The 5 best AI tools to analyze support tickets in 2026
Short answer. For support teams that need to know whether a ticket is a known problem, who else hit it, and what engineering is doing about it, start with Modem, which we build. It groups tickets from Zendesk, Intercom, Plain, and Pylon with Slack and other reports into one topic per problem and links the Linear, Jira, or GitHub issue. For contact-driver and sentiment reporting, pick SentiSum or Chattermill. For themes across many feedback sources, pick Unwrap or Enterpret.
Every ticket tool claims AI in 2026, so "AI-powered" tells you nothing. What separates these five is what the AI hands back. Some produce tags, contact drivers, and sentiment for support leadership. Some produce themes and trends for CX and product teams. Modem produces one record per problem, with the customers behind it and the engineering work attached. Decide who reads the output before you compare features.
“we need SSO before rollout”
“any update on single sign-on?”
“SSO came up twice on this call”
Linear issue, quotes attached
insight report in NotionThe short version
| Tool | What the AI hands back | Primary audience | Where it doesn't fit | Pricing model |
|---|---|---|---|---|
| Modem | One topic per problem across tickets and other channels, with people, companies, linked issues, and drafted follow-ups | Support, product, and engineering | Agent QA scoring, deflection, staffing, CSAT and sentiment analytics | Free, Startup $80/mo, Scale $250/mo; unlimited seats |
| SentiSum | Ticket tags, contact drivers, sentiment, and what each issue costs | Support and CX leadership | Teams under about 1,000 tickets a month | By conversation volume |
| Chattermill | Themes and sentiment across tickets, surveys, reviews, and calls, with anomaly alerts | CX, insights, and product teams at enterprises | Small teams that only need ticket analysis | Custom, by feedback volume; no per-user fees |
| Unwrap | Themes ranked by volume and movement; SupportIQ reviews every support interaction | Product, CX, and support teams with high volume | Teams that need Slack as an input (not documented) | From $24,000 a year; unlimited seats |
| Enterpret | Adaptive three-level taxonomy, themes weighted by ARR, alerts | Product and insights teams | Teams that want issues created from findings (listed as coming soon) | Custom; no public price |
Competitor details come from each vendor's own site and docs, checked in October 2026. Plans and prices change, so confirm on the vendor's page before you buy.
1. Modem
Modem is an AI teammate for support and product teams at software companies that groups every report of the same problem across Zendesk, Intercom, Plain, Pylon, and Slack, shows which customers are affected, links the engineering issue, and drafts the follow-up when a teammate asks for it.
Modem reads tickets through native connectors for Zendesk, Intercom, Plain, Pylon, Front (a beta enabled per organization), and Jira Service Management, plus email forwarded to an inbound address. It reads Slack, Discord, Microsoft Teams, Gong and Fathom calls, GitHub issues, and Sentry user feedback alongside them. Instead of scoring each ticket, it groups conversations by meaning into topics and classifies each topic as a bug report, feature request, complaint, praise, or discussion. That output answers the questions support asks most often:
- Has this been reported before? A new ticket joins the topic that already holds earlier reports of the same problem, from any connected source. Ask
@Modemin Slack (members of your Modem organization only) or ask in the dashboard. - Who else hit this, and what do they pay? Each topic lists the people and companies behind it. With Stripe connected, matched customers' person and company pages show plan and subscription status, and the agent can tell you which paying customers reported a problem when you ask.
- What is engineering doing about it? Topics link to the Linear, Jira, GitLab, and GitHub issues and merged pull requests that cover them. When a teammate asks, or an automation your team built runs, the agent files a new issue; a Linear issue carries a summary, the affected companies, up to three quotes, and a link back to the topic.
- Who do we tell when it's fixed? An opt-in automation posts an internal Slack note naming who asked when a PR directly linked to the topic merges. When a teammate asks, the agent drafts a reply for each requester and can send it through Intercom or Pylon (after an admin turns on agent writes), Plain (within the API key's permissions), Slack, or Discord. In Slack and, by default, in the dashboard, each customer-facing write waits for approval. Modem has no reply path into Zendesk.
Each topic also gets an AI-assigned priority from very low to very high that reflects how much attention it needs, based on who is affected, how many customers and companies, whether it recurs, and whether it's already being handled. The topic list filters and sorts by priority, type, and lifecycle, and person and company pages show 25 weeks of message activity.
Why we built it this way. The same bug arrives in different words across a dozen channels, so a per-ticket tag never shows its real size, and finding everyone who reported it was almost entirely manual. Priority measures attention needed rather than how severe a message sounds, so an outage that's already handled ranks low and a quiet, unanswered customer complaint ranks high.
Where it doesn't fit: agent QA scoring, deflection, staffing, and CSAT or sentiment analytics. Modem stores no sentiment score (Complaint and Praise are topic types, and the agent can describe tone when asked), reads Intercom CSAT ratings as part of the conversation without computing a score, and has no report builder or CSV export button. It also has no ticket queue, SLAs, or assignment of its own; your helpdesk keeps those. SentiSum, Chattermill, and Unwrap's SupportIQ are built for the reporting side.
Pricing: Free ($0), Startup ($80/month), and Scale ($250/month), each with unlimited seats and a monthly allowance of events and agent credits, opt-in pay-as-you-go overage under a budget cap, and custom Enterprise plans. New Gong connections need the Scale plan or a trial. See Modem's pricing.
2. SentiSum
SentiSum calls itself AI-native CX intelligence software. It pulls in tickets, chats, calls, reviews, and surveys, tags them, and reports what is breaking and what it costs. It connects natively to Zendesk, Intercom, Freshdesk, Gorgias, Dixa, and Salesforce, sends alerts to Slack, and can route specific issues to Jira or Slack.
Pricing: by conversation volume and history, on SentiSum's pricing page. SentiSum aims it at teams handling more than about 1,000 support tickets a month.
Where it fits: support and CX leaders who want automated tagging and contact-driver reporting without asking agents to tag by hand.
3. Chattermill
Chattermill is a customer feedback analytics platform built for enterprises. It consolidates support tickets, surveys, app reviews, social posts, and call and chat transcripts, then runs aspect-based sentiment, clustering, and generative AI over them to surface themes, sentiment shifts, and anomalies. It connects natively to Zendesk, Intercom, Salesforce, and survey tools; alerts go to Slack, anomaly alerts can become Jira tickets, and an MCP server lets AI agents query the insights.
Pricing: custom, scaled to feedback volume and data sources, with no per-user fees. Chattermill doesn't publish a price list.
Where it fits: larger companies with a CX or insights function that reports on experience across many sources, tickets among them.
4. Unwrap
Unwrap groups feedback into themes it builds itself, without a hand-made taxonomy, and ranks them by volume and movement with sentiment per theme. Sources include Zendesk, Intercom, Freshdesk, Help Scout, Gong, GitHub Issues, and Discord. SupportIQ, its support product, evaluates every support interaction and tags outcomes. Linked Actions tie a theme to a Jira or Asana work item (Unwrap's blog adds Linear) and filter themes by that item's status, and Unwrap has offered a read-only MCP server since August 2026. Unwrap's Slack integration pushes alerts and digests; reading Slack as a source isn't documented.
Pricing: plans start at $24,000 a year with unlimited seats, per Unwrap's pricing page, with a 30-day trial on your own data.
Where it fits: teams with high ticket and review volume that want theme discovery without maintaining a taxonomy, and can sign an annual contract. See our Modem vs Unwrap comparison.
5. Enterpret
Enterpret connects more than 50 feedback sources, support tickets among them, and tags them with an adaptive three-level taxonomy. With account data synced (Salesforce is documented), themes can be filtered and weighted by ARR. It links themes to existing Jira and Linear issues and syncs their status back; creating new issues from Enterpret was listed as coming soon in its help center in October 2026. Its Wisdom MCP server gives AI tools read-only access.
Pricing: no public price list; Enterpret quotes by feedback volume, integrations, and team size.
Where it fits: high-volume companies with an insights team and many feedback channels. See our Modem vs Enterpret comparison.
How to choose
Name the reader of the AI's output first, then match:
| Who reads the output | What they need | Start with |
|---|---|---|
| Support agents and leads working tickets | Whether a ticket is a known problem, who else hit it, engineering status, a drafted follow-up | Modem |
| Support or CX leadership | Contact drivers, sentiment, cost of each issue | SentiSum |
| A CX or insights team | Themes and sentiment across tickets, surveys, reviews, and calls | Chattermill |
| Product teams with high volume | Ranked themes without a taxonomy, plus SupportIQ for support interactions | Unwrap |
| An insights team that reports by revenue | ARR-weighted themes across 50+ sources | Enterpret |
If you only need a label on every ticket and you already run Zendesk, try its built-in intelligent triage first. It classifies each new ticket by topic, sentiment, language, and entities and suggests new topics from your ticket data; check Zendesk's docs for which plans and add-ons you need.
Analyze tickets by hand before you buy
A month of tickets tells you which tool's output you need. You can do this with an export and a spreadsheet:
- Export 200 to 300 recent tickets with the requester's company and the first customer message.
- Sort by error text and product nouns, not the customer's wording. Customers describe the same bug differently; error strings and screen names repeat.
- Group duplicates into one row per problem and count tickets and distinct companies for each.
- Search your tracker for each of the top ten problems and note the Linear, Jira, or GitHub issue, or that none exists.
- Write down who to tell when each fix ships. If the issue lives in a public repo or project, keep customer names and private ticket links in an internal note instead.
If step 3 takes most of the time, you need grouping across tickets. If steps 4 and 5 are the gap, you need the tickets linked to engineering work. If the question your leaders ask is "what are customers upset about this quarter", you need driver and sentiment reporting. For turning grouped tickets into planned work, see tools to turn support tickets into product insights and how to close the feedback loop with customers. For one helpdesk in depth, see tools to mine feedback from Zendesk tickets.
FAQ
Can AI tell my support team which tickets are about the same bug?
Yes, with different scopes. Modem groups tickets with reports from Slack, Discord, email, and calls into one topic per problem. Unwrap and Enterpret group feedback into themes across their connected sources. Zendesk's intelligent triage classifies each ticket and suggests topics from your Zendesk data. Grouping is a model's judgment in every case, so check a sample of the groups by hand.
Which tool shows which customers are affected and what they pay?
Modem lists the people and companies behind each topic, and with Stripe connected it shows plan and subscription status on matched customers' person and company pages; the agent can join billing to topics when asked. Enterpret weights themes by ARR once account data is synced. Revenue doesn't set Modem's priority.
Do these tools measure CSAT or agent quality?
SentiSum and Chattermill report sentiment and drivers, and Unwrap's SupportIQ evaluates every support interaction. Modem reads Intercom CSAT ratings as part of the conversation but computes no CSAT, sentiment, or QA score.
Is Modem only for product and engineering teams?
No. Support uses Modem to check whether a ticket is a known problem, see which other customers hit it, check the linked engineering issue, and draft the follow-up, with the helpdesk still handling the queue. Product and engineering use the same topics to decide what to fix.