Decagon vs Sierra: Which AI Support Agent Fits Your Team?

Enterprise support and CX leaders shortlisting modern AI agents almost always land on Decagon and Sierra together. Both are AI-native (not bolted onto a legacy helpdesk), both target large-volume support orgs, and both price on results rather than seats. This page gives a fair head-to-head, then explains where a fully-managed model like Auralis changes the calculus.

Quick comparison

Pricing and capabilities as of 2026; vendors publish little publicly and "starting" figures change.

Decagon: the configurable AI concierge

Decagon positions itself as "the AI concierge for every customer" — an AI-native platform that resolves customer conversations across chat, email, and increasingly voice. It's known for a strong admin experience: business users can shape agent behavior, and its analytics surface why conversations resolve or escalate. Decagon has won meaningful enterprise logos and is regarded as one of the most polished AI agent products on the market.

Pricing is quote-based. Third-party reporting describes an annual platform fee (commonly cited around $50,000) layered with usage — either per conversation the AI handles (regardless of outcome) or per successful resolution. There's no public pricing page or calculator, and Decagon has no native helpdesk, so most buyers keep a separate ticketing system (Zendesk, Salesforce Service Cloud) alongside it.

Best for: Enterprises that want a configurable, analytics-rich AI agent and have the internal team to build, train, and maintain it. Watch-outs: Custom-quoted six-figure contracts; you run the platform yourself; a separate helpdesk is still required; complex integrations can trigger professional-services fees.

Sierra: outcome-based agents from Bret Taylor

Sierra, co-founded by Bret Taylor (former Salesforce co-CEO and chair of the OpenAI board), is an enterprise "agent OS" for building autonomous, on-brand AI agents across chat, voice, email, SMS, and messaging. Its signature contribution is outcome-based pricing: you pay when the agent achieves a defined result (a resolution, a saved cancellation, an upsell), and in most cases pay nothing when a conversation goes unresolved. Sierra has grown exceptionally fast, crossing $150M ARR in early 2026 and raising a large Series E, and it emphasizes brand safety and governance for Fortune 500 deployments.

Sierra publishes no pricing; independent estimates put typical enterprise engagements in the low-to-mid six figures per year. As with Decagon, it's a platform: your team (with Sierra's help) designs the agent, connects systems, and owns ongoing quality.

Best for: Large brands that want tightly governed, on-brand agents and prefer to pay strictly for outcomes. Watch-outs: No public pricing; enterprise-scale commitments; you still own the build-and-maintain work; newer category with evolving best practices.

Decagon vs Sierra: how to read the head-to-head

The two are more alike than different. Both are AI-native, enterprise-focused, and results-priced. Practical differences buyers report:

• Pricing philosophy. Sierra is purist about outcomes (pay on results). Decagon more often offers per-conversation pricing, which is predictable but charges whether or not the issue is solved.
• Product surface. Decagon is frequently praised for its admin/analytics depth; Sierra for governed, multimodal (especially voice) agents and brand control.
• Helpdesk. Neither is a system of record; both sit on top of your existing ticketing stack.

Either way, you are buying software you operate. That's the axis where a managed alternative differs.

Why teams choose Auralis instead

Decagon and Sierra sell you an AI platform. Auralis delivers the outcome. Everyone else sells software your team has to configure, train, run, and maintain. Auralis is a fully-managed, done-for-you AI support layer: its experts build, run, and continuously tune the AI against your KPIs, so you get resolved tickets, higher CSAT, and lower cost per contact as a service — not another license to administer.

That difference shows up in results and effort:

• Up to 74% of requests resolved autonomously — across chat, voice, email, and tickets in one system, not five point tools.
• 45% lower cost per ticket and 5x higher agent productivity, with leadership analytics and CSAT reporting via Auralis Audit.
• Days, not months to value — because Auralis' team does the building and tuning, not yours.
• 500+ integrations out of the box (anything with an API), and it's LLM-agnostic — orchestrating public, open-source, or your own models, deployable cloud, private, or on-prem.
• Enterprise security by default: SOC 2 Type II, ISO 27001, GDPR, and HIPAA-ready.

Proof it travels: TouchPoint Software reduced operational costs 40% (Morgan S., VP), and PowerOffice Go — with 250k+ users — chose Auralis after evaluating alternatives (Terje Johansson, Product Director). Auralis is trusted by Norwegian Cruise Line, Visma, Popeyes, and the State of California, and has been featured by NBC, the Associated Press, Business Insider, and Yahoo Finance.

How to choose

• Want maximum control and have the team to run it? Decagon and Sierra are both strong AI-native platforms; pick Sierra for strict outcome pricing and governed voice, Decagon for admin/analytics depth.
• Want the result without staffing an AI ops function? Choose the managed model. Auralis owns the build, tuning, and continuous optimization against your KPIs.
• Need voice, email, and tickets — not just chat? Confirm true multichannel coverage. Auralis resolves across all four in one system.
• Security-sensitive? All three target enterprise; verify certifications map to your requirements (Auralis: SOC 2 Type II, ISO 27001, GDPR, HIPAA-ready).