Selected Salesforce and enterprise AI architecture engagements — problem, constraints, decisions, and measurable outcomes.
Recent Work
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Customers Wanted a Human. We Changed AI’s Role.
Read case study: Customers Wanted a Human. We Changed AI’s Role.A case study in using AI to support effective customer meetings, from the first request to the final follow-up. Imagine calling your lawyer or doctor about something that worries you. You want to explain what happened, ask questions, and speak with someone who understands your situation. Instead, you receive an AI-generated answer. Even if it…
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Optimizing Salesforce Token Consumption
Read case study: Optimizing Salesforce Token ConsumptionCut Agentforce token waste by replacing repetitive conversational lookups with dashboards and tightening agent scope to intended use cases.Problem: Agentforce billing is metered per action against a fixed token allowance, and it isn’t obvious where an implementation’s token spend is going or how to reduce it without guessing.Result: Replacing a repetitive agent lookup with a…
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How to Use Agentforce Grid to Find and Resolve Duplicate Cases
Read case study: How to Use Agentforce Grid to Find and Resolve Duplicate CasesA practical walkthrough using Prompt Builder, Flow, and a spreadsheet-style AI workspace. If you have ever solved a bulk AI problem by exporting records, running a script, and loading the results back into Salesforce, Agentforce Grid will feel familiar – but much more direct. It is a spreadsheet-style workspace in which every record is a…
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Building OnboardingMate: A Salesforce Agentforce Assistant for Employee Onboarding
Read case study: Building OnboardingMate: A Salesforce Agentforce Assistant for Employee OnboardingOnboardingMate is an AI-powered Salesforce onboarding assistant that creates role-based tasks, tracks progress, answers grounded questions, and resolves blockers through a guided conversation.