Best AI customer support tools
Best AI stack for customer support, ranked by effect on the work, with the risk read beside each one.

TL;DR
- 01Choose one primary AI agent for routine questions before adding another overlapping agent.
- 02Keep ticket routing, escalation and the customer record in a system the support team already owns.
- 03Judge the stack on resolution time, first-contact resolution and the quality of handoffs to people.
- 04Review knowledge sources, customer-data access and account actions before allowing broader automation.
We picked these tools for customer support leaders to answer customers, complete support actions, and keep service records.
The stack at a glance
| # | Tool | Level | Grade | Trains on your data |
|---|---|---|---|---|
| 1 | Workflow tools | A+ | Free: No, Paid: Yes | |
| 2 | Systems of record | A | Yes, with opt-out | |
| 3 | Workflow tools | A- | No training on user data | |
| 4 | Workflow tools | A+ | No training on user data | |
| 5 | Workflow tools | B | Yes | |
| 6 | Systems of record | A+ | No training on user data | |
| 7 | Systems of record | A | No training on user data |
Oximy grade and training readings are shown on the assessment date. We do not show prices: vendor pricing is mostly quote-only, and we print a number only with a source and a date.
The recommended tools
In rank order. Named customers come from the vendor's own published stories, which we opened and checked. They show the tool is used for that job, not that it worked.
Fin answers customer questions and hands unresolved conversations to support staff.
What it should move: fin resolves more questions at first contact and reduces resolution time.
Best fit
The catch
Fin reads help content and customer conversations. Poor source material weakens answers, and the tool depends on Intercom.
Zendesk AI agents resolve common requests and route remaining tickets to staff.
What it should move: they resolve tickets sooner and handle common requests so staff have more capacity.
Best fit
The catch
The agents act on customer conversations and approved processes. Complex policies need clear escalation paths and regular answer reviews.
Sierra handles customer conversations and completes actions across business systems.
What it should move: it shortens resolution time and completes more requests without a handoff.
Best fit
- It fits teams ready to connect an agent to billing, account, and fulfilment processes.
- Rocket Mortgage uses Sierra for customer conversations about loans, rates, application status and payments.[5]
- Ramp uses Sierra to answer transaction questions and complete card, shipping and address support workflows.[6]
The catch
Sierra can change customer accounts. Teams must own permissions, action limits, and escalation rules.
Decagon handles support conversations and connects them to business workflows.
What it should move: it shortens resolution time and handles more requests without staff intervention.
Best fit
The catch
Decagon needs support content and system access. Test policy exceptions, handoffs, and actions that affect customer accounts.
Forethought classifies support requests and resolves routine questions across chat and email.
What it should move: it resolves more tickets without staff, routes requests more accurately, and reduces handling time.
Best fit
The catch
Forethought learns from tickets and help content. Find old classification errors and stale answers before rollout.
Salesforce stores opportunities and runs agents that engage leads and update records.
What it should move: it shortens lead response and records more sales work in the CRM.
Best fit
The catch
Agent pricing depends on usage and excludes seats. Estimate agent usage before wider use.
Gainsight stores customer health, engagement, success plans, and lifecycle actions.
What it should move: teams address account risks sooner, help customers use self-service, and prepare for renewals.
Best fit
The catch
Customer health records depend on accurate product, support, and commercial data. Conflicting sources increase setup and maintenance work.
Where to start
Customers ask the same questions
Start with one agent using maintained help content, then measure how many questions it resolves without a handoff.
Requests need account actions
Choose an agent that can use the required systems, then restrict its actions and define exceptions before rollout.
Tickets reach the wrong team
Fix categories and ownership in the support record before adding another conversational tool.
Service affects renewals
Keep customer health and success actions beside the support queue, with one owner for each risk.
Questions
References
- 01Lightspeed Commerce: how it uses Intercom FinIntercomVendor-published
- 02Hospitable: how it uses Intercom FinIntercomVendor-published
- 03BritBox: how it uses Zendesk AI agentsZendeskVendor-published
- 04Best Egg: how it uses Zendesk AI agentsZendeskVendor-published
- 05Rocket Mortgage: how it uses SierraSierraVendor-published
- 06Ramp: how it uses SierraSierraVendor-published
- 07Duolingo: how it uses DecagonDecagonVendor-published
- 08Substack: how it uses DecagonDecagonVendor-published
- 09Fetch: how it uses ForethoughtForethoughtVendor-published
- 10Cotopaxi: how it uses ForethoughtForethoughtVendor-published
- 11Equinox: how it uses Salesforce with AgentforceSalesforceVendor-published
- 12Uber: how it uses Salesforce with AgentforceSalesforceVendor-published
- 13Oleeo: how it uses GainsightGainsightVendor-published
- 14Learnship: how it uses GainsightGainsightVendor-published