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 and Elite move 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, weights, confidence, caveats, and ranked task options for the question being asked.

Explain

LLM task brief

Fortress sends JSON to your chosen LLM. Elite can use KynticAI's on-prem open-source LLM path with no third-party token charges.

Back to case studies
Manufacturing / field operationsReliability lead

Asset downtime risk and predictive maintenance action

Sensor, spare-part, and technician signals drive a maintenance recommendation before downtime expands.

A production asset has a vibration threshold breach, rising temperature, critical spare-part shortage, and technician availability gap. Reliability needs a maintenance action before the issue becomes downtime.

Runtime Query

The scenario is run as a query against comparable relationship sets.

A production asset has a vibration threshold breach, rising temperature, spare-part shortage, and technician availability gap. What maintenance action should reliability take next to prevent downtime?

Run 2026-06-17-base-run / manufacturing-field-operations/query-results/urgent-risk-next-action.json

downtime_prevented

Primary outcome

Highest-ranked outcome from the runtime query result.

0.564

Best score

Runtime score for the primary action option.

3

Options

Primary plus alternative action options returned by the runtime.

Data Examples

  • Vibration threshold breach from condition monitoring
  • Bearing temperature rise over baseline
  • Critical spare-part stock warning
  • Qualified technician availability gap
  • Comparable downtime-prevention, spare-reservation, and technician-dispatch outcomes

Event Path

  1. 01vibration_threshold_breached
  2. 02temperature_rise_detected
  3. 03spare_part_stock_low
  4. 04technician_availability_gap
  5. 05maintenance_window_scheduled
  6. 06downtime_prevented

Scout Output

  • Runtime generated Scout-shaped data items for the domain.
  • Runtime generated Scout relationships and ordered attribution paths.
  • Domain manifest cross-checks the journey, event, and relationship-set counts.

Fortress Output

  • Runtime generated comparable relationship sets.
  • Runtime returned ranked action options with scores, confidence labels, outcomes, and supporting relationship-set IDs.
  • Runtime preserved synthetic-only and customer-data false caveats.

Ranked Outcomes

Fortress returns a primary recommendation and the credible alternatives.

Primary Recommendation

Reserve the critical spare, schedule a planned intervention window, and dispatch the qualified technician before automatic shutdown.

Outcomedowntime_prevented

ConfidenceHigh

Score0.564

This is a practical operations demo: relationship evidence becomes a maintenance plan with spare, schedule, and technician context.

Other Ranked Options

Option 2 - Low - score 0.1721

Reserve the critical spare and expedite replenishment before assigning the work order.

Expected outcome: spare_part_reserved

Option 3 - Low - score 0.1557

Dispatch the correctly certified technician with the diagnostic checklist before closing the alarm.

Expected outcome: technician_dispatched

Elite LLM Handoff

Explain the reduce_asset_downtime recommendation using the governed Fortress output and caveats.

governed_handoff:
  - Goal: reduce_asset_downtime
  - Primary path: downtime_prevented, score 0.564, high confidence
  - Supporting signals: planned_intervention, spare_part_shortage, technician_gap, temperature_rise, vibration_threshold_breach
  - Runtime relationship sets returned: 8
  - Domain journeys: 120; events: 520; relationship sets: 120

Outcome Prompt JSON

{
  "schema": "kynticai.elite.outcome-prompts.v1",
  "caseStudyId": "manufacturing-field-asset-risk",
  "domain": "Manufacturing / field operations",
  "stakeholder": "Reliability lead",
  "runtimeQuery": "A production asset has a vibration threshold breach, rising temperature, spare-part shortage, and technician availability gap. What maintenance action should reliability take next to prevent downtime?",
  "promptContract": "You are Elite, the KynticAI recommendation-writing layer.\n\nYou receive governed Fortress output, not raw customer data. Use only the supplied relationship-set facts, scores, confidence labels, alternatives, caveats, and outcome goal.\n\nWrite a decisive operational recommendation for the accountable team. Your output must include:\n1. Recommended action.\n2. Why this action is supported by the comparable relationship sets.\n3. What to do now.\n4. When to choose one of the alternative actions.\n5. What outcome to capture so the system improves.\n\nRules:\n- Do not invent facts outside the governed handoff.\n- Do not promise revenue, retention, clinical, legal, financial, safety, or compliance outcomes.\n- Do not apologise for using synthetic demo data.\n- Be commercially useful, specific, and direct.\n- Keep human review and claim boundaries visible where the domain requires them.",
  "governedFacts": [
    "Goal: reduce_asset_downtime",
    "Primary path: downtime_prevented, score 0.564, high confidence",
    "Supporting signals: planned_intervention, spare_part_shortage, technician_gap, temperature_rise, vibration_threshold_breach",
    "Runtime relationship sets returned: 8",
    "Domain journeys: 120; events: 520; relationship sets: 120"
  ],
  "outcomePrompts": [
    {
      "rank": 1,
      "outcome": "downtime_prevented",
      "action": "Reserve the critical spare, schedule a planned intervention window, and dispatch the qualified technician before automatic shutdown.",
      "confidence": "High",
      "score": "0.564",
      "prompt": "You are Elite, the KynticAI recommendation-writing layer.\n\nUse only the governed Fortress handoff below. Do not invent facts.\n\nCase study: Asset downtime risk and predictive maintenance action\nDomain: Manufacturing / field operations\nStakeholder: Reliability lead\nRuntime query: A production asset has a vibration threshold breach, rising temperature, spare-part shortage, and technician availability gap. What maintenance action should reliability take next to prevent downtime?\n\nGoverned facts:\n- Goal: reduce_asset_downtime\n- Primary path: downtime_prevented, score 0.564, high confidence\n- Supporting signals: planned_intervention, spare_part_shortage, technician_gap, temperature_rise, vibration_threshold_breach\n- Runtime relationship sets returned: 8\n- Domain journeys: 120; events: 520; relationship sets: 120\n\nCandidate outcome to explain:\n- Rank: 1\n- Outcome: downtime_prevented\n- Action: Reserve the critical spare, schedule a planned intervention window, and dispatch the qualified technician before automatic shutdown.\n- Confidence: High\n- Score: 0.564\n- Evidence summary: Comparable relationship sets ended in downtime_prevented and share signals such as planned_intervention, spare_part_shortage, technician_gap, temperature_rise, vibration_threshold_breach.\n- Supporting relationship sets: set-b9eebc3b76ab, set-30d87d158f4c, set-b7fa01947f62, set-dbd7e7183031, set-35bfbd1cb6b2\n\nWrite the operational recommendation for this outcome.\nInclude why the comparable relationship sets support it, what the team should do now, when this outcome should be chosen over the other ranked options, and what reviewed outcome must be captured next.",
      "expectedTextOutput": "Recommended action: Reserve the critical spare, schedule a planned intervention window, and dispatch the qualified technician before automatic shutdown.\n\nWhy this is supported: Fortress ranked downtime_prevented first with score 0.564 and high confidence. Comparable relationship sets ended in downtime_prevented and share signals such as planned_intervention, spare_part_shortage, technician_gap, temperature_rise, vibration_threshold_breach. The supporting relationship sets are set-b9eebc3b76ab, set-30d87d158f4c, set-b7fa01947f62, set-dbd7e7183031, set-35bfbd1cb6b2.\n\nWhat to do now: brief the reliability lead with the runtime query, the shared signals (planned_intervention, spare_part_shortage, technician_gap, temperature_rise, vibration_threshold_breach), and the exact action. Keep the action specific to this scenario rather than turning it into a generic campaign or workflow rule.\n\nWhen to choose an alternative: switch if the live evidence is closer to spare_part_reserved (Reserve the critical spare and expedite replenishment before assigning the work order.); technician_dispatched (Dispatch the correctly certified technician with the diagnostic checklist before closing the alarm.).\n\nOutcome to capture: record the action taken, the reviewed outcome, and any contradictory signal so the next Scout/Fortress comparison has stronger evidence."
    },
    {
      "rank": 2,
      "outcome": "spare_part_reserved",
      "action": "Reserve the critical spare and expedite replenishment before assigning the work order.",
      "confidence": "Low",
      "score": "0.1721",
      "prompt": "You are Elite, the KynticAI recommendation-writing layer.\n\nUse only the governed Fortress handoff below. Do not invent facts.\n\nCase study: Asset downtime risk and predictive maintenance action\nDomain: Manufacturing / field operations\nStakeholder: Reliability lead\nRuntime query: A production asset has a vibration threshold breach, rising temperature, spare-part shortage, and technician availability gap. What maintenance action should reliability take next to prevent downtime?\n\nGoverned facts:\n- Goal: reduce_asset_downtime\n- Primary path: downtime_prevented, score 0.564, high confidence\n- Supporting signals: planned_intervention, spare_part_shortage, technician_gap, temperature_rise, vibration_threshold_breach\n- Runtime relationship sets returned: 8\n- Domain journeys: 120; events: 520; relationship sets: 120\n\nCandidate outcome to explain:\n- Rank: 2\n- Outcome: spare_part_reserved\n- Action: Reserve the critical spare and expedite replenishment before assigning the work order.\n- Confidence: Low\n- Score: 0.1721\n- Evidence summary: Comparable relationship sets ended in spare_part_reserved and share signals such as purchase_order, replenishment_expedited, spare_reserved, stock_low.\n- Supporting relationship sets: set-f7ca03201aa7\n\nWrite the operational recommendation for this outcome.\nInclude why the comparable relationship sets support it, what the team should do now, when this outcome should be chosen over the other ranked options, and what reviewed outcome must be captured next.",
      "expectedTextOutput": "Alternative action: Reserve the critical spare and expedite replenishment before assigning the work order.\n\nWhy this route exists: Fortress returned spare_part_reserved at rank 2 with score 0.1721 and low confidence. Comparable relationship sets ended in spare_part_reserved and share signals such as purchase_order, replenishment_expedited, spare_reserved, stock_low. The supporting relationship sets are set-f7ca03201aa7.\n\nWhen to use it: choose this instead of the primary route when the live evidence matches purchase_order, replenishment_expedited, spare_reserved, stock_low more closely than the current top-ranked outcome.\n\nWhat to do now: make the action explicit for the reliability lead, preserve the caveat for this domain, and avoid inventing extra facts beyond the governed handoff.\n\nOutcome to capture: record whether spare_part_reserved happened and feed that reviewed result back into the relationship-set evidence."
    },
    {
      "rank": 3,
      "outcome": "technician_dispatched",
      "action": "Dispatch the correctly certified technician with the diagnostic checklist before closing the alarm.",
      "confidence": "Low",
      "score": "0.1557",
      "prompt": "You are Elite, the KynticAI recommendation-writing layer.\n\nUse only the governed Fortress handoff below. Do not invent facts.\n\nCase study: Asset downtime risk and predictive maintenance action\nDomain: Manufacturing / field operations\nStakeholder: Reliability lead\nRuntime query: A production asset has a vibration threshold breach, rising temperature, spare-part shortage, and technician availability gap. What maintenance action should reliability take next to prevent downtime?\n\nGoverned facts:\n- Goal: reduce_asset_downtime\n- Primary path: downtime_prevented, score 0.564, high confidence\n- Supporting signals: planned_intervention, spare_part_shortage, technician_gap, temperature_rise, vibration_threshold_breach\n- Runtime relationship sets returned: 8\n- Domain journeys: 120; events: 520; relationship sets: 120\n\nCandidate outcome to explain:\n- Rank: 3\n- Outcome: technician_dispatched\n- Action: Dispatch the correctly certified technician with the diagnostic checklist before closing the alarm.\n- Confidence: Low\n- Score: 0.1557\n- Evidence summary: Comparable relationship sets ended in technician_dispatched and share signals such as certified_technician, diagnostic_checklist, dispatch_completed.\n- Supporting relationship sets: set-baf64826ed77\n\nWrite the operational recommendation for this outcome.\nInclude why the comparable relationship sets support it, what the team should do now, when this outcome should be chosen over the other ranked options, and what reviewed outcome must be captured next.",
      "expectedTextOutput": "Alternative action: Dispatch the correctly certified technician with the diagnostic checklist before closing the alarm.\n\nWhy this route exists: Fortress returned technician_dispatched at rank 3 with score 0.1557 and low confidence. Comparable relationship sets ended in technician_dispatched and share signals such as certified_technician, diagnostic_checklist, dispatch_completed. The supporting relationship sets are set-baf64826ed77.\n\nWhen to use it: choose this instead of the primary route when the live evidence matches certified_technician, diagnostic_checklist, dispatch_completed more closely than the current top-ranked outcome.\n\nWhat to do now: make the action explicit for the reliability lead, preserve the caveat for this domain, and avoid inventing extra facts beyond the governed handoff.\n\nOutcome to capture: record whether technician_dispatched happened and feed that reviewed result back into the relationship-set evidence."
    }
  ]
}

Elite Textual Recommendation

Recommended action: Reserve the critical spare, schedule a planned intervention window, and dispatch the qualified technician before automatic shutdown.

Why this is supported: Fortress ranked downtime_prevented first with score 0.564 and high confidence. Comparable relationship sets ended in downtime_prevented and share signals such as planned_intervention, spare_part_shortage, technician_gap, temperature_rise, vibration_threshold_breach. The supporting relationship sets are set-b9eebc3b76ab, set-30d87d158f4c, set-b7fa01947f62, set-dbd7e7183031, set-35bfbd1cb6b2.

What to do now: brief the reliability lead with the runtime query, the shared signals (planned_intervention, spare_part_shortage, technician_gap, temperature_rise, vibration_threshold_breach), and the exact action. Keep the action specific to this scenario rather than turning it into a generic campaign or workflow rule.

When to choose an alternative: switch if the live evidence is closer to spare_part_reserved (Reserve the critical spare and expedite replenishment before assigning the work order.); technician_dispatched (Dispatch the correctly certified technician with the diagnostic checklist before closing the alarm.).

Outcome to capture: record the action taken, the reviewed outcome, and any contradictory signal so the next Scout/Fortress comparison has stronger evidence.

Generated Elite Action Brief

  1. 01Recommended action: Reserve the critical spare, schedule a planned intervention window, and dispatch the qualified technician before automatic shutdown.
  2. 02Evidence: Comparable relationship sets ended in downtime_prevented and share signals such as planned_intervention, spare_part_shortage, technician_gap, temperature_rise, vibration_threshold_breach.
  3. 03Primary action: Reserve the critical spare, schedule a planned intervention window, and dispatch the qualified technician before automatic shutdown.
  4. 04Primary expected outcome: downtime_prevented
  5. 05Alternatives: spare_part_reserved: Reserve the critical spare and expedite replenishment before assigning the work order. | technician_dispatched: Dispatch the correctly certified technician with the diagnostic checklist before closing the alarm.
  6. 06Capture the reviewed outcome and feed it back into the relationship-set evidence.

Reviewed outcome loop

  • Capture which ranked action was taken.
  • Record whether the expected outcome happened.
  • Feed the reviewed outcome back into the next relationship-set comparison.

Boundary

Synthetic manufacturing demo only. It is not live plant telemetry, safety certification, or autonomous control proof.

Evidence Results

Case studies show the same relationship engine in different workflows.

These examples help buyers recognise the pattern in their own sales, support, operational, or governance data.

KynticAI Result
Case Studies

Runtime pack - multiple domains, one relationship-analysis pattern

Recognise your own workflow

The case studies prove the same product chain across ecommerce, logistics, legal, manufacturing, education, healthcare operations, and professional services.
KynticAI Result
Elite Output

Runtime pack - governed JSON to text recommendation

See the model explain evidence

Each case shows how Elite turns governed Fortress JSON into a clear operational recommendation.
KynticAI Result
Outcome Capture

Runtime pack - feedback into relationship memory

Turn examples into a learning system

Each case ends by asking what outcome should be captured so the recommendation loop improves.