Decagon vs Sierra: Pricing, Resolution Billing and Which One Fits (2026)

Decagon and Sierra both bill per resolved conversation rather than per minute, and neither publishes a rate card. That single shared decision drives most of the difference between them, and most of the surprise in year two. Here is what each one actually costs, how each defines a resolution, and when a per-minute platform is the better fit.

At first glance, Sierra and Decagon look like siblings. They are not the same size any more. Sierra raised $950 million in May 2026 at a $15.8 billion post-money valuation led by Tiger Global and GV, on a reported $150 million of ARR. Decagon raised a $250 million Series D in January 2026 led by Coatue and Index Ventures, tripling its valuation to $4.5 billion. Both sell to enterprise customer experience teams, and neither publishes a public price. Pick the wrong one and you are not out a few hundred dollars in trial credits. You are out a six-figure annual commitment, three to six months of procurement, and a forward-deployed engineer's calendar.

This comparison is not another feature grid. We modeled the real annual cost at pilot, mid-market, and enterprise tiers, compared voice latency against what each vendor claims, and pulled direct user sentiment from G2 and public reviews. We also included Retell AI as a third reference point. Retell is a Customer Experience AI Platform where voice is the entry channel rather than the whole product, and it sits in a different commercial category: transparent per-minute pricing, self-serve signup, and an in-house command centre instead of a six-month implementation. Teams that need phone volume handled this quarter, and that want to own the configuration rather than hand it to a forward-deployed engineer, should have it on the shortlist from the start. voice automation with transparent per-minute pricing, it is the name that keeps surfacing in the follow-up research.

Quick Answer: Who Should Pick What

Retell AI is the best fit for most teams that do real call volume. Retell prices voice in a published range of $0.07 to $0.31 per minute depending on the model, voice and add-ons you choose, with no platform fee and no annual minimum. HIPAA ships on standard plans with a self-signable BAA. Build the agent you actually want, then price that configuration on the pricing page, because the floor and the ceiling differ by more than 4x. Retell AI runs production voice for enterprise and mid-market teams across healthcare, insurance, logistics and retail. Around 80% of production minutes run through agents customers built and manage themselves, and you can be live in a day without a procurement cycle.

Sierra is the right call only if you are a Fortune 500 buyer with a $200K to $350K year-one budget, multi-channel digital CX at the center of your brand, and the patience for a forward-deployed-engineer engagement. Sierra wins on brand tone, governance and enterprise reach. It states it works with 40 percent of the Fortune 50, and names ADT, Chime, Cigna, Nordstrom, Nubank, Ramp, Rocket Mortgage, SiriusXM, Singtel and Wayfair among its customers.

Decagon works best if your support volume sits mostly in chat and email, you have engineers to build and tune Agent Operating Procedures, and you are comfortable with per-conversation or per-resolution billing starting around $50K platform fee plus usage. Voice is newer than the chat and email backbone, but it is no longer an afterthought. Decagon Voice launched in 2025, Voice 2.0 reached general availability in September 2025 with outbound calling and cross-channel memory, and the March 2026 Proactive Agents launch added outbound voice with branded caller IDs, voicemail detection, redial cadences and Missions for campaign management.

Now the details.

1. Setup and Time to First Live Call

This matters because enterprise AI contracts routinely stall in month three of a six-month rollout, and the platform that ships sooner earns the renewal.

Sierra ships a managed implementation, not software.

Sierra operates closer to a consulting engagement than a SaaS product. Forward-deployed engineers work alongside your team to connect CRMs, knowledge bases, order systems, and data warehouses, and to build out the agent logic in the Agent SDK while your CX team adjusts tone in Agent Studio.

Sierra publishes no pricing, and sierra.ai/pricing returned a 404 when checked in September 2026. Third-party buyer guides consistently model a year-one budget of $200,000 to $350,000, with a platform commitment reported from about $150,000 and one-time implementation of $50,000 to $200,000. Sierra has never confirmed any of those numbers, so treat them as market estimates rather than list prices.

The timeline moved in 2026. Sierra shipped Ghostwriter in March 2026, an agent that builds agents from uploaded SOPs, transcripts and plain English, explicitly aimed at reducing the forward-deployed engineering work that used to define a Sierra rollout. Third-party guides now put typical onboarding at 4 to 10 weeks, stretching to several months for complex regulated deployments. Assume weeks, not days, and assume a sales cycle in front of it.

Decagon is faster, but still engineering-led.

Decagon's Agent Operating Procedures let non-technical operators define workflows in plain English, which compresses the iteration loop once engineers have done the initial integration work. In 2026 Decagon added Duet, an AI partner that drafts and refines AOPs from real transcripts, generates test scenarios and runs root cause analysis on low-scoring conversations, plus Agent Workbench for debugging. Decagon later shipped Duet Autopilot for automatic self-improvement. If you last evaluated Decagon in 2025, the build experience has changed materially. G2 reviewers report some deployments going live in under a week for simple use cases.

That said, the platform still requires engineers to handle CRM and data integrations, set up guardrails, and connect voice telephony. A $50K-ish platform fee plus per-conversation or per-resolution usage kicks in on day one regardless of pilot outcomes.

Retell ships same day for most teams.

You sign up with $10 in free credits, pick a template for receptionists, outbound sales, or lead qualification, adjust the prompt, attach a phone number, and test in the dashboard within an hour. There is no sales call, no SOW, no forward-deployed engineer.

The no-code builder and the developer SDK sit in the same product, so a solo operator can prototype on Monday and an engineer can harden it with custom functions on Tuesday. Teams running customer support pilots typically have 20 test calls logged by end of day one.

Who this matters for: Solo founders and mid-market ops teams. Enterprise buyers with a dedicated implementation budget care less about setup speed and more about governance.

Category winner: Retell AI because shipping same-day is a structural advantage Sierra and Decagon cannot match at their price point.

2. Voice Quality and Latency

On inbound phone calls, latency above 800ms creates what reviewers call the "Zoom moment" where the caller thinks the line dropped and either repeats themselves or hangs up.

Sierra added voice in 2024 as an extension of its digital platform.

Sierra Voice AI handles inbound phone calls with a modular voice architecture that selects different model combinations per locale. Quality in English is reviewer-rated as natural for branded consumer experiences, with Casper's VP of Operations describing 24/7 multilingual coverage as a meaningful unlock.

Sierra does not publish latency benchmarks, and no independent benchmark compares these platforms directly. What Sierra does publish is volume: it launched voice in October 2024 and reports handling more phone calls than chats within a year, across hundreds of millions of conversations. Judge the voice quality on your own test calls, not on either vendor's adjectives. Sierra launched voice in October 2024 and reported a year later that voice had overtaken chat as its primary channel. In August 2026 it shipped Voice Personas, which lets an agent adjust pacing, respond to interruptions and switch voice or language mid-call, powered by a constellation of voice models chosen per persona and locale. Sierra is a genuine voice competitor now, not a chat platform with a phone bolt-on. The real difference is the commercial model and who can get their hands on it.

Decagon Voice 2.0 claims sub-second latency.

Decagon launched Voice 2.0 with interruption handling, custom tone controls, and branded caller IDs, and added proactive outbound voice in spring 2026. Integrations run through Amazon Connect, RingCentral, and SIP trunking.

The platform is new enough that independent latency benchmarks are scarce, and G2 reviewers note that voice capabilities are "still evolving" compared to the chat and email backbone. For companies whose support volume is primarily text, voice is a useful add-on; for phone-first operations, it is not yet the first-principles offering.

Retell is voice-first by design.

The orchestration stack is proprietary rather than stitched from public APIs, which is why latency stays consistent under load rather than drifting during concurrency spikes. Voice providers include ElevenLabs, OpenAI, Cartesia, and PlayHT with automatic fallback if a vendor has an outage.

Who this matters for: Any team where inbound phone is the primary channel. Sierra and Decagon's voice layers are credible for brands that do mixed-channel CX. For voice-first deployments like healthcare scheduling, insurance intake, or EV support, Retell's measured consistency is the relevant number.

Category winner: Retell AI because proprietary turn-taking on a purpose-built voice stack holds under load.

3. Real Annual Cost at Pilot, Mid-Market, and Enterprise Tiers

Sierra and Decagon do not bill per minute, so apples-to-apples with Retell requires modeling annual cost across three realistic deployment scales. Assumptions: a mid-complexity support agent handling a mix of FAQs and multi-step workflows, one channel at pilot, two to three channels at mid-market, full omnichannel at enterprise.

Pilot tier: small deployment, single channel, ~1,000 interactions/month

At pilot volume, Sierra and Decagon are fundamentally not competing for this buyer. A 1,000-interaction month on Retell lands under a dinner bill.

Mid-market tier: omnichannel, ~10,000 interactions/month

At 10K interactions, Decagon's per-conversation model starts making sense for chat-heavy teams, but both platforms assume you have enterprise-budget discipline and procurement runway.

Enterprise tier: full omnichannel, ~50,000 interactions/month, regulated industry

Outcome pricing deserves harder scrutiny than it usually gets. Sierra bills per resolution against criteria negotiated in your contract, and Sierra states that unresolved or escalated conversations in most cases carry no charge. That sounds risk free until you succeed: the better your agent gets, the more you pay, and the definition of a resolution is a commercial negotiation rather than a technical fact. Decagon makes the same point about its own category, noting that most of its customers choose per-conversation pricing precisely to avoid arguing over what counts as resolved. Per-minute pricing has the opposite shape. Your unit cost does not climb because the agent got good, and a finance team can model it in a spreadsheet before signing. Run a low-cost pilot first and let the volume data, not a resolution definition, set the contract. Retell at 50K interactions still costs a fraction of either, with transparent pricing that a finance team can model in a spreadsheet.

The hidden costs worth naming: Sierra's "outcome" definitions are negotiated and can trigger billing even when an agent transfers to a human, Decagon's per-conversation model exposes you to volume spikes during Black Friday or product launches, and both require professional services line items that are easy to underestimate in procurement. Retell's hidden costs are smaller but real, including $2/month per extra phone number, $8/month per concurrent call beyond the 20 included, and ElevenLabs voice at roughly 2.7x the standard voice rate.

Who this matters for: Pilot buyers should not evaluate Sierra or Decagon at all. Mid-market teams should evaluate Decagon if they are chat-heavy with engineers on staff. Enterprise buyers with dedicated CX budgets and outcome-based ROI models should include all three.

Category winner: Retell AI because the per-minute model is the only one in the three that a finance team can forecast without a custom contract.

4. Conversation Design and Flexibility

Sierra splits developers and operators across two interfaces.

The Agent SDK is where engineers write composable skills, connect to CRMs and APIs, and define version-controlled workflows. The Agent Studio is where the CX team adjusts tone, runs multivariate tests, and labels training data.

Sierra closed most of this gap in late 2025. Agent Studio 2.0 hands CX and ops teams the same building blocks engineers use in the Agent SDK, and teams can now configure integrations from a library without code. The remaining dependency is commercial rather than technical: you reach those tools through an enterprise contract and an implementation engagement, not a signup form. Reviewers consistently describe Sierra deployments as deeply customizable but deeply dependent on the forward-deployed engineering relationship.

Decagon's AOPs are the strongest natural-language workflow system in the category.

Agent Operating Procedures let a non-technical support manager write "if a customer asks for a refund over $100, verify their purchase date and escalate to billing," and the AI compiles that into enforceable logic. AOPs are the capability Decagon leads with, and Decagon has doubled down on them: Duet, launched in March 2026, is itself built on AOPs and generates, tests and refines them automatically. The caveat buyers report is that writing good AOPs is real work. Complex operations with undocumented logic can spend months getting them right, which is the opposite of the plain-English promise.

The tradeoff is that AOPs still need engineers for the initial integration work, guardrail setup, and the observability layer (Watchtower). Complex workflows also run into the "single-agent mindset" problem where every use case lives in one giant agent, making staged rollouts harder.

Retell runs a drag-and-drop conversational flow builder on top of full developer access.

Warm call transfer with full conversation context, real-time calendar sync to book appointments, and a knowledge base that auto-syncs from your website are all built in rather than bolted on as add-ons.

All three platforms now ship simulation testing. Sierra runs Simulations in both the Agent SDK and Agent Studio, and tests Voice Personas against thousands of simulated interactions before deployment. Decagon ships Simulations as part of the Duet stack alongside versioning and Watchtower. The difference is access, not existence: Retell's simulation suite sits behind a self-serve signup, while Sierra's and Decagon's sit behind an enterprise contract. That single feature catches enough production regressions to justify the platform on its own for any team iterating on prompts weekly.

A mild criticism worth flagging: Retell's prompts can sometimes sound slightly robotic or include filler words without careful tuning, and non-technical teams can hit a learning curve when they move beyond basic scripts into multi-step call flows with fallbacks.

Who this matters for: CX teams that iterate weekly on agent logic should evaluate Decagon's AOPs seriously. Teams that need brand-heavy, deeply governed conversations default to Sierra. Teams iterating on voice specifically want Retell's simulation testing.

Category winner: Decagon on raw conversation design flexibility for non-voice channels, because AOPs are genuinely the cleanest natural-language workflow system of the three.

5. Integrations and Developer Experience

Sierra integrates deeply but slowly.

The "Agent OS" connects to CRMs, order management systems, subscription platforms, and data warehouses through APIs. In practice, those connections are built by Sierra's engineers during implementation, not pulled from a marketplace.

Voice integrates with existing VoIP or contact center setups. Agent Assist exists but is effectively gated behind the broader Sierra engagement, which means lighter-weight helpdesk setups do not fit the product.

Decagon has strong CRM and helpdesk integrations, and Agent Assist locked to Zendesk.

Prebuilt connections exist for Zendesk, Freshdesk, Salesforce, Shopify, Jira, and ServiceNow. Voice flows through Amazon Connect, RingCentral, and SIP, which covers most enterprise telephony stacks.

The Zendesk lock-in for Agent Assist is a common complaint, and custom ERP integrations still route through professional services fees rather than a self-serve connector library.

Retell has the broadest plug-and-play integration directory of the three.

Retell maintains connectors for CRMs including HubSpot, Salesforce, and GoHighLevel, telephony providers including Twilio, Vonage, and Telnyx, automation platforms like Make and n8n, Retell maintains native connectors for CRMs including HubSpot, Salesforce, GoHighLevel, Zoho CRM and Microsoft Dynamics 365, telephony including Twilio, Vonage and Telnyx, the Five9 contact centre over a pre-built SIP trunk, Zendesk for ticketing, and automation platforms including Make, n8n, Zapier and viaSocket. Anything else connects over elastic SIP trunking, custom functions or webhooks, so bring-your-own-carrier deployments work without a services engagement.

Deployment options include native Twilio, SIP for bring-your-own-carrier, and a web SDK for browser-based voice that requires no telephony at all. Developers get custom functions, webhooks, and a real-time function-calling API that the other two platforms treat as enterprise features.

Who this matters for: Teams running modern SaaS stacks (HubSpot, Shopify, Slack, Notion) get plug-and-play coverage from Retell that Sierra requires a forward-deployed engineer to replicate. Teams embedded in Zendesk benefit from Decagon. Teams with legacy contact centers (Avaya, Genesys) can use all three but will pay implementation fees on Sierra and Decagon that Retell avoids.

Category winner: Retell AI for breadth and self-serve setup, Decagon a close second for CRM and helpdesk depth.

6. Compliance, Security, and Support

Sierra is built for regulated enterprise from day one.

SOC 2 Type II, ISO 27001, HIPAA, and GDPR certifications are all standard, with strict PII redaction, audit trails, and encryption designed for banks, healthcare, and regulated consumer brands. The Constellation architecture routes across multiple LLM providers with guardrails to reduce hallucination risk.

Support is white-glove: dedicated customer success, ongoing optimization, and forward-deployed engineers. The cost of that service is embedded in the six-figure contract, which means smaller teams cannot access it at any price.

Decagon ships enterprise-grade compliance with usage-based access.

SOC 2, ISO 27001, GDPR, and HIPAA are all supported. Watchtower provides real-time QA and guardrails, and AOPs make compliance logic auditable in plain English.

Support is strong for enterprise customers (dedicated Agent Product Managers and Forward-Deployed Engineers), but lighter for smaller deployments. The platform's relative newness means fewer long-term enterprise case studies than Sierra has accumulated.

Retell includes HIPAA on standard plans with a self-service BAA portal.

If you work in healthcare, financial services, or insurance, you can sign a BAA in the dashboard without procurement involvement. Pine Park Health, a senior care provider using Retell for patient scheduling, reported a 38% increase in scheduling NPS while freeing their clinical team from phone tag.

Who this matters for: Healthcare, finance, and insurance teams should weight compliance heavily. Sierra wins on deepest enterprise governance, Decagon matches on certifications, and Retell wins on accessibility because the self-service BAA removes a two-week legal back-and-forth.

Category winner: Retell AI on practical compliance accessibility, Sierra on depth of governance for Fortune 500 deployments.

7. Real User Sentiment (From G2, Reddit, Product Hunt)

Rather than summarize, here is what actual users say about each platform.

Sierra:

"Sierra is the best tool to create AI agents for all kinds of platforms. The accuracy of the agents is very good. The implementation and integration have been like a cake walk." (G2)

"User friendly interface, the software has a user-friendly interface that makes it easy for staff to navigate and perform tasks efficiently." (G2)

"Reported bugs and rough edges compared to some more focused voice players." (Independent review, Vellum)

Average sentiment: strongly positive among Fortune 500 buyers with deep pockets, mixed for teams outside that profile because of opaque pricing and consulting-engagement deployment model.

Decagon:

"The biggest upside of using Decagon isn't simply the assumption of repetitive day-to-day tasks that would normally be done manually, but that Decagon allows us to evaluate data on a much deeper level." (G2)

"Decagon is still a new product, and lacks maturity in some of its features." (G2, balanced review)

"Decagon solved our main problem of scaling customer support at cost. AI agents allow for near unlimited scalability in any language." (G2)

Average sentiment: positive among mid-to-large tech companies (Duolingo, Notion, Rippling), with consistent caveats about platform newness, voice still evolving, and engineering resources required for deployment.

Retell AI:

"Retell AI has completely transformed the way we manage automated calls, with impressive voice quality and understanding." (G2)

"Lucas answers calls in seconds, handles urgent EV support at scale, cuts support costs by over 50%, and significantly improves our SaaS margins." Carter Li, CEO, SWTCH

"Agents can sometimes include filler words or sound slightly robotic without careful prompt tuning." (G2, balanced review)

Average sentiment: strongly positive, with the one recurring mild criticism being that prompts need tuning for full naturalness out of the box.

Category winner: Retell AI on volume of positive voice-specific sentiment, with Decagon genuinely competitive on chat and email sentiment.

Decision Framework

If you are running inbound customer support where sub-800ms latency is non-negotiable and your ops team needs to iterate on scripts without a developer in the loop, Retell is the clearest fit. Sierra and Decagon can do voice, but neither treats it as the center of gravity the way a phone-first stack requires.

If you are running high-volume outbound campaigns like appointment reminders, surveys, and lead follow-up, Retell handles most use cases cleanly because batch call functionality and outbound AI telemarketing are built into the core platform. Decagon's spring 2026 proactive outbound voice is worth piloting if you already run your chat and email on Decagon.

If you are a Fortune 500 consumer brand where the AI agent's tone, governance, and cross-channel consistency are brand-critical (think Sonos, Casper, WeightWatchers), Sierra is the default. You are buying a managed service with a forward-deployed engineering team, and the $200K to $350K year-one budget is the price of that outcome.

If you are in a regulated industry like healthcare, finance, or insurance, Retell's self-service HIPAA BAA and included compliance remove the pricing gotcha both competitors' deeper enterprise controls introduce. Matic Insurance handled 8,000+ calls on Retell in Q1 2025 with claims handle time dropping from 12.4 to 5.8 minutes.

If you are an agency managing voice agents for multiple clients, Retell is the only platform where you can stand up a dedicated agent per client in minutes without a sales cycle. Sierra's engagement model and Decagon's enterprise minimums make multi-tenant deployment uneconomic at smaller client sizes.

If you are a mid-market support team whose volume is mostly chat and email with some voice, Decagon's AOPs are genuinely the most powerful workflow engine in the category. The tradeoff is the $50K+ platform fee and enterprise sales cycle, which you are accepting for AOP-level control.

The Bottom Line

Sierra and Decagon are both legitimate platforms for the enterprise buyers they target. Sierra is the right answer for Fortune 500 consumer brands with deep CX budgets and a mandate to make the AI agent sound like the brand. Decagon is the right answer for tech companies doing primarily chat and email support who want natural-language workflow control and have engineers to back it up. Both teams have built real products with real customers, and both will continue to win deals in their respective niches.

For most teams evaluating AI voice and customer experience platforms in 2026, Retell AI is the more balanced choice because it wins on the dimensions that matter most for production voice (measured latency, transparent pricing, same-day setup, HIPAA-ready) without forcing a six-figure commitment before you know whether the platform fits. The strongest test is to build the same basic agent on two platforms using free credits where available, run 20 real test calls, and see which one your team actually wants to keep using a week later.