Cresta vs Decagon
Side-by-side comparison of features, pricing, and ratings
At a glance
| Dimension | Cresta | Decagon |
|---|---|---|
| Best for | Enterprise contact centers with 100+ agents, especially in regulated industries needing real-time agent assist and conversation intelligence for both sales and service. | High-volume consumer brands with engineering-led support teams seeking autonomous AI agents to deflect 60%+ tier-1 tickets across chat, email, and voice. |
| Pricing | Custom enterprise pricing (six-figure+). No self-serve or published tiers. Quotes require sales engagement. | Custom enterprise pricing with outcome-based billing (per resolved conversation). No published standard tiers. |
| Setup complexity | High — multi-quarter deployment, requires dedicated CCaaS infrastructure (Genesys, NICE, Five9) and CRM integration. Custom model tuning adds weeks. | Moderate to high — weeks to months depending on training data quality and integration complexity. Includes dedicated solutions architect. |
| Strongest differentiator | Real-time Agent Assist with whisper prompts that guide agents mid-call using custom-tuned models on the customer's conversation corpus. | Autonomous AI agents that take actions autonomously (refunds, account updates) using a reasoning engine and natural-language policies. |
Decagon vs Cresta comes down to a fundamental difference in philosophy: Cresta is built to augment live human agents with real-time coaching and conversation intelligence, while Decagon aims to replace human agents with autonomous, end-to-end resolution. Cresta wins for enterprises that prioritize in-call intervention and agent development, especially in regulated environments like airlines and lending. Decagon wins for high-volume consumer brands that want to deflect the majority of tickets without human involvement. Both require significant integration effort and custom pricing.
Real-time AI agent assist and conversation intelligence for enterprise contact centers.
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Core Capabilities: Cresta vs Decagon
Cresta's primary strength is real-time Agent Assist, which provides whisper prompts, knowledge retrieval, and behavioral guidance during live calls. It also offers full conversation intelligence with coaching analytics, quality management, and post-call summaries. Decagon focuses on autonomous resolution: its agents can handle end-to-end tickets across chat, email, and voice, taking actions like refunds and account updates without human intervention. It also provides evaluation harnesses and A/B testing for agents. Cresta wins for real-time augmentation; Decagon wins for full automation.
AI/Model Approach: Cresta vs Decagon
Cresta uses proprietary models fine-tuned on each customer's conversation corpus, ensuring suggestions align with internal playbooks. This is a key differentiator for compliance-heavy environments. Decagon employs an in-house reasoning engine grounded in help center docs, past tickets, and CRM data. Its Agent Operating Procedures (AOPs) allow natural-language policy authoring. Both avoid generic LLM output. Cresta wins for customization depth; Decagon wins for autonomous reasoning and action-taking.
Integrations & Ecosystem: Cresta vs Decagon
Cresta integrates deeply with major CCaaS platforms (Genesys, NICE, Five9, Amazon Connect, Twilio) and CRMs (Salesforce, MS Dynamics). It also connects to Zendesk, ServiceNow, and Snowflake. Decagon integrates with helpdesks like Zendesk, Salesforce Service Cloud, Kustomer, Intercom, Gladly, Front, and Slack, plus Snowflake. Cresta covers the contact center stack more broadly, while Decagon focuses on modern support platforms. Cresta wins for traditional CCaaS-centric environments; Decagon wins for modern, cloud-first helpdesks.
Performance & Scale: Cresta vs Decagon
Cresta is designed for enterprise contact centers with 100+ agents, processing millions of calls monthly. Its real-time whisper prompts require sub-second latency, and its conversation intelligence mines interactions at scale. Decagon handles high-volume consumer brands, deflecting 60%+ of tickets. Outcome-based pricing aligns with scale. Performance benchmarks for both are not publicly available. Both are viable for large deployments. Tie on current data.
Workflow & Developer Experience: Cresta vs Decagon
Cresta requires deep integration with existing CCaaS and CRM, and its custom model tuning is a multi-week process involving customer conversations and playbook data. It provides AI quality management and auto-scorecards. Decagon offers a more self-service approach with A/B testing, evaluation harnesses, and dedicated solutions architect support. Its Agent Operating Procedures can be authored in natural language. Decagon wins for engineering-led teams seeking control and experimentation capabilities.
Pricing compared
Cresta Pricing (2026)
Cresta offers only a custom Enterprise plan. Pricing is not publicly disclosed but is typically six figures annually, with an upfront commitment and multi-quarter deployment. There is no self-serve or free tier. The plan includes Real-time Agent Assist, Conversation Intelligence, Knowledge Agent, Autonomous AI Agent, custom-tuned models on customer corpus, quality management, and CCaaS+CRM integrations. Overage fees and contract terms are not published.
Decagon Pricing (2026)
Decagon also offers only a custom Enterprise plan with outcome-based pricing, meaning charges are per resolved conversation. This aligns cost with value. The plan includes autonomous AI agents across chat, email, and embedded widgets, CRM and helpdesk integrations, reasoning engine, evaluation harness, SOC 2 Type II, enterprise SSO, and a dedicated solutions architect. No published standard tiers or free trial.
Value-per-dollar: Cresta vs Decagon
For organizations that need real-time human augmentation and conversation intelligence, Cresta's value lies in improving agent performance and compliance at scale. For teams aiming to fully automate tier-1 support, Decagon's outcome-based pricing offers clear alignment with resolution volume. Cresta likely commands a higher upfront cost due to custom model tuning and CCaaS ecosystem depth. Decagon's per-resolution model may be more predictable for growing volumes. Tie on value — depends on use case and budget model.
Who should pick which
- Enterprise contact center ops lead (200+ agents, regulated industry)Pick: Cresta
Cresta's real-time agent assist and compliance risk detection are tailored for lending, insurance, and telecom environments where in-call coaching and regulatory guardrails are critical.
- Head of CX at high-volume consumer brand (e.g., fintech, retail)Pick: Decagon
Decagon's autonomous agents can deflect 60%+ of tier-1 tickets and take actions like refunds and account updates end-to-end, reducing human burden.
- Engineering-led support team at a mid-growth startup (<100 agents)Pick: Decagon
Decagon offers A/B testing, evaluation harnesses, and natural-language policy authoring, fitting engineering workflows better than Cresta's heavier professional services model.
- VP of Operations at a large airline or hospitality chainPick: Cresta
Cresta's deep CCaaS integrations (Genesys, NICE, Five9) and custom-tuned models on conversation history are proven in similar high-volume, regulated environments.
Frequently Asked Questions
What is the primary difference between Cresta and Decagon?
Cresta focuses on real-time agent augmentation (whisper prompts, coaching, conversation intelligence) for live agents during calls. Decagon focuses on autonomous, end-to-end ticket resolution by AI agents, handling actions like refunds without human input.
Which tool is better for real-time agent coaching?
Cresta wins for real-time agent coaching. Its Agent Assist provides whisper prompts, behavioral guidance, and knowledge retrieval mid-call, plus conversation intelligence and quality scoring.
Can Decagon or Cresta handle full ticket deflection without human agents?
Decagon is built for full autonomous deflection across chat, email, and voice. Cresta has an Autonomous AI Agent feature but is primarily designed to augment, not replace, human agents.
Do Cresta and Decagon integrate with Salesforce?
Yes, both integrate with Salesforce. Cresta integrates with Salesforce CRM and Microsoft Dynamics. Decagon integrates with Salesforce Service Cloud and other modern helpdesks like Zendesk and Intercom.
What industries are best suited for Cresta vs Decagon?
Cresta suits regulated industries like financial services, airlines, and telco where compliance and human agent coaching are critical. Decagon suits high-volume consumer brands like fintech and e-commerce that want to automate support.
Is there a free trial for Cresta or Decagon?
Neither offers a public free trial or self-serve tier. Both require custom enterprise pricing and typically involve a sales-led process.
How long does it take to deploy Cresta vs Decagon?
Cresta deployments are multi-quarter due to CCaaS integration and custom model tuning. Decagon deployments are weeks to months, depending on training data quality and integration complexity.
Which tool is better for small teams with limited CX ops?
Neither is ideal for small teams. Cresta targets enterprises with 100+ agents. Decagon is designed for high-volume brands and may overwhelm teams without dedicated CX ops headcount.
Last reviewed: May 12, 2026