Customer voice arrives everywhere, and gets lost everywhere.
A bug report in a Slack thread. A feature request buried in a 45-minute discovery call. The same complaint in a CSV export, the support inbox and a Reddit thread — counted three times or not at all. Most of it never reaches a decision, because no one has the time to read every channel and connect what’s being said across them.
Annsa reads all of it as it arrives. Every message is structured, deduplicated and attributed to a customer before it reaches your priority list — so no voice is lost, whatever channel it came in on.
From raw message to structured signal.
Every source runs the same pipeline.
Slack, CSV, Google Sheets, transcripts, manual, Reddit, surveys and an API/MCP ingress. Eight sources, in 16 languages.
Each message is scored before clustering. “OOO until Monday” and “lol yeah” never reach the list.
Non-English feedback is translated before classification, so a French and a Japanese complaint cluster with their English equivalents under one theme.
The same complaint from three channels becomes one signal, tied to the customer who sent it.
Sources most tools treat as too hard.
The easy channels are table stakes. Annsa reads the ones that usually get left out — and pulls more signal from each.
Upload a call from Otter, Fireflies, Whisper, Grain, Google Meet Gemini or plain text. Annsa detects the speakers and company, then turns a 45-minute call into structured signals — in the same pipeline as everything else.
One message often contains more than one thing. Annsa pulls up to five separate signals from a single message, so a bug and a feature request become two priorities, not one confused row.
Add a survey anywhere in your product — Open-ended, NPS, CES or PMF. Responses don’t sit in a separate dashboard; they cluster and rank alongside every other source.
The rest of the pipeline.
Bubble, Embed, Banner, Thumbs or Trigger. Pick the format that fits the surface.
Track competitor mentions and the threads your customers post in — the ambient layer around your product.
The same complaint from Slack, the widget and a CSV becomes one signal, not three.
A Slack thread with eight replies is read as one conversation, not eight fragments.
Intercom, Zendesk, HubSpot and Typeform skip the mapping step at ≥85% confidence; the rest match on required headers. Move a year of history in minutes.
Wire any custom source into annsa without waiting for a native integration.
A bad CSV doesn’t poison the data; roll it back cleanly.
Listen only where signal is. Opt-in by default, no noise leakage from #random.
Hit your plan cap and feedback queues rather than drops. Upgrade and the backlog releases FIFO.
A message in #support becomes a structured signal in under a second.
Asked and answered.
Slack, in-product surveys and the feedback widget, discovery-call transcripts, CSV exports, Google Sheets, Reddit, a programmatic API for anything custom, and a manual entry form. Across 16 languages.
Upload the recording from Otter, Fireflies, Whisper, Grain, Google Meet Gemini or plain text. Annsa detects the speakers and company, then extracts the distinct signals — a single call often becomes a dozen structured priorities.
Every message from a chat source is scored before it’s clustered. Low-signal messages like out-of-office replies and reactions are filtered out before they reach your priorities.
Yes. Feedback in 16 languages is translated before classification, so it clusters under the same themes as your English feedback — you don’t read it to count it.
Annsa deduplicates across channels. The same complaint from Slack, a widget and a CSV becomes one signal, so your priorities aren’t inflated by re-imports.
No. Classification by intent, clustering by theme and customer attribution all happen in the same pipeline. There are no tagging rules to set up.
Learn more about the annsa Discovery suite.
The full feature overview — feedback in, ranked into one priority list.
One ranked list, sorted by impact and re-weighted for your goal in a click.
Every signal tied to a real account: who asked, how often, what revenue.
NPS, CES, PMF and open-ended — clustered in the same pipeline as everything else.