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Ada vs Fin
A plain-English comparison to help you choose between them.
Two meters for the same promise. Ada prices per conversation its agents handle, attempts whether or not the customer walks away satisfied, with the rate quoted through sales; Fin prices per resolution it completes, publishes an average resolution rate of 76 per cent across customers, and layers over your existing helpdesk rather than standing alone. The pending Salesforce acquisition of Fin's company, noted in the catalogue's own record, belongs in any long-term comparison. Pick Ada when platform depth and a mature operational workspace matter more than the meter; pick Fin when paying only for resolved outcomes fits your risk appetite and the helpdesk you run today.
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Side by side
- Summary
Ada is an enterprise customer-service automation platform, describing its current generation as agentic: AI agents that resolve complex, multi-step requests rather than answering FAQs, which its own marketing explicitly distinguishes from the chatbot era it came from. The platform covers building, testing, measuring and improving those agents across channels.
Pricing is published as a shape rather than a number: Ada charges per conversation, and publishes no rate card. Its site carries automated-resolution figures for itself and named customers; these are the vendor's own numbers and belong in an evaluation as claims to verify.
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It suits organisations that want mature customer-service automation with the operational tooling around it, bought through a sales process.
- Best for
- AI agents resolving multi-step service requests
- Conversation-based pricing, published as a shape rather than a rate card
- Building, testing and measuring agents in one platform
- Organisations graduating from chatbot-era automation
- Service automation bought and scoped through sales
- Cost
- Enterprise
- Ease
- Openness
- Hosted service
- Data
- Customer conversations flow through Ada's platform under enterprise agreements; agree retention, residency and escalation-transcript handling as part of procurement rather than assuming defaults.
- 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.
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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
- Ada
- 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 | Ada | Fin |
|---|---|---|
| By job | ||
| Customer support | Ada's substance is operational: agents built from your content, tested before exposure, then measured and improved, which is the work that decides whether automation holds up | Fin's pending Salesforce acquisition belongs in any long-term platform decision taken about it |
| By task | ||
| Customer support & chatbots | Ada treats published performance numbers as the vendor's own claims rather than as measurements | Fin states its baseline plainly: real-world resolution settles well under half of volume for most teams, so humans remain the majority channel |
Common questions
Attempts or outcomes: which meter is actually cheaper?
It depends entirely on resolution rate at your volume. Per-conversation pricing charges every attempt, so high resolution makes it efficient and low resolution expensive. Per-resolution pricing shifts that risk to the vendor and costs more per success. Model both against a realistic forecast before believing either answer.
How does the definition of resolved affect Fin's model?
Materially, and the market defines it inconsistently, which the catalogue's Fin entry notes plainly. A resolution counted generously inflates both the published average and your bill. Agreeing the definition contractually, and testing it in a trial on your own conversations, is the diligence this pricing model demands.
What does the Salesforce situation mean for this choice?
The catalogue's record, verified in August 2026, notes an agreed acquisition with Fin expected to fold into Salesforce's Agentforce line. That is context rather than a verdict: it may strengthen the product's resourcing or reshape its roadmap. Long-term contracts deserve direct answers from sales either way.
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Tool facts last checked August 2026