Inject

Any data item

Connectors or approved one-off imports load email addresses, cookies, events, CRM rows, products, support, billing, documents, and outcomes.

Store

Attribution paths

Scout stores each item's relationship set, vector, and ordered attribution path in customer-owned PostgreSQL/pgvector. Fortress moves high-load memory into Rust/LanceDB, not KynticAI product operations.

Compare

Rust + LanceDB

Enterprise contains the proprietary Rust relationship, weighting, traversal, and LanceDB path for fast similarity analysis across millions of relationship sets.

Output

Top-example JSON

The engine creates JSON with the best examples, importance bands, confidence, caveats, and ranked task options for the question being asked.

Explain

LLM task brief

Fortress sends JSON to your approved model boundary. The proposed Elite path shows the executive walkthrough from safe discovery to scoped pilot and outcome review.

Clarity Gateway / Session Memory

Let the session remember the clarified task, not the whole conversation.

For deployments that enable Redis-backed mode, Clarity Gateway can remember safe resolved intent for a short-lived session, so follow-up work stays in scope without carrying the whole transcript forward.

Clarify once

The first resolved request creates a safe session marker that can support compatible follow-up turns.

Scope follows the session

Users can add a source, narrow a list, or change output format without restating the whole task.

Expiry keeps control

Session memory remains tied to deployment policy, cache behaviour, and validation markers.

What it does

The concrete job

It stores session-level intent markers, cache hits, route context, and clarification state behind protected key patterns and expiry settings.

Why buyers care

The commercial reason

The experience feels dramatically smoother: one clarification can shape the next few turns, while the system keeps a clean operational boundary for session memory.

Support path / Session Memory

The session remembers the clarified task, not the whole conversation.

Session memory is a supporting Clarity capability for follow-up work. It keeps the useful resolved scope available without turning the whole chat into baggage.

Buyer question

The user clarified renewal risk once. Can the next turn stay in scope without restating everything?

Example output buyers can understand

Follow-up accepted: keep the renewal-risk task and narrow it to enterprise accounts.

No transcript dump required: the handoff carries the resolved intent marker and the new filter.

Owner output: ranked enterprise renewal list with next action, caveat, and source need retained.

The workflow feels joined-up for the user while the product keeps memory focused on the task shape that matters.

01

Resolved turn saved

The first clarification creates a short-lived intent marker for the active workflow.

resolved_intent = renewal-risk action brief

scope = accounts renewing in next 45 days

output_shape = account owner next actions

02

Compatible follow-up

The user narrows the work, and Clarity can keep the original scope instead of making them start again.

follow_up = now only show enterprise accounts

cache_marker = compatible with active renewal-risk task

privacy_shape = intent marker rather than full transcript

03

Scoped output out

The next model, tool, or owner receives a tighter task that respects the previous clarification.

cache_hit = true

new_scope = enterprise accounts renewing in next 45 days

next_route = refreshed owner action brief

Clarity example in plain English

Session memory in plain buyer terms.

The buyer can see the motion without proprietary internals: a confusing request enters, Clarity resolves the task shape, and a cleaner handoff leaves for the next model, workflow, tool, or human owner.

In

The buyer brings a confusing moment

The input is the prompt, request, handoff, workflow step, or support question that usually creates rework.

Read

Clarity reads the task shape

It stores session-level intent markers, cache hits, route context, and clarification state behind protected key patterns and expiry settings.

Fix

The ambiguity is resolved

The page-specific capability either asks the useful question, frames intent, stores safe session scope, builds a handoff, or prepares the integration route.

Out

A usable handoff comes out

The output is buyer-readable: a question, structured brief, safe envelope, proof marker, route hint, or action-ready note.

Example input

One renewal-risk clarification powers the next request

Turn 1: 'Show risky renewals.'

Clarification answer: 'Renewal risk over the next 45 days, prioritising accounts with open support issues.'

Turn 2: 'Now do the top five with product usage signals as well.'

Example output

cache_marker = resolved_intent_available

session_scope = renewal risk / next 45 days / support issues prioritised

new_source_need = add product usage signals

handoff = top five action brief using cached scope plus the new source requirement

Buyer result

The experience feels dramatically smoother: one clarification can shape the next few turns, while the system keeps a clean operational boundary for session memory.

Concrete example

One renewal-risk clarification powers the next request

Example input

Turn 1: 'Show risky renewals.'

Clarification answer: 'Renewal risk over the next 45 days, prioritising accounts with open support issues.'

Turn 2: 'Now do the top five with product usage signals as well.'

Example output

cache_marker = resolved_intent_available

session_scope = renewal risk / next 45 days / support issues prioritised

new_source_need = add product usage signals

handoff = top five action brief using cached scope plus the new source requirement

Proof marker

Redis-mode proof can check cache writes, reads, expiry behaviour, and route markers.

Hashed cache-key patterns keep sensitive prompt fragments out of the keyspace.

Session memory stores the minimum safe resolved state needed for repeat clarification avoidance.

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.

Resolve

Clarify once

The first clarified request creates a safe session intent marker.

Cache

Store short-lived context

Redis-backed mode keeps the resolved scope available for follow-up turns.

Reuse

Avoid repeated questions

Follow-up requests inherit the resolved scope when the new instruction is compatible.

Expire

Close the session

Expiry settings keep session memory scoped to the deployment policy.

Output created

The data artefacts that make the capability useful.

Session intent marker

A safe marker describing the resolved task scope for the active conversation.

Cache-hit signal

A routeable signal that lets the next turn reuse prior clarification.

Updated handoff

The new request plus cached intent becomes a compact downstream instruction.

Buyer payoff

The assistant finally remembers what the conversation is about.

Pain

Users keep restating the same timeframe, account set, and output shape, or the model silently drifts.

Relief

Clarity reuses the resolved session scope and only asks again when the request changes enough to matter.

Outcome

Less friction for high-value users, fewer repeated model calls, and a cleaner agent or support experience.

Proof

Proof comes from session-cache fixtures, Redis-mode counters, hashed-key checks, and expiry behaviour validation.

Example scenario boxes

Where this capability shows up in the real buyer conversation.

Account-room workflow

Old way

Every follow-up asks the user to restate account, timeframe, and risk lens.

With Clarity

Redis-backed memory carries the resolved scope through the session.

The account team moves from question to action with less conversational drag.

Support incident

Old way

The assistant forgets the severity and keeps asking broad incident questions.

With Clarity

The cache remembers severity, impacted product, and desired handoff shape.

The escalation brief stays consistent across turns.

Analyst workflow

Old way

Follow-up prompts create accidental scope drift.

With Clarity

Compatible follow-ups inherit the clarified decision frame.

The analyst can iterate while the session keeps the clarified context in view.

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.

Evidence Results

Clarity Gateway clears intent before provider routing.

These examples show how resolved intent, routing, and safer handoffs improve model output.

KynticAI Result
Intent Clarity

Clarity scenario - vague prompt, missing timeframe, missing account scope

Stop answering the wrong question

Before an ambiguous request reaches the configured provider, Clarity Gateway asks the one useful question that pins the subject, timeframe, data source, or output shape.
KynticAI Result
Agent Routing

Clarity scenario - model, tool, Context Engine path, human review

Send the work to the right path

Resolved intent can route to Scout, Fortress, KynticAI Importance, an approved model endpoint, a tool, or a human workflow.
KynticAI Result
Instruction Fidelity

Clarity scenario - structured request, cleaner handoff, fewer retries

Reduce ambiguous provider calls

A clarified request can be framed as a cleaner instruction before generation begins.