Every conversation, decoded into structured findings
Synthight reads every support ticket, chat, and email — and pulls out the specific issues, frictions, opportunities, and moments of praise buried inside. Nothing useful gets lost in free text.
From ticket · Sarah K. · Enterprise
"Onboarding took forever — the checkout kept failing on larger orders. I almost gave up, honestly. The dashboard is great once you're in."
Overview
Most customer conversations hide more than one signal. A single ticket often contains a bug report, a usability complaint, a feature request, and a compliment — all tangled into one block of text. Traditional tagging systems force agents to pick one label and move on, so the other signals vanish.
Findings are Synthight's atomic unit of customer intelligence. Every conversation is parsed into one or more findings, each classified as an issue, friction, opportunity, or praise. Each finding is linked back to the source message and the specific customer, so you always have the quote, the context, and the full thread a click away.
The result: your team stops skimming and starts acting. Product sees feature requests without hunting through Slack. Support sees patterns without re-reading 200 tickets. Leadership sees what's trending without asking anyone to build a report.
What you get
Multi-finding extraction
A single conversation can yield multiple independent findings. Synthight identifies each one separately, so a compliment about your dashboard doesn't drown out a bug report in the same thread.
Automatic classification
Every finding is tagged as an issue (broken behavior), friction (working but painful), opportunity (unmet need or feature request), or praise (what customers love).
Source-linked context
Every finding links to the original message, customer profile, channel, and timestamp. One click away from the raw context — always.
Search and filter
Slice findings by type, sentiment, customer, segment, plan, channel, or date range. Save views and share them across your team.
Language-agnostic
Works across English, Spanish, Portuguese, French, German, and more — without needing to configure language rules per channel.
Export and integrate
Push findings into Linear, Jira, Notion, or your data warehouse. Findings are structured JSON — ready for any downstream workflow.
How it works
- 01
Ingest
Synthight streams conversations from your connected channels — Intercom, Zendesk, HubSpot, Freshdesk, Gorgias, and more — in real time.
- 02
Extract
Each message is parsed by Synthight's analysis engine, which identifies distinct findings and classifies them with their sentiment, intent, and affected feature area.
- 03
Link
Findings are persisted against the source conversation and customer, so every insight keeps its full provenance.
- 04
Surface
New findings flow into the Insights Feed, feed topic clusters, update customer profiles, and trigger alerts where you've set them.
Built for every team
Product
See which feature gaps are driving real tickets — not just the ones users vocally request.
Support leaders
Spot systemic issues before they become ticket surges. Prioritize work by frequency and severity.
Customer success
Track praise and friction at the account level. Walk into QBRs with evidence.
Engineering
Get bug reports enriched with customer context, steps to reproduce, and affected segments.
Frequently asked questions
How is a finding different from a ticket tag?
A ticket tag describes the whole conversation. A finding is a single specific signal inside a conversation — and one conversation often has several. Synthight doesn't force you to reduce a nuanced message into a single label.
Do I need to train the model on my data?
No. Synthight works out of the box across any SaaS, e-commerce, or fintech vocabulary. You can optionally refine categories for your domain, but it's not required to get value on day one.
Can I correct a finding if it's mislabeled?
Yes. Every finding can be re-classified, merged, or dismissed. Synthight learns from your corrections to improve future extractions for your workspace.
How fast are findings available after a conversation closes?
Typically under five minutes after the ticket closes. Historical backfills run at about 10,000 conversations per hour on a standard workspace.
Does this work with conversations in multiple languages?
Yes. Findings are extracted natively across major languages, and classification categories stay consistent across them for cross-language reporting.
Ready to turn conversations into clarity?
Connect your channels, and Synthight gets to work. No migration. No new workflows.