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Bring Your Own Model

Fifteen provider adapters and a separate binding for each thing the platform asks a model to do, so transcription and post-call reading are two decisions rather than one. The bindings are set by the operator, not inside a workspace.

Which model answers this call

healthy
Purposes bind separately
  • primaryAnthropic2/3 failuresserving
  • fallback 1Azure OpenAIstandby
  • fallback 2Bedrockstandby
Bindable providers
OpenAIAzure OpenAIAnthropicGeminiBedrockCohereMistralGroqTogether
Plus the speech providers for the audio purposes · every binding is set once, centrally, and never in a page's code
Two consecutive failures. Still on the primary, one away from the threshold.
0
provider adapters in the registry
0
of them able to serve text work
0
failures in a row that shut a binding

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

The mechanism

How it works.

01

A purpose is a category and a modality together

Thirteen categories across four modalities, each bound on its own, so transcription and post-call reading never have to sit on the same model. Two of the thirteen are a cheap text reading and a heavier one, which is how short work and long work end up on different models and different bills.

02

One primary, then an ordered chain

Each purpose names a primary and a list of fallbacks in the order to try them. An unusable primary leaves the purpose unbound rather than promoting a fallback into the gap, because promoting one would hide the breakage.

03

What went wrong decides what happens next

A rate limit or a timeout counts as capacity: one further attempt on the same model behind a jittered wait, then onward. Everything else advances immediately with no second try, and an authentication or missing deployment failure raises an alert on its way past rather than moving quietly.

04

Three strikes shuts a binding for half a minute

Failures are counted per provider and model in shared state, so an outage is noticed once instead of once per workspace. After the wait exactly one request is let through, and it either reopens the binding or restarts the clock. If that state is unreachable, everything is treated as healthy.

Where it sits

One moment in every read.

Every read passes through the same seven. Bring Your Own Model 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.

8 facts
Coverage
Fifteen adapters, nine text capable, over thirteen categories and four modalities
Nothing bound
Fails loudly and names what is missing. Audio routes alone may fall back to environment keys
Chain
A primary plus an ordered fallback list, per purpose. Not one global preference
When one fails
A rate limit or a timeout gets two attempts on that model, then the next. Everything else moves on at once. Configuration failures raise an alert as they pass, and the last one in the chain is thrown
Breaker
Three consecutive failures, thirty seconds shut, one probe to reopen it
Timeout
Sixty seconds per attempt, unless the calling code asks for its own limit
Where it is bound
One platform-level catalogue of providers, models and purposes. Credentials are held once and encrypted; there is no per-workspace key store, so this is the operator's choice on your behalf
Not the same as
This is which model answers. Which instruction it gets is the presets page

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.

Call Scoring & QA

Communication, resolution, satisfaction and compliance scored nought to ten beside a separately judged overall, on every call that clears the analysis gates.

Compliance Scoring

Compliance scored nought to ten against what the vertical says matters, because no phrase list exists to recite. A missing reading is excluded, never passed.

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.

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.

Intelligence

See bring your own model on your own floor.

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

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