Turn every conversation into findings
Synthight reads every ticket, chat and email, finds each problem, request and compliment inside it, and groups them by topic so you can see which ones come up most.
Overview
Conversation volume is usually reported as a number: tickets opened, chats handled, first response time. None of that says what customers were actually saying, which is the only part product and engineering can act on.
A single conversation rarely says one thing. It can hold a complaint about a wait, a billing question, a request and a compliment, and a tag forces someone to pick one and lose the rest. Synthight splits every conversation into findings instead: each one a single, specific signal, typed as an issue, friction, opportunity or praise, and linked to the exact message and customer it came from.
Every finding is labeled with its topic. Topics are grouped by meaning, not by keyword, so "I was charged twice", "the payment went through two times" and "why do I have two charges?" land on the same one, and nobody has to maintain a taxonomy. New topics appear on their own when a new issue starts, and each one carries its volume, trend, sentiment and resolution rate.
The output is a ranked list your team can argue with: the top topics this month, how fast each is growing, how often each gets resolved, and one click to the findings and conversations behind every number.
It starts with the conversations already in your helpdesk: support tickets, live chats and email threads. The analysis itself is channel-agnostic, so every new source lands in the same findings and the same topics, and nothing has to be re-learned when a channel is added.
What you get
Every conversation, not a sample
Quality programs review 2% of conversations. Synthight reads 100% of them, which is the difference between an anecdote and a count.
Several findings per conversation
One conversation can yield several independent findings, so a compliment about your team never drowns out the complaint in the same message.
Typed automatically
Every finding is classified as an issue (something broken), friction (works, but painful), opportunity (an unmet need or request) or praise (what customers love).
A topic on every finding
Findings are labeled with their topic by meaning, not keyword matching. Synonyms, typos and other phrasings land in the right place, there is no taxonomy to maintain, and history stays comparable when your product changes.
Topics ranked and trending
See every topic by volume, with trend, sentiment and resolution rate, and get flagged when one grows unusually fast for its baseline, before it shows up in your metrics.
Every channel, the same topics
Tickets, chats and emails are read the same way and grouped into the same topics. The same complaint arriving as a Zendesk ticket, an Intercom chat and an App Store review becomes one finding with three mentions, not three separate items in three tools.
Any language, one report
Conversations are analyzed natively in English, Spanish, Portuguese, French, German and more, and roll up into the same topics for a single cross-language view.
From any number to the source
Every number links to the findings and conversations behind it, with the customer, channel and timestamp. Filter by type, topic, segment, channel or date, save views, and push findings to Linear, Jira, Notion or your data warehouse.
How it works
- 01
Connect your channels
Authorize Zendesk, Intercom, Freshdesk, Freshchat, Gorgias or HubSpot to bring in tickets, chats and emails. It takes minutes and needs no engineering work.
- 02
History and new conversations
Up to a week of history is synced on connection so there is something to read immediately, and new conversations stream in from then on.
- 03
Extract findings
Each conversation is split into findings, typed, and linked to its source message, customer, channel and timestamp.
- 04
Label, rank and alert
Findings are labeled with their topic, topics are ranked by volume and growth, and alerts fire when one surges or a new one appears.
Built for every team
Support leaders
Report on what is driving volume, not just how much of it there is. Deflect the top topics instead of hiring against them.
Product
See which gaps come up in real conversations, with the count and the quotes, before the next priorities meeting.
Operations
Get recurring problems with their frequency, the customers affected and the context from real conversations, ready to fix at the source.
Customer success
Track praise and friction customer by customer, and walk into every review meeting with the evidence.
Frequently asked questions
How do I analyze customer conversations without tagging them?
Connect your channels and Synthight reads every conversation automatically, splits it into findings and labels each one with its topic. There is no taxonomy to define and no tagging for agents to do, which also means your historical data stays comparable when your product changes.
How is a finding different from a ticket tag?
A ticket tag describes the whole conversation. A finding is one specific signal inside it, and one conversation often has several. Synthight never forces a nuanced message into a single label.
Do I have to define topics in advance?
No. Topics emerge from your actual conversations, and a new one is created within hours when a new issue starts. You can pin, rename or merge topics to match how your team already thinks, but nothing needs to be configured first.
Can I correct a finding or change a topic?
Yes. Findings can be re-classified, merged or dismissed, and topics can be renamed, merged, split or pinned in one click. Changes apply to history, and Synthight learns from your corrections.
Which conversation channels does Synthight read?
Today, the tickets, live chats and email threads in Zendesk, Intercom, Freshdesk, Freshchat, Gorgias and HubSpot, connected by OAuth in a few minutes. The analysis is channel-agnostic, so new sources feed the same findings and topics. If your stack is not on the list, tell us which tool you use and we will confirm what is possible.
How is this different from the analytics my helpdesk already gives me?
Helpdesk analytics measure the process: volume, response time, CSAT, tickets per agent. Synthight measures the content: what customers were writing about, how often, whether it is growing, and which customers it affects.
Can I analyze conversations that already happened?
Yes. Historical conversations are backfilled when you connect a channel, at roughly 10,000 conversations per hour on a standard workspace, so you get trend lines rather than a report that starts today. New findings are usually available within five minutes of a conversation closing.
Does it work if my conversations are in more than one language?
Yes. Analysis is native per language and topics are consistent across all of them, so a Spanish and an English conversation about the same problem land on the same topic.
Ready to turn customer feedback into decisions?
Connect your channels, and Synthight gets to work. No migration. No new workflows.