Salesforce support / case triage

SUPPORT OPERATIONS / CASE TRIAGE

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BrioBotCase triage with evidence and checks.

A Salesforce support workflow built to gather context, find product evidence, and prepare a review-ready case update.

Prior Brio team product experience. Not a Teregon client engagement.

Illustrative three-dimensional flow showing a support request passing through evidence and review gates — ILLUSTRATIVE WORKFLOW VISUAL

THE WORK / A CASE ARRIVES INCOMPLETE

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Support cases carry
more than a question.

SUPPORT CASEIllustrative record

Customer issueWater dispenser needs troubleshooting

ProductNeeds verification

Reason / sourceNot yet classified

Next actionAwaiting review

For e-commerce support, a person may need to connect the case, product details, policy, and attached images before the right action is clear.

The system was designed to prepare structured fields for a representative to inspect, while keeping the source material and checks close to the proposed update.

Illustrative case details. No customer record or product screenshot is shown.

THE WORKFLOW / FROM CASE TO PROPOSAL

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Gather first.
Propose second.

The model works inside a pipeline that gathers context, retrieves supporting material, and validates a draft before a person acts.

01INPUTCase contextSalesforce fields and conversation history
02RETRIEVEEvidenceProduct and policy material; attached images
03DRAFTProposed fieldsA model extracts and drafts a structured update
04CHECKValidationPython checks formats, allowed values, and records
05DECIDEHuman reviewA representative reviews before any write

Workflow summarized from prior Brio team implementation notes.

CONTROL / BOUNDED AUTOMATION

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The model proposes.
Rules protect the record.

Illustrative case workflow surrounded by verification rings

Evidence requiredUnsupported values are cleared instead of guessed.
Existing work preservedFields already completed by a person are not overwritten.
Explicit write boundaryThe model does not write to Salesforce; deterministic checks validate proposed fields.
Safe stopUncertain or invalid cases stop for human review; dry-run is the default.

Langfuse traces supported review of the workflow. This deck does not claim a production outcome or measured business impact.

WHAT THE CASE ESTABLISHES

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An engineering result,
not a revenue claim.

Evidence before fields

Product records and policy material inform the proposed case update.

Deterministic checks

Python rules validate values and protect the Salesforce write boundary.

Review stays visible

Dry-run, safe-stop, and tracing support inspection before action.

What we can supportWorkflow design · source retrieval · structured extraction · validation · human review

Prior team materials include offline evaluation work. No production accuracy, time-saved, cost, or revenue result is claimed here.

TEREGON LABS / APPLIED AI + SOFTWARE

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The useful part is
the whole workflow.

For a support team, the model is only one step. Useful automation connects the case system, product knowledge, validation rules, and the person responsible for the answer.

Map the current processConnect approved evidenceKeep writes boundedMeasure against a team baseline

Read the BrioBot case page ↗Explore Teregon Labs ↗

BrioBotCase triage with evidence and checks.

Support cases carrymore than a question.

Gather first.Propose second.

The model proposes.Rules protect the record.

An engineering result,not a revenue claim.