The performance layer for Customer Experience.
Define your KPIs, score 100% of your conversations, whether a person or an AI agent handled them, and reveal the business insights behind every one, on your existing stack. Enastro cites every number back to the moment in the call it came from, so you see clearly instead of sampling in the dark.
CLIENTHi, I'm calling about my bill, I think I've been charged twice for last month.
AGENTLet me pull up your account... okay, I can see it, you're right, that second charge shouldn't be there.
AGENTI've gone ahead and refunded the €40 duplicate charge back to your original card.
CLIENTOh, brilliant. So there's nothing else I need to do on my end?
AGENTNothing at all, you'll see it back within three to five working days.
AGENTOh, and just so you know, we do keep a recording of these calls for training purposes.
CLIENTNo worries at all, thanks for sorting it out so quickly.
Every value cites the line it came from, and your team can correct any of them.
Manual QA hears 1 call in 100. Enastro reads all 100.
The insight you need is rarely in the calls you happened to sample. Enastro transcribes and scores every recording, so the pattern hiding in the 99% you never listened to finally shows up.
- Sampled by hand
- ~0%
- Read by Enastro
- 0%
Hover a call, or tap it, to see a KPI Enastro scores.
From a recording to a cited metric.
Five stages, each an independent worker on an event-driven pipeline, so a hundred thousand recordings move through the same way one does.
Ingest
Pull or receive recordings, with de-duplication and incremental watermarks so nothing is processed twice.
Transcode
Normalize every file to a clean, consistent audio stream and probe its true duration.
Transcribe + diarize
Turn audio into words attributed to speakers, who said what, and when.
Analyze
Summary, sentiment, topics, action items and key phrases for the whole conversation.
Extract KPIs
Every KPI in your set becomes a value, with the reasoning and confidence behind it.
Choose your speech-to-text provider per job. Rerunning the same recording and config never double-charges you.
Your metrics, your definitions.
The KPI Catalog is a growing catalog of ready-made metrics you apply to your audio. Start from one, or define your own in plain language, no rules to wire up.
- A Group KPIs into Sets you apply to any job.
- B Eight types cover the answers you need: yes/no, category, multi-select, number, percentage, currency, text, or entity.
- C Some are computed deterministically; the rest are read by the model.
- D Every value is correctable by your team . Overrides are tracked.
Every insight traces to a Job.
A Job pins the source, the KPIs, the model, the schedule and exactly which recordings are in scope, so any result is reproducible, and you see the cost itemized before a single minute is processed.
- Source
- Acme · Google Cloud Storage
- eu-recordings/inbound/
- Scope
- Last 30 days
- 280 recordings match
- KPI Set
- QA · Support
- 12 KPIs
- Transcribe
- Speech-to-text
- provider of your choice
- Trigger
- Recurring
- daily · 06:00 CET
- Speed
- 4×
- priority processing
Example estimate · synthetic figures. Usage is metered per operation, you're billed for what you actually analyze.
Run jobAsk your data. In plain language.
Skip the dashboard archaeology. Ask a question about a job's results and Enastro answers from the numbers it actually extracted, and proposes the chart to go with it.
Grounded in this job's analyzed results · % resolved on first contact, by weekday · synthetic
Point Enastro at your recordings.
See what you've been missing.
Connect a source, pick your KPIs, and read every conversation, with the cost in front of you before anything runs.