Load
Your data
Connectors or approved imports bring in emails, cookies, events, CRM rows, tickets, billing, documents, and outcomes.
Store
The trail
Scout keeps ordered attribution paths in your estate (PostgreSQL/pgvector for proof). Fortress moves heavy load into Rust and LanceDB.
Match
Past outcomes
The Rust engine compares the current path with similar journeys that converted, retained, escalated, delayed, or lost.
Return
A task brief
Checked JSON with top examples, confidence, caveats, and ranked next steps for the goal you asked about.
Explain
Your model or team
Your approved model can explain the brief. It does not invent the plan. Elite covers the leadership walkthrough when needed.
Relationship Pilot Estimator
Select a customer or investor scenario, tune the assumptions, and turn the result into a governed pilot agenda with source systems, relationship reuse, confidence, JSON handoff, and next-best-task value on the table.
Current estimate
Hours saved
313.7/mo
Direct workflow reduction plus relationship reuse.
Impact score
17,854
Monthly planning score from effort reuse and risk assumptions.
This is a scoping estimate. It excludes commercial terms, implementation effort, customer validation effort, procurement, hosting, support, and any unproven production dependency.
Buyer spark
The estimator should make the conversation feel concrete. Which team, which workflow, which signals, which outcome, and what would a better next task be worth?
The buyer stops debating generic AI and starts naming the first valuable workflow.
The investor sees a commercial path from Scout proof to Fortress and Elite expansion.
The walkthrough starts with assumptions everyone can challenge instead of vague transformation language.
Scenario Selection
Source Systems and Product Path
Support leaders, customer success, operations teams
Source-system focus
CRM, support cases, product telemetry, knowledge documents
Connector status
Connectors scoped during walkthrough with customer-controlled credentials
Product path
Free open-source Scout for the first local PostgreSQL/pgvector relationship-analysis workflow, Enterprise/Fortress when private connectors, Rust/LanceDB analysis, and governance matter
Before
A support lead opens the CRM, ticket system, product notes, and old handover threads before they can explain why a customer is stuck.
After
Schema-validated execution packet gives the model the customer, entitlement, recent issues, attribution path, source provenance, confidence, similar saved/lost pattern, and safest next task to review.
Default basis
Editable Assumptions
Estimate Output
Monthly hours saved
313.7
272.8 direct hours plus 40.9 evidence reuse hours.
Relationship reuse score
2,250.5
45% reuse assumption at 3 minutes each.
Risk reduction score
600
10% of monthly risk exposure.
12-month impact score
214,247.6
Before implementation, procurement, hosting, and support assumptions.
Demo Agenda
The useful next step is not to defend a spreadsheet. It is to decide which pilot path can test the assumptions and make the relationship-analysis story real.
Defaults and limits
These defaults anchor the demo conversation, but the editable business assumptions above decide the estimated value.
Enterprise/Fortress local value path
This is a synthetic benchmark through real local ONNX embedding, LanceDB vector write, and L3 evidence synthesis. Customer-scale sizing is confirmed in a technical walkthrough.
Source: ENT-041 local benchmark evidence, 2026-05-29
Embedding shape
Useful for technical sizing conversations. Model choice, latency, and P95/P99 targets are confirmed for each deployment.
Source: ENT-041 local benchmark evidence, 2026-05-29
KynticAI product operations surface
Supports reviewed commercial onboarding without becoming the raw customer data plane.
Source: Product operations readiness material
Contact path
Requests are reviewed by KynticAI. Do not send secrets, credentials, source exports, or raw customer records in the form.
Source: Contact-form safety checks and request flow
Relationship-analysis scenario map
This maps source systems and relationship-analysis scenarios for buyer scoping; connector certification is handled per provider and customer environment.
Source: Data-plane connector docs, Enterprise connector/CNX docs, and local product-proof evidence, 2026-06-16
Assumptions
Clear limits
Next Step
Use the contact path to request a pilot, customer demo, or investor conversation. Do not send credentials, raw records, source exports, or sensitive material.
Product Reveals
These examples keep commercial conversations focused on product fit, source boundaries, and the first measurable workflow.
Commercial scenario - product fit, deployment shape, support need
No public pricing table needed
“Commercial conversations should start with product fit, source boundaries, deployment shape, and the first measurable workflow.”
Commercial scenario - one workflow, agreed sources, outcome measure
Scope the buyer properly
“A good pilot starts with one workflow and one next-best-task question, not a generic AI transformation promise.”
Commercial scenario - serious first conversation, deeper materials
Keep the conversation focused
“Investors and design partners need the product story first, then deeper materials when the fit is real.”