Decagon and Sierra will both quote you a polished demo and a clean resolution rate. Your privacy officer will ask a different question: what happened to the protected health information on the ticket the agent handed back. In healthtech, that ticket is the one that matters.
Decagon and Sierra alternatives for healthtech are AI customer support platforms that resolve patient and member tickets end-to-end while meeting the obligations a healthtech team carries: BAA-ready HIPAA handling, PII and PHI redaction, documented security posture, regulated-grade guardrails, and an audit trail a privacy and compliance team can replay. Decagon and Sierra are both credible enterprise agents, but healthtech teams routinely shortlist alternatives once a HIPAA review, not deflection rate, becomes the deciding criterion. In 2026 the leading options resolve a large share of sensitive volume autonomously and price per outcome rather than per seat.
The first filter for healthtech support is not resolution rate. It is whether a vendor will sign a BAA, redact protected health information, prove what its agent did on every ticket, and pass the same review a privacy officer or auditor would run.
Both Decagon and Sierra lean on outcome-based or per-conversation billing, which aligns incentives but can pull any vendor toward the easy tickets and away from the sensitive ones (eligibility, prior authorization, a benefits dispute) that carry the real risk.
Gartner predicts 80% of common customer service issues will be resolved autonomously by 2029, up from low double-digits in 2024.
Regulated-grade guardrails (PHI redaction, scripted disclosures, no-medical-advice boundaries, escalation triggers, and behavior that is provable before launch) now separate genuine healthtech tools from chat-only deflection.
Multi-step action chains (verify identity, check eligibility or coverage, update the system of record, draft a compliant message, coordinate with a pharmacy or payer, escalate when blocked) are what a healthtech ticket actually needs, in the right order, with state preserved across steps.
Last updated: June 2026
Healthtech support has a different failure mode than e-commerce or SaaS. A patient asking why a claim was denied, a member trying to confirm coverage before a procedure, or someone updating a dependent on a plan is not a churn-risk ticket. It is a ticket where the wrong answer can expose protected health information, give clinical guidance the platform was never cleared to give, or trigger a HIPAA complaint. Most vendors lead with a resolution rate of 70 to 90 percent. For a healthtech business that number alone is a vanity metric: you can reach it by handling routine tickets and mishandling the one case that draws an auditor. This guide is a buyer-neutral look at the alternatives healthtech teams shortlist when they evaluate Decagon and Sierra, judged on shipping product, regulated depth, and what a security and privacy team will actually approve. Decagon and Sierra are treated fairly throughout: both are strong products, and the goal here is fit, not a takedown.
Why Healthtech Teams Evaluate Decagon and Sierra Alternatives
Decagon and Sierra are both capable enterprise AI agents. Sierra, founded by Bret Taylor and Clay Bavor, scaled quickly and built a strong enterprise procurement story around outcome-based pricing, where customers pay only when the agent fully resolves a case and escalations cost nothing. Decagon is a well-funded enterprise agent with a polished product, strong analytics, and per-conversation or per-resolution options across voice, chat, and email. For a large enterprise that wants a refined general-purpose agent, either is a reasonable default. The reasons healthtech teams evaluate alternatives are specific to regulated healthcare work, not a knock on either product.
The first reason is the incentive structure. Outcome-only and per-conversation pricing are attractive on paper, but a vendor paid mainly on clean resolution has a structural reason to optimize toward tickets that resolve easily and away from the ambiguous, sensitive ones that escalate. In healthtech, the hard tickets (a denied claim, an eligibility edge case, an account takeover on a member portal) are exactly the ones that carry regulatory weight, so a pricing model that quietly deprioritizes them is worth examining closely.
The second is depth of provable controls. Healthtech buyers increasingly evaluate on whether a vendor will sign a business associate agreement, redact PHI in transit and at rest, demonstrate guardrail behavior before go-live, log every tool call and reasoning step for later examination, and pass a formal security review. A branded persona or a polished analytics dashboard does not answer those questions on its own. The third is breadth of channel and workflow control: healthtech teams often need voice, chat, email, SMS, and outbound on one engine, plus deterministic workflows for scripted disclosures, no-medical-advice boundaries, and approval gates, not only natural-language reasoning. The alternatives below each address one or more of these gaps.
At-a-Glance Comparison
At a glance
Platform: Lorikeet · Best For: Healthtech, fintech, insurance, and other regulated teams where a privacy or compliance officer is the toughest stakeholder · Key Strength: BAA-ready HIPAA handling, defence-in-depth guardrails with simulation testing before launch, replayable audit trails, deterministic plus natural-language workflows, sub-1-second voice, and 100% automated QA · Pricing: Outcome-based: about $0.80–$0.95 per chat, email, or SMS resolution and about $1.20–$1.50 per voice; Coach QA about $0.25–$0.30 per ticket; escalations not charged
Platform: Fin by Intercom · Best For: Intercom helpdesk customers wanting drop-in AI for general support · Key Strength: Lowest published per-outcome price; fast trial; works on Intercom plus Salesforce and HubSpot · Pricing: $0.99 per resolution, plus a helpdesk seat fee
Platform: Ada · Best For: Mid-market teams with high chat volume and lighter regulatory load · Key Strength: Mature automation platform with a high claimed autonomous resolution rate · Pricing: Custom; reported near $70K median annual contract
Platform: Salesforce Agentforce · Best For: Enterprises standardized on Salesforce data and Health Cloud · Key Strength: Native to the Salesforce platform and data model; coexists alongside specialist agents · Pricing: Per-conversation, around $2 per conversation, plus platform costs
Platform: Gradient Labs · Best For: Regulated fintechs and adjacent regulated teams in the UK and Europe wanting an autonomous agent · Key Strength: Compliance-aware autonomous agent with a strong regulated focus and outcome alignment · Pricing: Custom; outcome-aligned
Platform: Cognigy · Best For: Contact centers needing enterprise voice and IVR-grade routing · Key Strength: Strong enterprise voice and conversational IVR with broad telephony integration · Pricing: Custom enterprise contracts
Platform: Forethought · Best For: Support teams wanting AI triage, routing, and resolution layered on an existing helpdesk · Key Strength: Ticket triage, routing, and knowledge-based resolution with helpdesk-native integration · Pricing: Custom; tiered by volume
The 7 Best Decagon and Sierra Alternatives for Healthtech in 2026
1. Lorikeet
Lorikeet is the AI customer support platform built for complex, regulated companies, with healthcare and healthtech as core verticals alongside fintech, financial services, insurance, and gaming. It builds AI concierges that resolve multi-step tickets end-to-end across voice, chat, email, SMS, and WhatsApp, and it is designed so a privacy and compliance team can sign off before launch rather than review after the fact. Where an outcome-billed general agent is tuned to resolve cleanly and hand back the rest, Lorikeet is tuned for the sensitive tickets that carry the most risk and the most scrutiny.
Key Features
Defence in depth as the core design: pre-launch adversarial simulations and red-teaming, inbound message checks, outbound guardrails, and 100% post-facto QA through the Coach agent. The intent is provable behavior before go-live, not a runtime promise.
Compliance-grade audit trail: every tool call, prompt, and reasoning step is logged and replayable, which is the artifact a privacy team or auditor reviews when they ask what the agent actually did on a given ticket.
Multi-step action chains across systems of record: verify identity, check eligibility or coverage, update the CRM or core system, draft a compliant message, coordinate a third party such as a pharmacy or payer through a team-of-agents pattern, and escalate when blocked, in the right order with state preserved across steps.
Deterministic structured workflows and natural-language workflows that combine in one interaction, configured in plain English, so scripted disclosures, no-medical-advice boundaries, and approval gates run reliably rather than being left to model discretion.
Omnichannel on one engine: chat, email, SMS, and WhatsApp plus native voice at sub-1-second latency, with outbound re-engagement (appointment reminders, abandonment) under consent, do-not-contact, and call-hour controls.
Documented security and compliance posture to support your obligations: SOC 2, BAA-ready HIPAA handling, GDPR alignment, PII and PHI redaction, role-based access control, data residency in the US, UK, and Australia, and contractual no-train agreements with model providers.
Ideal For
Healthtech platforms, digital health and telehealth providers, payers, and benefits teams handling workflows (eligibility checks, prior authorization status, claims questions, account and plan changes) where every action needs an audit trail and a compliance-approvable answer. Lorikeet's customer base skews to regulated companies, and the platform has passed security reviews including those of major US banks, a useful proxy for the bar a regulated procurement and security team will hold any vendor to. In published results, a regulated customer reached roughly 85% automation with equal-or-better CSAT, the kind of depth-on-hard-tickets outcome healthtech teams should ask any vendor to demonstrate on their own data and their own hardest tickets.
A Limitation to Weigh
Lorikeet is deliberately specialized. If your support is mostly simple FAQ deflection with no regulated workflows, no sensitive data handling, and no need for action chains or guardrail testing, a lighter general-purpose tool will be faster and cheaper to stand up. Lorikeet also runs a forward-deployed model with a hands-on launch (a sandbox in 20 to 30 minutes, operational in about a month), which is more involved than a pure self-serve switch-on and assumes you have a regulated use case worth that depth.
Pricing
Outcome-based and anti-deflection: about $0.80–$0.95 per chat, email, or SMS resolution and about $1.20–$1.50 per voice resolution, with the Coach QA agent at about $0.25–$0.30 per ticket. The customer defines what counts as a resolution and escalations are not charged, which removes the incentive to claim easy wins. Against a human baseline of roughly $1.25 to $4 per handled ticket, the per-resolution model is built to be honest about the hard tickets rather than rewarding the easy ones.
2. Fin by Intercom
Fin by Intercom is a strong general-purpose AI agent with the lowest published per-outcome price in the category. It ships with a fast trial and works on top of Intercom's messenger and helpdesk as well as Salesforce and HubSpot. For a high-volume healthtech team that already lives in Intercom and handles mostly general support, it is a reasonable default and a genuine alternative to Decagon and Sierra on cost.
Key Features
Pure outcome-based pricing at the category's lowest published rate.
Fast self-serve trial and quick time to first value.
Native to Intercom messenger and helpdesk, with Salesforce and HubSpot connectors.
Strong general-purpose resolution on knowledge-base and routine action tickets.
Ideal For
Intercom helpdesk customers and high-volume healthtech teams handling general support who want a drop-in agent at a low per-outcome price. Most healthtech buyers shortlist alternatives when PHI handling, a signed BAA, deeper audit trails, and provable pre-launch guardrails enter the picture, so confirm those before routing sensitive patient or member traffic through it.
Pricing
$0.99 per resolution, typically on top of an Intercom helpdesk seat fee.
3. Ada
Ada is a mature automation platform with a high claimed autonomous resolution rate and a long track record in mid-market and enterprise support. It is a credible alternative to Decagon and Sierra for healthtech teams with high chat volume and a lighter regulatory load who want a proven, configurable automation layer.
Key Features
Established automation platform with a large customer base.
High claimed autonomous resolution rate on suitable ticket types.
Flexible configuration and a no-code builder.
Multi-channel coverage for chat and messaging.
Ideal For
Mid-market and enterprise healthtech teams with high chat volume and lighter compliance requirements. More heavily regulated buyers should confirm BAA coverage, PHI redaction, audit depth, data-residency options, and pre-launch guardrail testing, since Ada is positioned for breadth of automation rather than regulated healthcare specialization.
Pricing
Not published. Enterprise contracts are reported near a $70K median annual spend.
4. Salesforce Agentforce
Salesforce Agentforce is Salesforce's native agent layer, built directly on the Salesforce platform and data model, including Health Cloud where it is in use. For healthtech enterprises already standardized on Salesforce, it removes integration friction and inherits the platform's governance. Lorikeet coexists alongside Agentforce in many deployments, so this is often a complement rather than a strict either-or choice.
Key Features
Native access to Salesforce CRM and Health Cloud data and the surrounding platform.
Inherits Salesforce platform governance, permissions, and tooling.
Per-conversation pricing that fits existing Salesforce procurement.
Designed to coexist with specialist agents on adjacent workflows.
Ideal For
Healthtech enterprises whose support data and CRM already live in Salesforce and who want an agent native to that ecosystem. Regulated teams should evaluate guardrail testing, audit-trail replay, PHI handling, and channel depth, particularly voice, against the specialized alternatives in this list.
Pricing
Per-conversation, reported around $2 per conversation, on top of underlying Salesforce platform costs.
5. Gradient Labs
Gradient Labs is a London-based AI support agent with an explicit focus on regulated industries, fintech first. It positions around autonomous resolution with attention to the controls regulated teams care about, which makes it a natural Decagon and Sierra alternative for UK and European buyers who want compliance awareness built in rather than bolted on.
Key Features
Autonomous agent designed for regulated support workflows.
Compliance-aware design oriented to UK and European regulatory expectations.
Outcome-aligned commercial model.
Focused product scope rather than broad horizontal coverage.
Ideal For
Regulated teams in the UK and Europe that want an autonomous agent built with compliance in mind. As a younger company with a fintech-first focus, healthtech buyers should confirm BAA-ready HIPAA handling, channel breadth (especially voice), and the depth of audit and guardrail tooling against their requirements.
Pricing
Not published. Outcome-aligned and quoted per engagement.
6. Cognigy
Cognigy is an enterprise conversational AI platform with particular strength in voice and IVR-grade routing for contact centers. It integrates broadly with telephony stacks and is a reasonable Decagon and Sierra alternative for healthtech organizations whose primary need is enterprise voice automation with structured routing rather than action-heavy regulated resolution.
Key Features
Strong enterprise voice and conversational IVR capabilities.
Broad telephony and contact-center integration.
Visual flow builder for structured conversation design.
Established presence in large enterprise contact centers.
Ideal For
Healthtech contact centers that need enterprise-grade voice and IVR routing at scale. Teams whose priority is autonomous resolution of complex regulated tickets with deep audit trails and PHI controls should weigh this against the more resolution-focused agents above.
Pricing
Not published. Custom enterprise contracts.
7. Forethought
Forethought is an AI support platform built around ticket triage, routing, and knowledge-based resolution layered on an existing helpdesk. It is a credible Decagon and Sierra alternative for healthtech teams that want to add AI deflection and intelligent routing to a helpdesk they already run, rather than replacing the support stack outright.
Key Features
AI triage and intent classification for incoming tickets.
Intelligent routing to the right queue or agent.
Knowledge-based resolution and suggested replies.
Helpdesk-native integration with common ticketing systems.
Ideal For
Healthtech teams that want AI triage, routing, and deflection on top of an existing helpdesk rather than a full action-chain resolution engine. Buyers handling sensitive patient or member workflows should confirm BAA coverage, PHI redaction, audit-trail depth, and how far the agent can act across systems of record versus surfacing suggested answers.
Pricing
Not published. Custom contracts tiered by volume.
How to Choose a Decagon or Sierra Alternative for Healthtech
BAA, PHI Redaction, and a Documented Posture
Before any agent touches patient or member data, your security and privacy team will want a documented posture: SOC 2, a business associate agreement the vendor will actually sign, PHI and PII redaction in transit and at rest, role-based access control, and data residency in the regions you operate. Equally important are contractual no-train agreements with the model providers, so your patient data is not used to train third-party models. Confirm these in writing rather than accepting a marketing claim, and remember these features support your obligations rather than discharging them.
Provable Guardrails Before Go-Live
In healthtech support the most important question is what happens on the bad paths, not the happy path. Ask whether the vendor can demonstrate guardrail behavior before launch through adversarial simulation and red-teaming, run inbound message checks and outbound guardrails at runtime, enforce no-medical-advice boundaries, and require human approval on sensitive cases. A vendor that can only show you the demo path, not the failure paths, has not answered the compliance question. Lorikeet treats this defence-in-depth chain as the core of the product.
Audit Trail Depth
A transcript is not an audit trail. The artifact a privacy team needs is a timestamped, replayable record of every tool call, prompt, and reasoning step the agent took on a given ticket, so they can reconstruct exactly what happened during an audit or dispute. Ask each vendor to show you a real replay, not a summary, and confirm how long the trail is retained. This is where outcome-billed general agents and triage-first tools tend to be thinnest.
Multi-Step Action Chains
Healthtech tickets are rarely a single question. Resolving one usually means verifying identity, checking eligibility or coverage, updating a system of record, drafting a compliant message, coordinating with a pharmacy or payer, and escalating when blocked, all in the right order with state preserved across steps. Confirm the agent can chain real actions across your CRM, core systems, and ticketing, rather than retrieving an answer and replying. A team-of-agents pattern that can coordinate third parties is a strong signal of genuine action depth.
Channel Breadth on One Engine
Healthtech teams increasingly need chat, email, SMS, WhatsApp, and voice on a single engine with shared context, plus outbound re-engagement under consent and call-hour rules. Sub-1-second voice latency matters when a patient is on the phone about a denied claim. Ask whether voice runs on the same workflow and guardrail engine as the other channels, or whether it is a separate, less-governed product bolted on.
Questions to Ask Your Vendor
Will you sign a BAA, and how do you redact PHI in transit and at rest?
Can you show me a full replayable audit trail for a single complex ticket, including every tool call and reasoning step?
How do you prove guardrail behavior before go-live, including no-medical-advice boundaries, and can I see the failure paths rather than only the demo path?
On an outcome-only or per-conversation model, what stops the agent from optimizing toward easy tickets and escalating the hard sensitive ones?
Does voice run on the same workflow and guardrail engine as chat, email, and SMS, with shared context?
Will you run my hardest tickets in my own stack, against my guardrails, before I sign?
Lorikeet's Take on Decagon and Sierra Alternatives for Healthtech
Decagon and Sierra are both strong enterprise agents, and outcome-based billing is a genuinely good idea for many businesses. The reason healthtech teams keep building shortlists is not that either is weak; it is that horizontal enterprise design and outcome or per-conversation pricing answer the procurement question better than they answer the HIPAA question. In healthtech the decision turns on a signed BAA, PHI redaction, provable controls, replayable audit trails, and depth on the hard tickets, and those are exactly the dimensions a billing model and a polished demo cannot settle on their own.
We built Lorikeet for the case where a privacy or compliance officer is the toughest stakeholder in the room. That means BAA-ready HIPAA handling, defence in depth before launch, an audit trail your team and your auditors can replay, deterministic plus natural-language workflows for scripted disclosures and no-medical-advice boundaries, omnichannel including sub-1-second voice, and 100% automated QA through Coach. We charge per resolution, let the customer define what counts, and never bill escalations, so the pricing rewards getting the hard tickets right rather than skimming the easy ones. If your support is simple and unregulated, a lighter tool will serve you faster, and we will say so. If it is not, the right test is simple: bring your hardest tickets and run them against the guardrails before you sign anything.
Key Takeaways
For healthtech support, the deciding criterion is a signed BAA, PHI redaction, provable controls, and replayable audit trails, not resolution rate or a polished demo.
Decagon and Sierra are both credible enterprise agents, but their outcome and per-conversation pricing can structurally favor easy tickets over the sensitive ones that carry the most risk.
The seven alternatives split by fit: Lorikeet for compliance-first healthtech teams, Fin by Intercom for low-cost general support, Ada for high-volume automation, Salesforce Agentforce for Salesforce-native enterprises, Gradient Labs for UK and European regulated teams, Cognigy for enterprise voice and IVR, and Forethought for AI triage and routing on an existing helpdesk.
Lorikeet differentiates on BAA-ready HIPAA handling, defence in depth (simulation testing, message checks, outbound guardrails, 100% QA), replayable audit trails, deterministic plus natural-language workflows, and omnichannel including sub-1-second voice.
Gartner predicts 80% of common customer service issues will be autonomously resolved by 2029, but in healthtech the bar is correctness and privacy on the hard tickets, not volume on the easy ones.
Conclusion
The healthtech support market in 2026 is not a question of whether to deploy AI. It is a question of which platform survives a security and HIPAA review and resolves the sensitive tickets that matter, with audit trails your team and your auditors trust. Decagon, Sierra, and the seven alternatives above each lead a different segment, and the right choice depends on your existing stack, your regulatory load, and how much of your volume is genuinely sensitive.
Lorikeet is the answer for healthtech teams whose privacy or compliance officer is the toughest stakeholder in procurement, who need multi-step action chains across voice, chat, email, and SMS, and who want their agent's behavior provable before go-live. The other six are credible alternatives depending on budget, helpdesk, and risk profile, and Decagon and Sierra remain strong options for enterprises that primarily want a polished general-purpose agent with outcome-aligned billing.
If you are evaluating Decagon and Sierra alternatives for healthtech, book a Lorikeet demo and bring your hardest 10 tickets. We will run them in your stack against your guardrails before you sign.
