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Adoptiv

Tonality Analysis

How the agent sounded, how the customer sounded, and one word for the pair of them together. Chosen words rather than a fixed list, which is what lets them describe a call that closed politely and grudgingly.

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How the call sounded

per analysed call
agent tonality
Marcus Hale
warm
customer tonality
Ben Osei
clipped
Overall
brisk
Sentiment, same pass
positive
Notes, one sentence, grounded in the transcript

The customer agreed to the renewal inside a minute and mentioned twice that they were between meetings.

The words are chosen, not picked from a list, so they read rather than chart · the record column keeps the overall one
This one closed, so the sentiment is positive and a dashboard built on sentiment alone would stop there. The tonality is what says the customer was in a hurry the whole way through.
0
things asked for on every call
0
of them kept on the record
0
characters the kept word gets

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

The mechanism

How it works.

01

Four pieces come back and one is kept

The request asks for the agent's dominant manner, the customer's, a single word for the conversation, and a sentence of evidence. Only the conversation word is validated, and only it is written down, into a fifty character column. The other three are read and dropped.

02

Nobody wrote the list of words in advance

Nothing holds the answer to a fixed set, so a call can come back clipped, resigned or apologetic without anyone having predicted those in advance. The cost is that these words read rather than compute.

03

The evidence sentence has to point at something

The instruction asks for a concrete moment rather than a restatement of the label, and nothing enforces it: the sentence is neither validated nor stored. Presets sharpen what to watch for by vertical: frustration and de-escalation on a support line, stress and empathy where a claim is being made.

04

Tallied, because it cannot be averaged

The overnight rollup counts how often each word appears for an agent and stores the whole spread as counts. Since no list exists in advance, a word nobody expected simply turns up in the tally rather than being swept into an other bucket that explains nothing.

Where it sits

One moment in every read.

Every read passes through the same seven. Tonality Analysis 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
Asked for
Agent manner, customer manner, one word for the conversation, one sentence of evidence
Kept
That single conversation word, in a fifty character column on the analysis
Vocabulary
Open. No enumeration, no fixed list, and no number attached to any of it
Rollup
Counted per agent per day as a spread, because averaging a word would mean nothing. Written nightly and read as counts
Per speaker on the record
Not persisted. The pair is produced by the model and written to no column
Not the same as
Sentiment is one enum about the outcome. This is the manner of both parties
On mail
Not asked for. Manner of speech is a call idea and the mail path leaves it out

More in Intelligence

12 capabilities

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

Call Analysis

A supervisor who used to open the audio reads it instead: what the call was about, how it went, what was asked for, what it scored. One reading, one answer.

AI CRM Writeback

Nothing on an existing lead moves by itself. What the call gave up arrives as proposed edits, each with the value it would replace and the words it came from.

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.

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.

Intent Detection

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

Follow-Up Extraction

A promise made out loud is worth nothing until it sits on a day. Callbacks and meetings come off the call with the time said, real the moment you accept.

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 tonality analysis on your own floor.

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

See pricing

14-day trial · no card · migration included