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.

Review Product Proof

Use-Case Ideas

What becomes possible when authorised data becomes relationship intelligence.

Ten scoped scenarios that show where governed relationship analysis could help. They are product ideas, not live customer proof or production deployment claims.

Opportunity spark

The best idea is the one where the data already exists and the pain is already expensive.

This page should help buyers spot themselves quickly: which workflow has scattered signals, pressure to act, and a clear outcome that would make better recommendations valuable?

Choose the First Use Case

Sales sees conversion opportunities hiding in web, email, and CRM trails.

Support sees churn pressure before the renewal conversation is already damaged.

Operations sees the constraint behind the noise before another meeting starts.

01

B2B SaaS enquiry conversion

Recommend the next task for testname@test.com.

Link email enquiry, page A search, product B interest, account registration, CRM contact, opportunity, support ticket, product usage, billing status, and converted/not-converted outcome relationships inside the customer data plane.

Relationship Facts

conversionProbabilitysimilarConvertedPatternrecommendedNextTask

Data Sources

Email EngagementWebsiteCRMSupportUsageBillingOutcome Store
02

Ecommerce abandoned basket

Recover with the evidence, not with a generic discount.

Use basket contents, search term, delivery question, commercial-intent page visit, support history, registration status, and prior recovered/lost basket outcomes to recommend the next recovery action.

Relationship Facts

basketRecoveryProbabilitydeliveryConcernSignalrecommendedRecoveryAction

Data Sources

StorefrontSearchCommercial Intent PageSupportAccount RegistrationOutcome Store
03

Support churn prevention

Fix the blocker before asking for renewal.

Combine ticket severity, open support threads, usage drop, billing status, meeting history, and similar saved/lost account outcomes to recommend a retention action.

Relationship Facts

retentionRiskPatternsupportDragrecommendedHumanEscalation

Data Sources

Support DeskProduct UsageBillingCRMEmail EngagementOutcome Store
04

Healthcare operations scheduling

Non-clinical operations only, with synthetic data.

Use synthetic rota, bed-flow, equipment, transport, supply, and service-desk signals to recommend an operational scheduling review. No clinical, diagnostic, treatment, or patient-specific claim is made.

Relationship Facts

operationsPressurestaleSourceCaveatrecommendedSchedulingReview

Data Sources

Rota SystemEquipment RegisterTransport DeskSupply QueueService Desk
05

Recruitment candidate matching

Explain why a candidate resembles previous successful placements.

Link candidate skills, role requirements, interview feedback, availability, salary range, recruiter notes, and placement outcomes to produce a reviewer-owned shortlist rationale.

Relationship Facts

candidateFitEvidencesimilarPlacedPatternshortlistRationale

Data Sources

ATSInterview NotesRole BriefAvailabilityCompensation RangePlacement Outcomes
06

Finance customer retention

Customer-service next action without regulated advice claims.

Combine support interactions, product usage, billing queries, contact preference, and service outcomes to recommend a retention-service action. The workflow avoids investment, credit, or insurance advice.

Relationship Facts

retentionServicePatterncontactPreferenceserviceNextAction

Data Sources

CRMSupportUsageBillingCommunication PreferenceOutcome Store
07

Manufacturing quality response

Recommend the next inspection action from exact production evidence.

Link batch data, machine telemetry, supplier record, support complaint, inspection outcome, and similar defect patterns to recommend the next human-reviewed inspection step.

Relationship Facts

defectSimilarityPatternsupplierQualitySignalrecommendedInspectionAction

Data Sources

MESMachine TelemetrySupplier QualitySupport ComplaintsInspection Outcomes
08

Logistics delivery recovery

Show the relationship between route pressure and customer outcome.

Combine route status, depot capacity, support ticket, account value, delivery promise, and similar successful recovery outcomes to recommend the next customer update.

Relationship Facts

deliveryRiskPatterncustomerImpactWeightrecommendedServiceUpdate

Data Sources

Route SystemDepot PlanningSupportCRMDelivery PromiseOutcome Store
09

Professional services account brief

Prepare the client meeting with governed relationship analysis.

Link project health, invoice status, support issues, stakeholder email engagement, upcoming renewal, and similar expansion/loss outcomes before a quarterly review.

Relationship Facts

accountReviewRelationshipsexpansionSimilarityrecommendedMeetingAgenda

Data Sources

Project SystemBillingSupportEmail EngagementCRMOutcome Store
10

Public-sector operations brief

Separate operational evidence from policy or clinical decision claims.

Use synthetic workload, queue, asset, staffing, service request, and resolution data to recommend an operational review path with strict source, role, and purpose controls.

Relationship Facts

operationsRelationshipPackconfidenceCaveatrecommendedReviewPath

Data Sources

Workload QueueAsset RegisterRotaService RequestsResolution Outcomes

Which relationship-analysis workflow should we scope first?

Use this page as a menu for a scoped relationship conversation. We will only discuss scoped paths that fit the current relationship architecture and your data boundary.

Scope Relationship PilotReview Product ProofRequest Technical Walkthrough

Evidence Results

Good use cases start where a team already has signals and pressure.

These examples help turn field notes and ideas into a measurable Context Engine workflow.

KynticAI Result
Use Cases

Ideas scenario - conversion, retention, recovery, operations

Find the first valuable workflow

“The best use cases are not generic AI demos. They are pressure points where the company already has signals but no relationship layer.”
KynticAI Result
Sales Ideas

Ideas scenario - enquiry, web event, product interest, conversion

Convert more moments with evidence

“Sales use cases work when an email, cookie, product page, account state, and prior outcome can become one relationship path.”
KynticAI Result
Operations Ideas

Ideas scenario - service pressure, asset signal, capacity constraint

Make operational pressure actionable

“Operations use cases work when scattered signals point to one next human-owned review path.”