening in the conversation. Knowledge Assist figures out when agents need information and surfaces relevant answers with citations automatically. AI summaries update throughout conversations and push to CRM systems on their own, which means agents don't have to do after-call work anymore. When AI agents escalate to humans, Agent Assist provides full handoff summaries so agents have complete context from the start.

Conversation Intelligence analyzes every interaction rather than the small sample traditional quality management covers. The platform scores conversations for quality, predicts customer satisfaction without needing surveys, and spots behavioral patterns that actually correlate with business outcomes. Contact center leaders can ask questions in plain language and get analysis across their entire conversation history in minutes. The same analytics apply to both human and AI agent interactions, letting organizations benchmark performance across their entire operation.

AI Agent delivers autonomous customer interactions across voice and digital channels with ultra-low latency and natural, human-like conversations. The platform supports 30+ languages and handles complex use cases including troubleshooting, proactive outreach, collections, and retention. Cresta's hybrid architecture means AI agents work alongside human teams rather than replacing them entirely. When situations require human judgment, AI agents escalate smoothly with full conversation context carried over to Agent Assist.

Cresta offers flexible deployment options. Organizations can take a transformation partnership approach with forward-deployed engineers who handle implementation complexity, set up workflows, train models on customer data, and drive measurable outcomes. For teams that prefer more control, self-serve options let you configure and manage the platform directly. Either way, the goal is the same: getting AI agents and human agents working together effectively.

How the approaches differ

The real difference comes down to platform scope. Decagon and Sierra focus exclusively on autonomous AI agents, while Cresta combines AI agents with conversation intelligence and real-time guidance for human agents on a single platform. This means shared data, models, integrations, analytics, and governance across both AI and human agent interactions. This creates different outcomes across key metrics.

Capability	Decagon & Sierra	Cresta
Workforce Impact	Replace agents with AI.	Automate conversations with AI agents across service, sales, and retention; improve human agent performance where judgment matters.
Complex Issues	Escalate when AI reaches limits.	AI agents handle complex use cases like troubleshooting and collections; humans step in with real-time guidance when judgment is needed.
Human Oversight	Limited visibility into live AI conversations.	Agent Operations Center lets supervisors monitor AI agents in real time, intervene when needed, and extend AI capabilities with human expertise.
Quality Coverage	Visibility limited to AI-handled interactions.	Analyze every conversation. Spot coaching opportunities.
Customer Experience	Customers interact with AI by default.	AI agents handle volume; humans engage on high-emotion or high-value interactions where personal touch drives better outcomes.
Regulatory Compliance	Requires careful oversight design.	Human agents maintain control with AI support.
Insights Foundation	Analytics focused on AI agent conversations.	Analyze your history of human agent conversations to identify what to automate and what top performers do to drive results.
Continuous Improvement	Visibility ends when conversations escalate to humans.	Unified analytics across AI and human agents let you measure, tune, and manage performance across your entire operation.
Primary Outcome	Cost reduction through automation.	Revenue improvement and efficiency gains together.

Combining augmentation and automation produces different business outcomes than automation alone. Pure autonomous platforms focus on reducing what each interaction costs by removing human labor. Cresta delivers cost savings through AI agents while also improving how much revenue each interaction generates by making human agents more effective at sales, retention, and resolution. Organizations that view contact centers purely as cost centers might find autonomous-only platforms sufficient, while those that also treat contact centers as revenue drivers often see stronger returns from a combined approach.

Making the decision

Decagon and Sierra focus exclusively on automating customer service by replacing human agents with AI. This works well for high-volume transactional environments where cost reduction is the only goal, but organizations often need human judgment for complex situations too. Cresta provides both: AI agents handle volume across service, sales, collections, and retention, while the Agent Operations Center gives supervisors real-time visibility to monitor, intervene, and extend AI capabilities with human expertise when high-emotion or high-value situations call for it.

Cresta offers an alternative for organizations where these human capabilities matter. The platform combines AI agents with real-time guidance for human agents and comprehensive conversation intelligence, delivering revenue improvements right alongside efficiency gains. Organizations where contact center performance drives competitive advantage often see stronger outcomes from augmentation because it addresses both efficiency and effectiveness rather than efficiency alone.

Ready to see how Cresta works with your team? Visit our resource library to explore case studies and implementation guides, or request a demo to see the platform working with your specific use cases.

Frequently asked questions about Decagon vs. Sierra vs. Cresta

Can you use automation and augmentation together?

Yes, but the emphasis differs by platform. Decagon and Sierra prioritize autonomous automation as their core offering. Cresta offers both as core capabilities on a unified platform. AI agents handle interactions autonomously across service, sales, and retention use cases, while human agents get real-time guidance for situations requiring judgment. The two work together rather than being separate products.

How do the implementation models differ?

Sierra uses a rip-and-replace model where the vendor handles everything but you're adopting a new system wholesale. Decagon takes an integration-based approach that connects to your existing infrastructure through APIs. Cresta supports phased deployment where you can start with conversation intelligence to identify automation opportunities, expand into AI agents, and gradually increase autonomy and self-serve control over time without fragmenting your data.

What happens when AI agents can't resolve an issue?

All three platforms escalate to human agents, but what happens next differs significantly. With Decagon and Sierra, human agents typically work without AI support after the handoff. With Cresta, the human agent receives real-time AI guidance and full conversation context, so the assistance continues even after escalation. Post-handoff outcomes feed back into the system to improve future automation and guidance.

Which approach works better for regulated industries?

Augmentation is generally simpler to oversee in regulated environments like healthcare and financial services because human agents maintain direct control. That said, autonomous agents with proper guardrails can also work in regulated contexts. The key is whether your compliance team can effectively monitor AI-only interactions at scale.

Do these platforms integrate with existing contact center software?

All three integrate with major CRM systems, telephony platforms, and contact center infrastructure. The depth and ease of integration varies. Check compatibility with your specific tech stack before committing.

What's the typical ROI timeline?

Autonomous platforms often show cost savings quickly since they directly reduce headcount needs. Augmentation platforms like Cresta typically show ROI through efficiency gains and revenue improvements over a slightly longer period, but the returns compound as agent performance improves across your organization.