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        <h1>Case Studies</h1>
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            <span class="badge badge-sample">Sample &amp; illustrative</span>
            The examples below are representative scenarios that illustrate the type of engagements and outcomes we deliver &mdash; not disclosures of a specific client's confidential results. <a href="about.html">Contact us</a> to discuss what's realistic for your business.
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                <h3>Retail Chain: From Five Spreadsheets to One Trusted Dashboard <span class="metric">70%<span class="metric-label">less manual reporting time</span></span></h3>
                <p><strong>Challenge:</strong> A multi-location retailer's weekly executive report was built by hand from five disconnected spreadsheets, taking a full day and frequently containing errors.</p>
                <p><strong>Solution:</strong> We modeled the underlying POS and inventory data in Power BI, built a governed semantic model, and enabled Fabric Copilot so leadership gets an automatic plain-English summary alongside every report.</p>
                <p><strong>Result:</strong> The weekly report now refreshes automatically and generates its own narrative, cutting manual prep time by roughly 70% and eliminating recurring reconciliation errors.</p>
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                <h3>Distributor: Automated Detection Catches a Pricing Error <span class="metric">$250K<span class="metric-label">in flagged cost savings</span></span></h3>
                <p><strong>Challenge:</strong> A distributor suspected margin erosion on a product line but couldn't pinpoint the cause across thousands of SKUs and vendor invoices.</p>
                <p><strong>Solution:</strong> We built a Fabric-based cost-analysis model and applied a custom insight engine to automatically flag unusual vendor pricing patterns.</p>
                <p><strong>Result:</strong> The model surfaced a systematic vendor overcharge that manual review had missed for months, representing an estimated $250K in identified savings.</p>
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                <h3>Professional Services Firm: Self-Service Sales Insights <span class="metric">3 weeks<span class="metric-label">kickoff to live dashboard</span></span></h3>
                <p><strong>Challenge:</strong> A growing services firm's sales team had no shared view of pipeline health and relied on the founder to manually compile updates.</p>
                <p><strong>Solution:</strong> We stood up a Microsoft Fabric lakehouse connected to their CRM, built a Copilot-enabled semantic model, and trained the sales team to ask questions of their own data in natural language.</p>
                <p><strong>Result:</strong> The team went from zero self-service reporting to a live, AI-assisted pipeline dashboard in three weeks, freeing the founder from being the reporting bottleneck.</p>
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            <h2 class="section-heading">Want to see the AI side of this in action?</h2>
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