8 Best Decagon Competitors for Contact Centers

‍Information updated as of January 2026.

TL;DR: Decagon has gained traction among tech-forward companies seeking autonomous customer support, but its focus on pure automation creates gaps for organizations that need both AI efficiency and human agent performance. The best alternatives depend on whether you want autonomous-first platforms like Sierra, enterprise conversational AI like Cognigy or Kore.ai, or a unified approach like Cresta that combines AI agents with real-time human agent guidance and conversation intelligence.

Contact center leaders need to scale customer support without constantly hiring, which has driven rapid adoption of AI agent platforms like Decagon. While Decagon works well for tech companies wanting code-level control over autonomous agents, organizations with large existing agent teams, regulated environments, or complex voice operations often find they need more than pure automation.

The reality is that most enterprise contact centers aren't choosing between humans and AI. They're figuring out how to integrate AI alongside their existing teams. Pure automation platforms solve part of the equation by handling routine interactions, but they leave gaps in human agent performance, quality visibility, and the handoff moments where customer experience often breaks down. 

Organizations evaluating Decagon alternatives increasingly look for platforms that treat contact center automation and augmentation as complementary rather than competing strategies.

This article examines the top Decagon competitors for contact center teams, comparing capabilities across autonomous platforms, enterprise conversational AI, and unified human-plus-AI approaches to help you identify the right platform for your organization.

Why contact centers are evaluating Decagon competitors

Organizations evaluate Decagon alternatives for varied reasons, from implementation constraints to gaps that pure automation leaves unaddressed.

Some teams find the technical requirements challenging. Decagon's Agent Operating Procedures (AOPs) offer granular control over AI behavior, but CX organizations without engineering support sometimes struggle with implementation and ongoing customization.

Others want more than automation alone. Organizations with large existing agent teams often look for platforms that improve human agent performance alongside AI capabilities, not just deflection metrics. They're thinking about the complete operation, not just the interactions AI can handle.

Analytics coverage also matters. Decagon provides reporting on AI agent performance, but organizations often want conversation intelligence across the full customer journey, not just AI interactions in isolation. When visibility ends at the handoff, teams can't connect AI containment rates to downstream resolution quality, agent performance, or customer satisfaction. 

And conversations that never involve AI at all still hold valuable insights into what top performers do differently to deliver strong customer experiences. Platforms that analyze both AI and human conversations give leaders a complete picture of what's actually happening.

Regulated industries often need specific compliance features and governance controls. Financial services, healthcare, and other regulated verticals may require platforms with deeper audit trails, human oversight mechanisms, and industry-specific certifications already in place.

Finally, some buyers simply prefer different deployment models. Whether that's a fully managed service or pre-built industry templates, the market offers varied approaches to enterprise AI agents.

Best Decagon competitors at a glance

The AI agent market breaks into a few categories. Autonomous-first platforms like Sierra focus on replacing human agents with AI for maximum deflection. Legacy conversational AI platforms like Cognigy and Kore.ai bring mature ecosystems with extensive integrations, channel partners, and pre-built industry templates.

Unified platforms like Cresta combine AI agents with real-time agent guidance and conversation intelligence, treating automation and human performance as connected rather than separate problems.

1. Cresta

Cresta approaches AI agents differently from pure automation platforms. Rather than treating AI agents as a standalone product designed to replace human agents, Cresta built AI agents on its foundation of conversation intelligence and real-time agent guidance. That heritage informs how AI agents are trained and how they handle complex conversations.

The same conversation data that trains AI agents also powers real-time guidance for human agents, and the same analytics that measure AI containment rates also track resolution quality and customer satisfaction across your entire operation. 

Cresta's conversation intelligence capabilities earned recognition in The Forrester Wave Conversation Intelligence Solutions for Contact Centers, Q2 2025, where Cresta was named a Leader with the highest score in the Current Offering category and the highest possible scores across 16 criteria.

Key features:

• Cresta AI Agent handles customer interactions autonomously across voice and digital channels. Unlike AI agents built from scripts and SOPs, Cresta AI Agents are grounded in real human conversations, using interaction data to understand how conversations actually unfold, where they deviate, and what drives successful resolution. Automation Discovery analyzes large volumes of conversations to identify which interactions are suitable for automation based on complexity, frequency, and resolution patterns, so AI agents are built around proven use cases rather than assumptions.
• Sub-agent architecture uses specialized task-specific agents coordinated by a routing agent, handling complex multi-intent conversations reliably at enterprise scale. Deterministic state management tracks each customer's progress step by step, ensuring the AI triggers appropriate actions at exactly the right moments while maintaining predictable, auditable behavior.
• Voice experience maintains proven low-latency response times backed by SLAs. Human-aware turn-taking accurately detects when customers intend to speak, distinguishes true interruptions from background noise, and avoids talking over callers. Barge-in handling preserves conversational state so the agent can rejoin smoothly without forcing repetition.
• Agent Operations Center provides human-in-the-loop supervision, letting supervisors monitor hundreds of simultaneous AI conversations, intervene when needed, and extend AI capabilities with human expertise. This control plane distinguishes Cresta from autonomous-only platforms, where visibility ends at deployment.
• Post-handoff continuity sets Cresta apart from pure automation platforms. When AI agents escalate to humans, Cresta Agent Assist provides full handoff context and continues supporting the human agent with real-time guidance, behavioral hints, and knowledge with citations. Customers do not have to repeat themselves, and teams maintain visibility into what happens after escalation.
• Cresta Conversation Intelligence analyzes 100% of interactions across both AI and human agents, connecting performance data to business outcomes rather than just containment metrics. Predictive CSAT scoring infers customer satisfaction from every conversation without surveys. This unified analytics approach lets organizations benchmark AI and human agent performance side by side.

Enterprise guardrails provide four layers of defense: system-level guardrails embedded in prompts, supervisory guardrails running in parallel, LLM-driven adversarial testing, and automated behavioral quality management.

The platform integrates with Salesforce, NICE, Five9, Genesys, Cisco, Amazon Connect, Twilio, Avaya, RingCentral, and 8x8, maintaining enterprise-grade security, including SOC 2 Type II, GDPR, HIPAA, PCI DSS, ISO 27001, and ISO 42001 certification for responsible AI.

Who it's for: Organizations that want automation and human agent performance together, not either/or. Large or regulated contact centers in financial services, healthcare, telecommunications, and travel benefit from human-in-the-loop oversight and granular compliance monitoring.

See how organizations like yours use Cresta. Visit the resource library to learn more or request a demo.

2. Sierra

Sierra is an autonomous AI agent platform that handles deployment through a fully managed service model. The company takes responsibility for coding, integrations, and implementation, letting organizations launch conversational agents without internal AI expertise.

Key features:

• Agent OS platform manages AI agents across voice, chat, and messaging with workflow setup, brand voice configuration, and policy enforcement
• Centralized configuration allows agents to be deployed across multiple channels without rebuilding for each
• Fully managed service handles implementation complexity, integrations, and ongoing maintenance

Who it's for: Brands wanting full-service AI deployment without internal technical lift. Works well for organizations comfortable with vendor-managed implementations seeking autonomous agents for transactional interactions.

3. Cognigy

Cognigy provides conversational AI using a hybrid architecture that combines rule-based automation with large language model capabilities. The platform emphasizes on-rails, predictable conversation workflows where structured logic governs how interactions unfold.

Key features:

• Hybrid architecture layers LLM reasoning on top of deterministic, rule-based workflows for predictable conversation paths
• Low-code and no-code AI Agent Studio lets business users and developers co-create and deploy AI agents
• Full automation spectrum, including conversational IVR, self-service, agent assist, and RPA across voice and digital channels

Who it's for: Global enterprises needing on-rails, predictable conversation workflows with flexible deployment options. The platform supports on-premise installations for organizations requiring that level of control.

4. Kore.ai

Kore.ai provides conversational AI with strength in no-code development and pre-built industry solutions. The platform offers on-rails templates and workflows designed for specific verticals, prioritizing structured paths over open-ended customization.

Key features

• Experience Optimization (XO) Platform enables no-code conversational AI development with pre-built templates
• Industry-specific solutions for banking, healthcare, and retail with pre-configured workflows and compliance features
• Multi-channel deployment across voice, chat, messaging, and email with unified conversation management

Who it's for: Enterprises seeking on-rails industry templates over custom development. Works well for banking, healthcare, and retail teams that prefer pre-configured workflows to building from scratch.

5. Google CCAI (Contact Center AI)

Google Contact Center AI brings Google's natural language processing and machine learning to contact center automation. The platform integrates with Google Cloud infrastructure for organizations already in that ecosystem.

Key features:

• Dialogflow CX provides conversational AI with Google's natural language understanding, intent recognition, and entity extraction
• Agent Assist delivers real-time suggestions to human agents, surfacing relevant information and recommended responses
• Insights analyzes conversation data to identify patterns, sentiment trends, and improvement opportunities

Who it's for: Organizations already on Google Cloud who want AI capabilities integrated with existing infrastructure. Works well for technical teams comfortable leveraging Google's broader ecosystem for custom implementations.

6. Forethought AI

Forethought AI is an agentic AI platform with particular strength in ticket triage and classification. The platform routes incoming requests to the right teams or workflows based on intent detection and historical patterns.

Key features:

• Triage agent automatically categorizes and routes tickets based on intent, sentiment, and historical resolution data
• Autoflows enable workflow creation from natural language descriptions, reducing setup time for routing logic
• The product suite also includes Solve (autonomous resolution), Assist (agent guidance), and Discover (knowledge gap identification)

Who it's for: Support teams prioritizing ticket routing and classification workflows. Works well for organizations with high ticket volumes needing consistent categorization and routing before human or AI resolution.

7. Intercom Fin AI

Intercom provides AI-powered support automation designed to work within its existing chat and messaging platform. Fin AI handles customer queries across chat, email, voice, SMS, and social channels using generative AI trained on organization knowledge bases.

Key features

• Native integration with Intercom's chat platform, leveraging existing conversation history and customer data
• Generative AI trained on organization knowledge bases across multiple channels
• Straightforward setup for teams already using Intercom, with minimal additional configuration required

Who it's for: Companies already on Intercom's chat platform seeking native AI integration. Works best for organizations that want to add automation without migrating to a new system or managing separate tools.

8. Ada

Ada is an AI-powered platform for customer service automation across chat and voice channels. The platform uses Playbooks to define agent behavior through structured, pre-built workflows that can be configured from natural language prompts or existing SOPs.

Key features

• Playbooks provide rigidly-defined conversation workflows, enabling fast deployment without extensive custom development
• Configuration from natural language or existing SOPs reduces time to launch
• Voice automation extends beyond chat to handle phone-based customer interactions

Who it's for: SaaS companies needing fast deployment through pre-built, rigidly-defined workflows. Works well for organizations that prefer structured automation over open-ended AI configuration.

Choosing the right alternative for your organization

Selecting the right AI agent platform requires an honest assessment of what you're actually trying to solve.

If your primary goal is maximum automation with minimal internal technical lift, Intercom offers easier self-serve deployment for companies wanting to get started quickly, though that simplicity can come at the expense of performance in both simple and complex conversations.

Alternatively, if you need traditional conversational AI with global language support or deterministic predictability, Cognigy and Kore.ai offer mature platforms with flexible deployment options. Google CCAI makes sense for organizations already invested in Google Cloud infrastructure who want basic AI capabilities integrated with their existing ecosystem.

And if the problem is that you need both automation and human agent performance, not just one or the other, Cresta takes a different approach. The platform treats AI agents and human agent performance as connected problems, giving you conversation intelligence across all interactions, plus real-time guidance when humans are on the line. That matters most for organizations with large existing agent teams, regulated environments, or situations where customer experience depends on getting the handoff moments right.

If you want to learn more about how Cresta's approach might work for your team, we've put together case studies and resources that show real results from organizations across financial services, healthcare, telecommunications, and travel. Request a demo to see the platform in action.

Frequently asked questions about the best Decagon competitors

How does Cresta differ from autonomous-first platforms like Decagon and Sierra?

Autonomous platforms focus on replacing human agents with AI, which works well for straightforward transactions but creates gaps elsewhere. Cresta combines AI agents with real-time guidance for human agents and conversation intelligence across all interactions. 

Cresta Agent Operations Center lets supervisors monitor AI conversations and intervene when needed, while Agent Assist continues supporting human agents after AI escalations. This unified approach delivers revenue improvements alongside efficiency gains rather than cost reduction alone.

What should I ask vendors about AI agent governance and oversight?

Ask how the platform manages context and state throughout conversations, what safeguards prevent hallucinations or skipped workflow steps, and whether human supervisors can monitor and intervene in AI conversations in real time. 

Understanding guardrail implementation matters for regulated environments. Cresta provides four layers of defense, including system-level guardrails, supervisory guardrails, adversarial testing, and automated behavioral quality management.

Can I start with conversation intelligence before deploying AI agents?

Yes, Cresta's recommended deployment follows an Analyze, Augment, Automate progression. Organizations often start with Conversation Intelligence to understand what's happening in their interactions, then add Agent Assist to improve human agent performance, and then deploy AI Agents for conversations identified as automation-ready. This phased approach reduces risk and builds organizational confidence.

How long does implementation typically take?

Timelines vary by scope and complexity. Organizations deploying conversation intelligence often see initial insights within weeks. AI agent implementations require workflow design, testing, and simulation before production deployment. 

Cresta's forward-deployed partnership model includes engineers and product managers working directly with customers to drive measurable outcomes rather than just technology deployment.

What happens to conversations when AI agents escalate to humans?

With autonomous-only platforms, visibility typically ends when AI escalates. With Cresta, the human agent receives full handoff context and real-time AI guidance through Agent Assist, so the assistance continues throughout the conversation. 

Post-escalation outcomes feed back into the system to improve both AI automation and human agent coaching.

Which industries see the strongest results from unified human-plus-AI platforms?

Financial services, healthcare, telecommunications, travel, and home services organizations with complex conversations, regulatory requirements, or high-value customer relationships often see stronger outcomes from combined approaches. 

These environments benefit from human oversight capabilities, compliance monitoring, and the ability to boost agent performance alongside automation.