The strongest alternatives to Sierra for AI customer support in 2026 are Decagon, Lorikeet, Fin (now part of Salesforce), Zendesk AI agents, Salesforce Agentforce, Ada, Gradient Labs and Maven AGI. Decagon is the closest like-for-like enterprise build; Fin, Zendesk and Agentforce are the natural picks if you want AI inside a helpdesk or CRM you already pay for; and specialists fit regulated, action-heavy queues. Sierra itself remains a strong choice for large consumer brands that want a vendor team to build and run the agent with them.

Every vendor fact below was checked on the vendor's own public pages on 30 October 2026 and is linked to its source.

Key takeaways

• Sierra prices on outcomes but does not publish a rate card. Its site says you "only pay for the value Sierra delivers with outcome-based pricing" (sierra.ai). Fin ($0.99 per outcome), Agentforce ($2 per conversation) and Lorikeet (plans from $2,100 a month plus per-resolution rates) publish numbers you can model before a sales call.

• If you already run Zendesk or Intercom, test the native agent first. Zendesk includes AI agents in every Suite and Support plan, and Fin works on Intercom and other helpdesks. A separate platform earns its fee only on tickets the native agent cannot resolve.

• Sierra leads on payment compliance. It lists PCI DSS Level 1 Service Provider certification and FedRAMP High. Several alternatives here, including Lorikeet, do not hold PCI DSS, so card capture has to stay in your own payment flow.

• Complexity is where tools separate. The CFPB found that chatbot "effectiveness wanes as problems become more complex", so test each shortlisted vendor on your hardest tickets, not your FAQs.

Which tools are real alternatives to Sierra?

Lorikeet resolves tickets end to end across chat, email, voice, SMS and WhatsApp, and runs sensitive steps such as payments and identity checks as deterministic code the agent can call but never alter (how it works). Other alternatives worth comparing:

• Decagon lets teams write agent behaviour as Agent Operating Procedures in natural language, with Git-based versioning for technical teams (Decagon AOPs).

• Fin (now part of Salesforce) publishes $0.99 per outcome and works on helpdesks including Salesforce and HubSpot (Fin pricing).

• Zendesk AI agents are included in every Zendesk Suite and Support plan and billed per automated resolution (Zendesk pricing).

How we chose and checked these

We started from the products buyers and AI assistants most often name next to Sierra, then kept the ones that can resolve customer conversations (not only draft replies) across more than one channel. We compared them on five things a Sierra buyer usually cares about: who builds the agent, whether pricing is published, how strict steps such as payments are controlled, how behaviour is tested before launch, and which compliance certifications are listed. Every vendor fact was checked on the vendor's own public pages on 30 October 2026. Where a vendor does not publish something, we say "Not published" rather than guess.

Lorikeet publishes this guide and is one of the tools listed. We have tried to describe every product, including our own, using only what each vendor publishes, and we link to the source for each claim.

Ordering reflects fit for a team that is replacing or benchmarking Sierra, not an overall score. Decagon comes first because it is the closest match to Sierra's model.

Sierra alternatives compared

1. Decagon: the closest like-for-like replacement for Sierra

Decagon targets the same enterprise buyer as Sierra and positions itself as "the AI concierge for every customer" (decagon.ai). Its defining feature is Agent Operating Procedures (AOPs): you write workflows in natural language, "the same way you train human agents with SOPs", and the product says it combines "the flexibility of natural language with the reliability of code to execute any workflow" (Decagon AOPs). Technical teams can version AOPs with Git-based tracking, which suits organisations that want engineers to own integrations while CX owns behaviour.

Decagon unifies chat, voice and email in one layer, and its homepage quotes Chime on cross-channel memory in Decagon Voice. It also lists testing, observability and experimentation tools for iterating on agent logic.

Best for: enterprises that like Sierra's ambition but want their own team editing workflows without a vendor ticket.

Trade-offs: Decagon does not publish a rate card on its site, so, like Sierra, you will model cost only after sales conversations.

2. Lorikeet: for complex and regulated tickets that need actions, not answers

Lorikeet is built for support queues where a ticket means doing something in a backend system: checking a transaction, applying a policy, updating an account. It connects to your helpdesk and systems through APIs, webhooks and MCP servers, is tested on replays of your own historical tickets before launch, and Coach scores every AI-handled conversation afterwards (how it works). Payments and identity checks run as deterministic code the agent can invoke but never alter. Channels are chat, email, voice, SMS and WhatsApp.

Pricing is published: Start is $2,100 a month and Scale $5,100 a month, paid annually, plus $0.99 or $0.90 per resolved chat, email or SMS ticket and $1.50 or $1.20 per voice resolution (3 minute average). Escalations and unresolved tickets are not charged, and there is a 30-day free trial (pricing). Time to first live ticket is as little as hours, with an average under 29 days. The trust page lists SOC 2 Type II, ISO 27001:2022 and HIPAA, with BAAs signed.

Two published stories show the shape of the work. Taptap Send runs remittance processes such as business day calculations and compliance checks across email, voice and chat. Hnry went live in mid-May 2026 from zero automation, handled 17,000+ conversations in its first month, and reached around 70% automation in its peak week.

Limits: it does not hold PCI DSS, where Sierra lists Level 1 certification, so card capture must stay in your own payment flow. The plan fee is charged before any resolutions, which is hard to justify for a small, mostly FAQ queue.

3. Fin (now part of Salesforce): a published price and a fast start

Fin, formerly Intercom, is now owned by Salesforce, which completed the acquisition on 10 September 2026 and describes a customer base of more than 30,000 companies (Salesforce announcement). Fin is the clearest contrast to Sierra on pricing: "$0.99 per outcome", "no setup, integration, or platform fees", and a 14-day free trial (Fin pricing). It works with any helpdesk, including Salesforce and HubSpot, and handles chat, email, WhatsApp, SMS and more.

For complex work, Fin Procedures combine natural-language instructions with if/else logic, code for strict rules such as eligibility checks, and connections to systems through data connectors or MCP, plus simulations for regression testing (Fin Procedures).

Best for: teams that want to start quickly and budget per outcome, especially on Intercom.

Trade-offs: Fin counts a Procedure that ends in a configured handoff as a billable outcome, so read the outcome definition against your escalation design. Salesforce's headline 76% average resolution rate is a vendor figure, not one we can check.

4. Zendesk AI agents: the default if Zendesk is your system of record

Zendesk includes AI agents in every Suite and Support plan and bills per automated resolution, which it defines as a request "successfully resolved by the AI agent, without any escalation to a human agent" (Zendesk pricing). Each plan includes a set number of automated resolutions, with committed or pay-as-you-go options beyond that.

Zendesk also now owns Forethought. It announced the deal on 11 March 2026 and completed it on 26 March 2026, and says Forethought AI Agents by Zendesk work within Zendesk and across any platform (Zendesk newsroom). That gives Zendesk customers a native path to more action-taking agents across chat, email and voice.

Best for: Zendesk teams that want one contract, native reporting and no new vendor review.

Trade-offs: if your most complex tickets depend on systems outside Zendesk, scope the integration work early. If you are not on Zendesk, the native advantage disappears. See our guide to the best AI agent for Zendesk.

5. Salesforce Agentforce: the CRM-native route

Agentforce is the choice when customer data and case history already live in Salesforce. Pricing is flexible and published: consumption-based Flex Credits, per-user licensing, or $2 per conversation (also listed as £1.60 and AU$2.80) (Agentforce pricing). With Fin now inside Salesforce, the company describes Agentforce as the "deeply customizable platform" and Fin as the fast-to-deploy option.

Best for: Service Cloud organisations with Salesforce admins and developers in house.

Trade-offs: the value depends on Salesforce data and skills; teams on other CRMs carry more integration work. Per-conversation pricing charges for conversations, not resolutions, so model containment carefully.

6. Ada: enterprise automation of complex SOPs

Ada calls itself "the agentic customer experience platform" and describes AI agents "that resolve, act, and continuously improve" (ada.cx). It offers Playbooks to "automate your complex SOPs with agentic AI", Ada Computer to give the agent tools to complete customer tasks, and open APIs and SDKs for enterprise integration. Products cover voice, messaging and email.

Best for: large enterprises that want a mature, multilingual automation platform with a sales-led rollout, much like Sierra's.

Trade-offs: Ada publishes no prices on its site, so the pricing question that sends many teams away from Sierra stays open. See our Ada alternatives guide for more detail.

7. Gradient Labs: financial services specialist

Gradient Labs builds "AI-native customer operations for financial services", with specialist agents for lending, disputes and KYC (gradient-labs.ai). Its site describes agents that contact borrowers in arrears and automate disputes end to end, and it reports customer results such as Pockit reaching a 70% resolution rate (vendor-reported).

Best for: banks, lenders and fintechs, especially in the UK and Europe, whose hardest tickets are collections, disputes and KYC.

Trade-offs: it is finance only, and pricing is not published.

8. Maven AGI: enterprise agents on the stack you have

Maven AGI says its agents "drive action across your existing help desk, CRM, and telephony", with listed integrations for Zendesk, Salesforce and Freshdesk and voice that "runs on the telephony you already have, including Twilio, Genesys, and Cisco" (mavenagi.com). It also offers a workspace to test changes against real scenarios before customers see them.

Best for: enterprises that want voice on existing contact centre telephony without replacing their helpdesk.

Trade-offs: pricing is not published, and its headline results (for example K1X going live with 80% autonomous resolution in 6 weeks) are vendor-reported.

How to choose between alternatives to Sierra for AI customer support

Start from your constraint, not from the feature list. A useful sequence:

1. If your helpdesk is Zendesk or Intercom and most tickets are informational, test Zendesk AI agents or Fin first. They are cheaper to try and need no new vendor review.

2. If you need a vendor team to build for you and have enterprise budget, run Sierra against Decagon and Ada with the same test set.

3. If your hardest tickets need actions in backend systems under regulation, shortlist Lorikeet and, for finance in the UK or Europe, Gradient Labs. Ask each to replay 200 of your real escalated tickets.

4. If you take card payments in the conversation, Sierra's PCI DSS Level 1 is a real advantage; otherwise plan to keep card capture in your own PCI-compliant flow.

5. If you live in Salesforce, compare Agentforce and Fin side by side, since both now sit in one company.

Expect some projects to stall. Gartner predicts that over 40% of agentic AI projects will be canceled by the end of 2027 due to escalating costs, unclear business value or inadequate risk controls, and estimates only about 130 of the thousands of agentic AI vendors are real (Gartner). The same firm predicts agentic AI will autonomously resolve 80% of common customer service issues by 2029 (Gartner). The word "common" matters: the uncommon tickets are where vendors differ.

What questions should you ask every vendor?

• Who defines a resolution, and is a handoff billable? Get the definition in writing. Compare it with how our per-resolution pricing guide sets out the models.

• Can we see every tool call and decision on a ticket from months ago? A transcript is not an audit trail.

• How do you defend against prompt injection? OWASP notes that it is "unclear if there are fool-proof methods of prevention for prompt injection", so ask how the agent's reach is limited when it is manipulated (OWASP LLM01).

• Which risk framework do you map to? The NIST AI Risk Management Framework, released on 26 January 2023, is voluntary but a common reference for compliance teams (NIST AI RMF).

• Who edits a workflow six months after launch, and how long does it take?

What still needs a human?

None of these tools removes the need for people on the hardest work. Keep humans on judgement calls such as hardship, complaints with regulatory weight, fraud disputes and anything clinical. The CFPB warns that financial institutions "risk violating legal obligations, eroding customer trust, and causing consumer harm when deploying chatbot technology", and that chatbots must comply with the same consumer financial laws as the processes they replace (CFPB). Design escalation paths first: the agent should hand over with context when a customer asks for a person, when it fails to progress, or when policy says a human decides. Compliance sign-off on new workflows should stay with your compliance team, whichever vendor you choose. Teams in high-compliance sectors can read our Sierra alternatives for high-compliance teams.

If your queue fits the complex, action-heavy profile above, you can start a 30-day Lorikeet free trial and replay your own tickets before deciding.