Turn every support interaction into
reusable service knowledge
Your best knowledge already exists
The right answer often lives in a senior agent’s email, the closing notes of a difficult support case, or a recorded call where an expert finally found the fix.
Traditional knowledge programs depend on experts stopping their work to author and maintain articles, which keeps high-value operational knowledge tribal, fragmented, and difficult to scale.
Knowledge Miner turns the agent’s response into the authoring process powered by AI, converting resolved interactions into a continuously improving enterprise knowledge asset.
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1. Mine
Unlock hidden expertise
Continuously analyzes resolved interactions to find repeatable questions, decisions, fixes, and high-value exceptions.
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2. Prove
Validate before trust
Tests the same questions before and after a candidate is added, publishing only when the answer quality improves.
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3. Learn
Turn exceptions into assets
When AI escalates to a person, the final human resolution becomes a new candidate for the next similar request.
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A governed path to trusted knowledge from raw interactions
Circuitry.ai separates one-off context from reusable expertise, creates a useful knowledge asset, and proves that it improves answers before publishing.
What does the Miner create?
The output can be a concise Q&A, a troubleshooting article, a diagnostic sequence, a resolution playbook, parts or warranty guidance, a decision rule, or an escalation criterion.
Every asset remains linked to its source evidence and governance history.
Typical applicability metadata
What makes a candidate reusable?
• Likely to repeat and materially affect resolution, cost, risk, or customer experience.
• The resolution is verified by closure, outcome evidence, source material or expert agreement.
• The full pattern is present: question and context → cause or decision → action → result.
• It doesn’t duplicate or conflict with approved manuals, policies, warranty terms or existing knowledge.
• Permissions, privacy, retention, ownership and effective dates are clear.
Metadata turns similar text into relevant knowledge
Circuitry.ai identifies when an asset should apply and when it shouldn’t. Metadata like product hierarchy, symptom, policy version, customer or dealer context, confidence, and source relationships can populate the Service Knowledge Graph so AI Workers retrieve the right answer for the specific situation
Every human resolution makes the system smarter
When the Service Advisor doesn’t have enough evidence or confidence, it escalates. The expert response, final resolution, and outcome are captured as a new knowledge candidate, validated, and added only when they improve future answers.
Service knowledge that compounds business value
Turn hidden expertise into a compounding service advantage
Mine one high-volume support journey. Prove which new knowledge assets improve answers. Scale what works.