AI & automation practice
AI agents and workflows that remove manual work without adding new fragility.
Agentforce and custom AI workflows, grounded in the same Salesforce and Java systems we build — not a bolted-on chatbot that can't see your actual data.
What this covers
Agentforce agent design — topics, instructions, and actions scoped to a job your team actually does
Grounding agents in your real data, not a generic knowledge base, using Data 360 and your existing Salesforce objects
Custom AI workflows outside Salesforce — Java services calling LLM APIs for document processing, triage, and summarization
Human-in-the-loop design for anything with real business or compliance risk attached
Testing and monitoring agent behavior before it touches production data, not after
How we think about automation
Automate the task, not the org chart
We start from a specific, recurring task someone dreads doing — not a mandate to "add AI somewhere." Scope creep here is how automation projects become expensive science experiments.
Grounded beats clever
An agent that's right 95% of the time and honest about the other 5% is worth more than one that sounds confident and is occasionally wrong in ways nobody catches.
Fragility is the real cost
The failure mode we design against isn't "the AI is dumb" — it's a workflow that breaks silently when an input changes shape. Error handling and fallbacks are part of the build, not a phase two.
In practice
Where this has shipped
Field Service Operations
Visualizing Field Service Capacity with a Zero-Cost Mapping Layer
Challenge
Dispatchers had no way to visually compare technician supply against appointment demand across service territories — just manual report cross-referencing, with no proactive way to catch understaffed regions before service levels suffered.
Approach
Built a custom Apex service layer aggregating technician counts and appointment volume per territory, rendered through a Lightning Web Component using Leaflet.js and OpenStreetMap — an open-source mapping stack that validated the concept with zero licensing cost.
Energy & Utilities
Automating Commission Import & Split Calculation
Challenge
An energy management firm processed monthly commission payments from multiple suppliers, each in a different CSV format, splitting them by hand across the client, up to three agents, and their own margin — slow, error-prone, with no audit trail or duplicate protection.
Approach
Delivered a custom Lightning Web Component with an Apex service layer that parses any supplier CSV format automatically, matches records to Salesforce via MPAN/MPRN, calculates every commission split server-side, and enforces a two-phase review-then-approve flow with duplicate protection at both the application and database level.