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 / Developer Integration

Put Clarity exactly where vague prompts become expensive.

Developers can place Clarity Gateway in front of approved model gateways, internal tools, agent workflows, CLI operations, MCP surfaces, or application code, turning ambiguous requests into inspected handoffs before costly routes begin.

Drop in before the gateway

Use SDK, CLI, MCP, or proxy-style routes at the point where user intent becomes model or workflow spend.

Clarify in the request path

Return a question, structured intent, or handoff contract that application code can inspect.

Forward approved work

Resolved requests move through the deployment's approved upstream boundary with safe error behaviour.

What it does

The concrete job

It exposes integration patterns for TypeScript, Python, CLI, MCP, and proxy-style routes so resolved intent can be created, inspected, and forwarded through the approved deployment boundary.

Why buyers care

The commercial reason

Product and platform teams can add intent clarity where the expensive mistakes happen: before retrieval, before model calls, before automated actions, and before confused tickets reach a human owner.

Sales path / Developer Integration

Clarity sits before the AI gateway where vague prompts become expensive.

The developer route gives product teams a simple buyer story: catch the ambiguous request in the app, return a useful question or handoff, then forward only approved work.

Buyer question

Where should Clarity sit in the product before the model route starts?

Example output buyers can understand

Developer output: a typed response saying clarification is required, with the exact question to show the user.

After resolution: a compact handoff envelope that the approved gateway can receive.

Product outcome: fewer vague prompts reach the costly route, and users see a smarter first interaction.

The buyer sees where Clarity plugs in: before the spend, before the wrong route, and before the support team inherits confusion.

01

App request in

A product feature receives a user prompt that is too vague to route straight to a model or workflow.

user_prompt = do the customer-risk thing for top accounts

app_route = AI workspace action

risk = gateway receives the wrong task

02

SDK responds

The application gets a structured result it can show, test, or route.

sdk_status = clarification_required

question = Should customer risk mean renewal, support, credit, or expansion risk?

next_step = wait for answer or use approved default route

03

Proxy forwards

After resolution, the proxy sends a compact handoff through the approved gateway boundary.

resolved_intent = renewal-risk action brief

proxy_route = approved gateway path

handoff = compact envelope with caveats

Clarity example in plain English

SDK and proxy 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 exposes integration patterns for TypeScript, Python, CLI, MCP, and proxy-style routes so resolved intent can be created, inspected, and forwarded through the approved deployment boundary.

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

Application prompt becomes a proxy-ready Clarity handoff

App call: classify and frame the user's request before routing to the approved AI gateway.

User request: 'Do the customer-risk thing for the top accounts and make it board ready.'

Deployment target: internal proxy path with approved upstream gateway shape.

Example output

sdk_result.status = clarification_required

question = 'Should customer risk mean renewal risk, support risk, credit risk, or expansion risk?'

resolved_handoff = created after answer

proxy_route = approved gateway path with compact intent envelope

Buyer result

Product and platform teams can add intent clarity where the expensive mistakes happen: before retrieval, before model calls, before automated actions, and before confused tickets reach a human owner.

Concrete example

Application prompt becomes a proxy-ready Clarity handoff

Example input

App call: classify and frame the user's request before routing to the approved AI gateway.

User request: 'Do the customer-risk thing for the top accounts and make it board ready.'

Deployment target: internal proxy path with approved upstream gateway shape.

Example output

sdk_result.status = clarification_required

question = 'Should customer risk mean renewal risk, support risk, credit risk, or expansion risk?'

resolved_handoff = created after answer

proxy_route = approved gateway path with compact intent envelope

Proof marker

SDK, CLI, MCP, and proxy surfaces can be covered by local package tests.

Proxy routes use approved upstream gateway configuration under deployment policy.

Safe error handling keeps provider or service details out of casual user-facing output.

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.

Place

Choose the integration point

Add Clarity before a model gateway, tool call, agent path, support workflow, or human queue.

Call

Use SDK, CLI, MCP, or proxy

Generate clarification, structured intent, or a routeable handoff through the integration surface.

Inspect

Read the contract

Inspect the public-safe intent fields, caveats, and route markers.

Forward

Route under policy

Send the handoff to the approved model, tool, workflow, or human route.

Output created

The data artefacts that make the capability useful.

SDK response

A structured result for application code, tests, and product workflows.

Proxy handoff

A compact routeable request for approved gateway shapes and internal model paths.

MCP tool surface

A tool-facing contract for agent and developer workflows that need clarity before action.

Buyer payoff

Clarity lands where the cost starts.

Pain

Developers bolt AI into the app, then discover the expensive failures all start with vague requests.

Relief

Clarity sits in the request path, clarifies or frames intent, and forwards the governed handoff.

Outcome

Faster product adoption, easier internal governance, and fewer model calls spent on ambiguous work.

Proof

Proof comes from package tests, proxy conformance checks, safe-error fixtures, and local integration walkthroughs.

Example scenario boxes

Where this capability shows up in the real buyer conversation.

AI gateway

Old way

Every user prompt is sent straight to the model route.

With Clarity

The proxy checks ambiguity and creates a compact intent envelope first.

The gateway receives a better task with a cleaner contract.

Agent workflow

Old way

An agent starts tool calls before knowing the user's real decision.

With Clarity

The MCP surface asks for clarification or returns a structured task.

The agent calls fewer irrelevant tools and produces a more useful dossier.

Product feature

Old way

The application team hardcodes prompt templates for every vague request.

With Clarity

The SDK creates a governed intent frame that the product can inspect.

The feature feels intelligent while proprietary internals stay protected.

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.