Intercom Fin vs Decagon (2026): AI Support Agents Compared

The short answer

• Choose Fin for nearly every team under enterprise scale, any team that wants to start this month, and anyone who wants to pay only for results without negotiating.
• Choose Decagon for enterprise support organizations with heavy voice volume, complex multi system workflows and the budget for a sales led deployment.

Pricing

Item	Intercom Fin	Decagon
Published price	$0.99 per outcome	None
Billing unit	Outcome: resolution, procedure handoff, disqualification, routing	Per conversation (default) or per resolution
Escalations	Request for a human not billed	Billed on per conversation contracts, free on per resolution
Voice	$1.99 per voice outcome, through sales	Included in quote
Seats	Inside Intercom $29 to $132 per seat annual; none standalone	Not seat based
Minimum	50 outcomes a month standalone ($49.50)	Contracted
Trial	14 days, unlimited outcomes	Demo

Worked example: 10,000 conversations a month, 65% resolved

• Fin standalone on your helpdesk: 6,500 outcomes at $0.99 = $6,435 a month, assuming the unresolved 35% are handoffs to humans that are not billed.
• Decagon per conversation: 10,000 x your quoted rate. To beat Fin, that rate must be under about $0.64 per conversation ($6,435 divided by 10,000).
• Decagon per resolution: 6,500 x your quoted resolution rate. To beat Fin, it must be under $0.99.

Use this break even math in your negotiation. More prices are on the AI Price Index and in Intercom Fin pricing.

One billing nuance cuts the other way: Intercom bills assumed resolutions, where a customer reads Fin's answer and leaves, unless Fin detects frustration. Decagon's pricing essay criticizes exactly that ("a user is upset, leaves, and that gets counted as a resolution"). On a weak knowledge base, Fin's outcome count can include silent failures.

Models and features

Feature	Intercom Fin	Decagon
Building	Procedures and workflows, simulations before launch	AOPs in natural language with Git versioning, simulations
Channels	Chat, email, WhatsApp, SMS, Slack, Instagram, Messenger, tickets; voice separately	Chat, email, voice, SMS
Languages	60+ languages and variants	70+ on voice
Models	Fin CX Model Suite, including Fin Apex 2.0, post trained on Fin production data, with multi provider failover	Third party LLMs with zero retention, own Chord speech model
Helpdesk	Full Intercom helpdesk, or standalone on others	None; integrates with Salesforce, Zendesk, Intercom, Kustomer
QA and testing	Simulations, reporting in Intercom	Simulations, live A/B experiments, Watchtower QA
Human assist	Copilot at $29 to $35 per agent	Decagon Assist
Uptime	99.8% SLA	Uptime SLAs, multi region

Head to head scenarios

Mid size SaaS company with 5,000 chats a month

Winner: Fin. Published pricing, a trial, a helpdesk if you want one and a large review base. Decagon targets bigger deployments.

Enterprise contact center moving phone traffic to AI

Winner: Decagon. Voice is core to its product, with its own speech model, 70+ languages, outbound calls and integrations with Amazon Connect, RingCentral and SIP trunks. Fin Voice is sold through sales at $1.99 per outcome.

Team already on Zendesk that wants better AI

Winner: Fin. Standalone Fin on Zendesk has no seat fees and a $49.50 monthly minimum. Decagon also integrates with Zendesk, but only through an enterprise contract.

CX team that rewrites policies weekly

Winner: Decagon. AOPs let support staff edit workflows in plain language, with engineers reviewing versions in Git and full reasoning traces.

Strict procurement and AI governance review

Winner: Fin. It lists SOC 2 Type II, HIPAA, ISO 27001, 27018, 27701 and 42001 and AIUC-1 for Fin itself, with self serve documentation. Decagon shows SOC 2, HIPAA, PCI, GDPR, CCPA and ISO badges, with reports through its trust center.

Privacy

Intercom says Fin trains only on your approved knowledge and procedures, can use anonymized customer data for fine tuning unless you opt out (with deletion within 30 days), and contractually bars third party AI providers from training on your data, with zero retention once a response is generated.

Decagon enforces zero data retention with LLM providers such as OpenAI and Anthropic, redacts PII with Google DLP after each conversation, uses short lived scoped tokens for system access and runs a supervisor model to catch hallucinations.

Decagon's default is stricter on training, since it does not describe any fine tuning on customer data. Fin's certification list is longer.

Verdict

Fin wins for most buyers: a public $0.99 per outcome price, free human handoffs, a trial, a choice of helpdesk and the strongest certification list we found. Decagon wins for enterprise support teams with heavy voice and complex workflows that CX staff need to own, and it has a cleaner stance on model training. Ask Decagon for a quote and hold it to the break even rates above. See also Intercom Fin vs Sierra and the Decagon review.