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Industry Presets

Fifteen verticals, each a paragraph telling the model what matters on that kind of call. Choosing one swaps the guidance above the contract and does not move a character of the keys beneath it.

Analysis tuned to the floor it runs on

preset 4 of 15
Fifteen to start from
What it tells the model to weigh
changes with the preset

Required disclosures, right-party verification, no threats, and any dispute or cease-contact request captured as it was made.

The shape it must answer in
identical under all fifteen
summarysentimenttonalityintentionsscoresspam_urgency
Editing the guidance cannot change the keys · which is why the reporting built on them survives the edit
A workspace can also append its own context, which is wrapped and handed to the model as data rather than as instructions. It can add what the model knows about your business; it cannot reach the shape of the answer.
0
verticals seeded on the shelf
0
output keys that never move
0
steps in the resolution order

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

The mechanism

How it works.

01

A preset is guidance and carries no schema

Each holds one paragraph spanning every dimension: what a summary ought to name, which dispositions are likely, what the numbers should be strict about. None of them contains any JSON, deliberately.

02

Five steps settle which one runs

An explicitly chosen preset, then the campaign this call belonged to, then the workspace default, then the older single setting, then the platform base. Whichever resolves first wins and the rest are never consulted.

03

A workspace can own one without ever seeing the base

Its preset is either entirely its own paragraph or built on a platform one, and in that second case the platform wording resolves on the server and is never sent to a browser. Either way its own context is appended afterwards.

04

Every edit keeps the wording it replaced

Each analysis is stamped with whichever version was live when it ran, so a rewording stays comparable against the calls that went through the one before. The versioning covers a workspace's own preset. The fifteen seeded ones refuse an edit outright, and resetting one to its seed rewrites the wording with no snapshot behind it.

Where it sits

Two moments in every read.

Every read passes through the same seven. Industry Presets is the lit ones, 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.

8 facts
Catalogue
Fifteen seeded verticals. A platform administrator can add more or deactivate one
A preset changes
Domain guidance only. The six output keys and their shapes are fixed in code
A workspace preset adds
Its own trigger mode, strong language masking, length floor and call opt-in
Resolution
Chosen preset, campaign, workspace default, older single setting, platform base
Workspace text
Appended inside a tag and labelled as data, so it cannot rewrite the rules above
Propagation
Cached for sixty seconds, with an invalidation message so an edit lands sooner
Versions
Append only. Each analysis stamps the version that produced it, or stamps nothing
Not the same as
This tunes what is looked for. Which calls enter at all is the gate settings

More in Intelligence

12 capabilities

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

AI CRM Writeback

The model proposes record updates with its confidence and the quote it heard them in, shown as a before-and-after you accept or reject row by row.

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

Positive, neutral or negative on every analysed call, stored in a column of its own so the ones that went wrong are a filter rather than a listening exercise.

Tonality Analysis

Chosen words rather than a fixed list for how the agent sounded, how the customer did, and the conversation overall - the manner behind the sentiment.

Intent Detection

What the customer was actually asking for and what the agent committed to, extracted as structured intents rather than left inside the transcript.

Follow-Up Extraction

Callbacks and meetings pulled out with their times, a confidence figure and the words they came from, ready to accept in one click or reject in one.

Diarized Transcripts

Four of six speech paths return the channel each side was recorded on, so the transcript knows who spoke rather than guessing, and one control swaps a pair.

AI Email Analysis

Threads summarised and read for intent and urgency, but only when a participant matches a record, so the model is never called on mail that is not yours.

AI Email Writing

Draft from an instruction or rework a message you have, landing in the composer with a suggested subject and going nowhere at all until you send it.

AI Field Generation

Describe what you track or paste a spreadsheet's columns, and get a named field group back with types, options and placeholders to approve one at a time.

Natural-Language Filtering

A sentence becomes a grid filter and a sort order with the reading explained back, on the toolbar of every grid that carries a column menu of its own.

Bring Your Own Model

OpenAI, Azure, Anthropic, Gemini, Bedrock and ten more, bound per purpose with an ordered fallback chain, a circuit breaker and a cost line on every attempt.

Intelligence

See industry presets on your own floor.

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

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