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How we solve real Salesforce problems

Below are representative examples of the work we do — the kind of challenges growing teams bring us, how we scope and solve them, and the outcomes our approach is built to deliver. As we publish named client stories with their permission, they'll appear here too.

About these examples: the engagements below are illustrative — representative of the problems we solve and the results our approach is designed to achieve. Figures shown are target outcomes for that type of project, not a specific client's audited results. Want a reference from a live project? Just ask.
Case study: Automating complex insurance claims with Agentic AI — Insurance, 4-week pilot

Automating complex insurance claims with Agentic AI

The challenge

A regional insurance carrier was spending 5–7 days on a single claim — manual policy-document review, claimant verification, damage assessment, and fraud screening across several disconnected systems. The result was delayed payouts, high operating cost, and slipping customer satisfaction.

The solution

An Agentic AI system inside Salesforce, built from specialized autonomous agents:

  • Research Agent — interprets policy & regulatory documents
  • Data Validation Agent — cross-references claimant data against internal and external sources
  • Assessment Agent — uses computer vision on damage photos and repair estimates
  • Orchestrator Agent — runs the workflow and escalates edge cases to a human

Built on Einstein GPT, custom Apex agents, and external data integrations — piloted first on auto claims.

Outcomes this approach targets

~85% faster (7 days → ~1 day) 40% lower manual cost 95%+ first-pass accuracy 30% CSAT lift
Case study: Health Cloud integration for a multi-clinic network — Healthcare, ~10 weeks

Health Cloud integration for a multi-clinic network

The challenge

Patient data scattered across multiple clinic systems created gaps in care continuity and delays in follow-up. Staff leaned on manual spreadsheets and disconnected EMR exports, making it hard to track patient interactions or referrals across locations.

The solution

A Salesforce Health Cloud build to centralize patient data and automate care coordination:

  • Flow automation turns referral records into task assignments for physicians and care coordinators
  • Every patient gets timely, tracked outreach — nothing falls through
  • Health Cloud dashboards surface follow-up rates, appointment backlogs, and referral outcomes for leadership

Outcomes this approach targets

Unified patient profiles across clinics ~25% faster care coordination Tighter front-office / nurse / physician comms
Case study: Education Cloud for a private university's admissions — Education, ~8 weeks

Education Cloud for a private university's admissions

The challenge

Admissions and enrollment ran on spreadsheets and disconnected systems, causing application-processing delays, inconsistent outreach to prospective students, and little visibility for leadership into where things stood.

The solution

An Education Cloud environment that consolidates applicant data and automates the workflow:

  • Salesforce Flows move applications through each stage automatically
  • An Experience Cloud student portal guides applicants from first submission to final enrollment
  • Automated alerts and task routing keep counselors on top of every applicant
  • Real-time dashboards track application metrics and flag bottlenecks

Outcomes this approach targets

Up to 40% faster application processing Centralized applicant data Better admissions / academic collaboration
Case study: A scalable CRM for a fast-growing SaaS sales team — SaaS, ~6 weeks

A scalable CRM for a fast-growing SaaS sales team

The challenge

A fast-scaling SaaS company had outgrown its CRM. Regional teams kept their own lead spreadsheets, reps worked from stale data, forecasting was inconsistent, and executives had no clear pipeline view. The root problem was fragmentation — leads, renewals, and trials all living in different tools.

The solution

Discovery workshops mapped the full lead-to-revenue flow, then we re-architected Sales Cloud for clarity and automation:

  • Standardized lead-qualification stages with custom Path guidance
  • Automated lead routing by territory and deal size
  • Flow-based follow-up and renewal reminders (renewals auto-created 90 days out)
  • Dynamic dashboards for reps, managers, and executives; validation rules to stop incomplete data

Outcomes this approach targets

45% faster lead-to-opportunity conversion 30% higher CRM adoption Unified real-time forecasting Zero duplicate leads

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