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Adoptiv

Intent Detection

What the customer asked for and what the agent promised, returned as two separate lists because they are two different obligations and only one of them is yours to keep.

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What each side meant

reading the transcript
Transcript
Customer intents
  • Invoice reissued at the agreed rateprimary
  • Credit rather than a carry-over
Agent commitments
  • Reissue the invoice today
  • Raise a credit note
Suggested disposition
waiting for the end of the call
interestednot_interestedcallback_requestedappointment_setvoicemail_leftwrong_numberdo_not_callno_answerfollow_up_neededcompletedother
Two lists rather than one, because what the customer asked for and what the agent promised are different obligations, and only the second one is yours to keep.
0
disposition codes it may propose, and not one more
0
lists pulled out of one conversation
0
thing the call was mostly about, named on its own

Product figures from the platform’s own defaults - not customer averages

The mechanism

How it works.

01

Two lists, and they are never merged

Customer intents on one side, agent commitments on the other, both as short labels rather than paragraphs. A single dominant intent is named separately and stored beside them, so a call can also be counted by the one thing it was mostly about.

02

A disposition is proposed from a closed set

Eleven codes: interested, not interested, callback requested, appointment set, voicemail left, wrong number, do not call, no answer, follow up needed, completed, other. A readable phrase comes with it and that phrase is not constrained at all.

03

The proposal stays a hint and does not click

It appears only while no disposition has been set, and setting one hides it. Your own catalog is what a rep picks from, because those eleven codes are the model's vocabulary rather than your reporting categories.

04

Leave this out and the review queue is empty

The proposed record edits and the proposed follow-ups ride inside this one answer rather than beside it, so a run that skips it leaves your reviewers with nothing to review. A sentence of notes sits underneath the lists.

Where it sits

One moment in every read.

Every read passes through the same seven. Intent Detection is the lit one, and everything either side of it is a different page in this category.

  1. 01
    Source

    the call or the thread it reads

  2. 02
    Transcribe

    audio into words, with speakers

  3. 03
    Read

    the pass over the whole of it

  4. 04
    Judge

    the score, the sentiment, the intent

  5. 05
    Extract

    the fields and follow-ups pulled out

  6. 06
    Write

    what lands back on the record

  7. 07
    Review

    a person checking the machine

The specifics.

7 facts
Returns
A list of customer intents, a list of agent commitments, and one dominant intent
Disposition
One of eleven categories plus a free phrase. Neither is written onto the call
Applying it
By hand. Nothing maps those eleven codes onto the codes your floor uses
Shown
Only while the call carries no disposition. Choosing one removes the hint
Also carries
The proposed column edits and the proposed follow-ups. They are fields of this block
Shape
Free JSON on the analysis row. Its presence is checked, its interior is not
Not the same as
Labels and a code. The summary answers the same call in readable prose

More in Intelligence

12 capabilities

AI that proposes edits to the record - an insight becomes a field once you accept it.

Call Summaries

One to six sentences on the record covering why the call happened and what was agreed, so nobody reading the list has to open the audio to find out.

Sentiment Analysis

Finding yesterday's bad calls is a filter, not an afternoon. Positive, neutral or negative on every analyzed call, kept in a field of its own you can sort on.

Tonality Analysis

How the agent sounded, how the customer sounded, one word for the pair. Chosen words rather than a fixed list, so a call can close politely and grudgingly.

Call Scoring & QA

A month of calls gets reviewed by whoever had time. Every call carries five numbers instead, and the overall is judged in its own right rather than averaged.

Compliance Scoring

Nobody re-listens to check the disclosure went out. Every call is scored against what compliance means on your floor, with a missing one excluded, not passed.

Diarized Transcripts

A coaching note never quotes the customer back at a rep who did not say it. Four of six engines return the channel each side was on, one control swaps them.

Industry Presets

A collections call and an admissions call are not judged the same way. Fifteen verticals ship knowing the difference. What comes back still reads the same.

AI Email Analysis

A thread is read only when somebody on it is one of your leads. No match and nothing is sent anywhere, so mail that is not about a customer is left alone.

AI Email Writing

A draft or a rewrite that lands in the composer and stops there. The subject is a suggestion, every word editable, and nothing leaves until a person sends it.

AI Field Generation

The field group you would otherwise build one field at a time. Describe what you track or paste a spreadsheet's columns, then approve or refuse each field.

Natural-Language Filtering

Type the list you want and it builds the filter and the sort. Then it says in one sentence what it understood: a filter nobody typed has to say what it did.

Bring Your Own Model

OpenAI, Azure, Anthropic, Gemini, Bedrock and ten more. When one starts timing out mid-afternoon the work moves down the chain rather than stopping on you.

Intelligence

See intent detection on your own floor.

Thirty minutes, your numbers and your data. We will set intent detection up live and you can decide from the thing itself rather than from this page.

See pricing

14-day trial · no card · migration included