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Sierra vs Fin
A plain-English comparison to help you choose between them.
Both platforms measure themselves on resolutions completed rather than conversations deflected, so this is a decision about shape. Pick Sierra when a large support operation wants one governed agent owning resolution across chat, voice and messaging channels, bought through a sales conversation and priced by outcome. Pick Fin when support already runs on Intercom or another helpdesk and an agent layered over it, paying per resolution, is the faster path. Sierra is a platform decision; Fin is an addition to the stack you have.
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Side by side
- Summary
Sierra is an enterprise AI agent platform for customer service, founded by Bret Taylor and Clay Bavor. One agent resolves conversations end to end rather than deflecting them, deployed across chat, voice, SMS, WhatsApp, email and a ChatGPT channel, with governance and guardrails built in. Ghostwriter turns procedures and transcripts into production-ready agents, Agent Studio manages them, Insights watches conversation quality, and Experiments runs multivariate tests of agent behaviour.
The commercial shape is strictly enterprise: pricing is outcome-based, so you pay for the resolutions the platform delivers rather than for seats, and there is no public rate card. It raised a major funding round in 2026, and it suits large support operations ready to hand real conversation volume to AI agents under supervision.
- Best for
- Resolving customer conversations end to end across chat and voice
- One governed agent deployed across chat, SMS, WhatsApp, email, voice and ChatGPT
- Building production agents from plain-English descriptions with Ghostwriter
- Enterprise support operations with serious conversation volume
- Paying for resolutions delivered rather than seats
- Cost
- Enterprise
- Ease
- Openness
- Hosted service
- Data
- Customer conversations and connected customer records flow through a closed platform. The Agent Data Platform holds agent memory and integrations into your customer systems, so procurement should treat it as a core data processor. Deployments reportedly handle regulated interactions such as insurance claims and financial services conversations, where AI agent outputs need human oversight and audit trails, automated customer decisions may trigger consumer-protection and disclosure obligations, and the platform does not substitute for compliance review of agent behaviour.
- Summary
Fin, formerly Intercom, is an autonomous support agent that resolves customer conversations end to end: grounded in your help content, working across chat and email, and priced by outcome rather than seat, so you pay per resolution it actually completes. It layers over existing helpdesks rather than demanding a migration.
The operating loop is the product: simulate answer quality before customers see it, deploy on routine volume, escalate the rest to humans with full context attached, and mine unresolved questions for the content gaps behind them.
MoreLess
Fin publishes an average resolution rate of 76 per cent across its customers; definitions of resolution vary across the market, so the honest baseline for staffing and economics is a trial on your own volume rather than any vendor's headline figure.
- Best for
- Autonomous end-to-end resolution of routine conversations
- Outcome pricing: pay per resolution, not per seat
- Layering over an existing helpdesk without migration
- Escalation to humans with full context attached
- Mining unresolved cases for missing help content
- Cost
- Paid only
- Ease
- Openness
- Hosted service
- Data
- Fin answers from your help content and past conversations under Fin's commercial terms. One strategic note: Salesforce has agreed to acquire the company, with Fin expected to fold into its Agentforce line, which is worth weighing in any long-term platform decision.
Pricing
- Sierra
- No published price
- Fin
Custom·Custom
Prices as of August 2026.
- Fin with your current helpdesk
- Price on application
- Fin with the Intercom helpdesk
- Price on application
By area
Where each one pulls ahead, area by area.
| Area | Sierra | Fin |
|---|---|---|
| By job | ||
| Customer support | Sierra is the standalone agent platform built to own resolution across chat and voice under brand-level governance and testing | Fin makes the operating loop the product: simulate, deploy on routine volume, escalate the rest with the full conversation attached, then mine the unresolved questions for the content gaps behind them |
| By task | ||
| Customer support & chatbots | Sierra measures itself on conversations completed rather than deflected and carries the same governed agent into phone-based voice | Fin decouples the bot decision from the helpdesk decision, running as the AI layer over Zendesk, Salesforce or HubSpot with no migration, and it simulates answer quality on real past conversations before a customer sees one |
Common questions
Can a smaller team trial either platform easily?
Fin is the more approachable buy: it is a paid product that layers over an existing helpdesk without migration, though outcome pricing means costs scale with volume resolved and forecasting takes modelling rather than a price list. Sierra is strictly enterprise: sales-led, outcome-based, with no public rate card, so smaller teams wanting to trial a bot this afternoon are outside its shape.
Which support channels does each agent cover?
Sierra deploys one governed agent across chat, voice, SMS, WhatsApp, email and a ChatGPT channel, and carrying the same agent into phone-based voice is a large part of its pitch. Fin works across chat and email, grounded in your help content. If telephone support must be part of the AI programme, that difference alone may decide the shortlist.
How much of our support volume will these agents resolve?
Fin's own reporting puts average resolution at 76 per cent across its customers, though definitions of resolution vary by vendor, and its operating loop assumes the remainder escalates to humans with context attached while unresolved cases are mined for content gaps. Fin's answer quality rides on your help content, and Sierra builds agents from your procedures and transcripts. Where deployments touch regulated interactions such as insurance or financial services, human oversight and audit trails remain necessary.
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Tool facts last checked August 2026