Clarity Gateway / Optional account-context framing
Make the subject and decision moment explicit before any model answers.
This optional Clarity capability clarifies prompts that refer to an account, supplier, candidate, or case — so the model receives a clear subject, moment, and missing detail list. Pure prompt clarification for commercial context. Completely separate from Context Engine.
Optional only
Account-context framing is an example of deeper clarification, not a dependency on Context Engine or Importance Engine.
Subject made explicit
Who or what the request is about becomes clear before any model spends tokens.
Missing detail listed
The clarification step names what is still missing so the first answer is not a guess.
What it does
The concrete job
It clarifies vague commercial prompts by making the subject, decision moment, expected outcome, and missing information explicit before any LLM runs.
Why buyers care
The commercial reason
Teams stop paying for generic model answers to 'help with the account' when the real ask was never clear.
Optional path / Relationship Intelligence
A customer note becomes a relationship moment the team can act on.
Relationship-intelligence is an optional Clarity route. It shows how Clarity can frame the commercial relationship behind a request without making the gateway depend on that capability.
Buyer question
What relationship moment is hidden inside this customer note?
Example output buyers can understand
Relationship frame: renewal recovery moment, with support frustration and lower usage as the key safe signals.
Missing-data note: confirm the latest owner note and support severity before recommending commercial pressure.
Account-team output: open with service recovery, prove follow-through, then move to renewal next steps.
The product feels commercially sharp because it understands the moment of the relationship, not just the words in the request.
01
Account note in
The user asks for help before a renewal call, but the real need is to understand relationship pressure.
prompt = help me prepare for the renewal call
signals = support frustration, usage lower, renewal date near
risk = generic account summary misses the relationship moment
02
Optional frame built
Clarity creates a safe relationship-intent frame with subject, moment, signals, and missing data.
relationship_intent.subject = selected account
moment = renewal recovery
missing_data = owner note, support severity, billing status
03
Team brief out
The account team receives a precise relationship brief rather than a generic summary.
route = account-team action brief
tone = recovery before commercial ask
next_action = confirm support fix before renewal discussion
Concrete example
Vague renewal prep becomes a clear request
Example input
User: 'Help the account manager prepare for the renewal call. Support is frustrated and usage looks lower than last month.'
Missing: which account, which renewal window, which success outcome.
Target: one clean request to any model the team already uses.
Example output
clarified_subject = named account
clarified_moment = renewal preparation
signals_mentioned = support frustration, usage decline
missing_data = commercial owner note, open support severity, billing status
clean_request = prepare a renewal briefing for account X focused on support and usage risk
Proof marker
Optional capability; core Clarity remains detect → ask → forward.
Output is a clarified prompt contract, not a runtime analysis product.
Works in front of any compatible LLM.
How it works
The operating flow buyers can understand.
Each Clarity capability is explained through input, output, route, and validation markers. The proprietary method stays protected while the buyer sees exactly what the system creates and why it matters.
Find missing commercial context
Identify when the prompt lacks subject, moment, or success criteria.
One clarifying question
Ask for the account, window, or outcome that produces an answerable task.
Write a clean request
Forward a precise prompt the model can answer without inventing the subject.
Only then call the model
Tokens are spent after the request is answerable.
Output created
The data artefacts that make the capability useful.
Clarified subject
Who or what the request is about, made explicit.
Missing-data notes
What still needs to be known before a good answer.
Clean model request
A precise prompt ready for any LLM.
Buyer payoff
Fewer generic answers to vague commercial asks.
Pain
A model treats 'help with the account' as generic text and wastes tokens.
Relief
Clarity forces subject, moment, and missing detail into the open first.
Outcome
Lower token waste and more useful first answers for sales, support, and diligence prompts.
Proof
Proof is the clarified request quality — not a separate analysis product claim.
Example scenario boxes
Where this capability shows up in the real buyer conversation.
Sales renewal
Old way
The model invents a generic renewal summary.
With Clarity
Clarity asks which account and what 'good prep' means before generation.
The first answer matches the real renewal moment.
Supplier diligence
Old way
The model summarises documents before the diligence question is clear.
With Clarity
Clarity clarifies the supplier and the decision question first.
The review starts from a precise ask.
Support recovery
Old way
A complaint prompt produces a generic apology script.
With Clarity
Clarity clarifies account, severity, and desired outcome first.
The reply path is specific and less wasteful.
Continue the product path
Connect this capability to the rest of KynticAI Clarity Gateway.
Bring the repeated ambiguous request. KynticAI will shape the first Clarity proof around it.
Pick the repeated prompt, workflow, support path, agent route, or executive brief where one missing variable causes expensive rework. KynticAI can map the first Clarity proof around that moment.