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Building the Operating System for Scaled Growth

How a fast-growing functional beverages brand turned scattered data and stretched processes into a single, OKR-driven operating rhythm.


Engagement Snapshot


The Situation

The company had earned its growth. Its products sat on shelves nationally, its direct-to-consumer base was expanding, and annual revenue had crossed $25M with momentum behind it. Growth of that speed carries its own tax. Data lived in separate systems for finance, sales, marketing, operations, and fulfillment, and no two teams read the same numbers the same way. Reporting was manual and lagged reality. Decisions rested on partial pictures, and the leadership team spent more energy reconciling figures than acting on them.

The brand needed an operating system that could hold up under scale: one shared set of goals, one source of truth, and a cadence that turned strategy into weekly execution.

The Engagement

Virgent AI came in as a full-service strategy and AI development partner, embedded across the leadership team rather than parked in an advisory seat. The work spanned facilitation, operating design, product management, hands-on software development, and capital markets support on an active raise. Every workstream pointed at one outcome: durable systems and processes that let the company keep growing without losing control of its numbers.

What We Did

The Dashboard

The dashboard is built around the OKRs rather than around the tools underneath it. Vision and mission stay pinned in view, and every metric maps to the objective and key result it serves, so a number always answers a question the leadership team already cares about. An embedded AI assistant lets executives interrogate the data in plain language, and a linked backlog keeps every planned improvement tied to a goal.

Under the surface it unifies more than sixteen live data systems, moving each source from manual pulls toward automated feeds on a phased schedule. It runs on a modern stack of Next.js and Vercel with a Postgres data layer and a multi-model agentic layer over MCP and API integrations, which is what lets the reporting scale as the business does.

Results


Systems Integration Architecture: One Dashboard, Every System

Each source below feeds specific objectives and key results, moving from manual reporting to automated integration on a phased schedule.

SystemCategoryStatusFeedsData ProvidedOwnerTarget
NetSuiteFinance / ERPmanualO1·KR2, O1·KR3, O1·KR4, +2Revenue, gross margin, net profit, cash, cost-by-customer, out-of-stock revenue loss and fill-rateFinance DirectorQ2
CamelotFulfillment Source of TruthplannedO3·KR1, O3·KR2, O3·KR4, +2Order events, OTIF split, inventory integrity, fulfillment errorsFulfillment DirectorQ2–Q3
Shopify / SkioDTC Commerce + SubscriptionsmanualO2·KR1, O2·KR2, O2·KR3Conversion, subscriptions, repeat rate, purchase eventsMarketing (CMO)Q2
ShipStationShipping ExecutionplannedO3·KR1, O3·KR3, O3·KR4Transit time, shipping cost, delivery exceptionsFulfillmentQ3
SPINSRetail IntelligencemanualO1·KR3, O2·KR4Velocity, retail performance, competitive movementSalesQ3
ConfidoDeductions & RecoverymanualO1·KR2, O3·KR4Disputes, deduction root cause, recovery trendFinance / FulfillmentQ2
Amazon Seller CentralMarketplace CommercemanualO1·KR5, O2·KR2Revenue, subscription, channel economicsMarketing / FinanceQ3

Why It Works

Strategy and software usually live in different vendors, and the handoff between them is where momentum dies. Virgent AI closes that gap. We facilitate the vision, structure the goals, install the operating cadence, and then build the systems that make all of it measurable—as one partner accountable for the whole outcome.

For a brand growing this fast, that combination is the point. The strategy is only as good as the data behind it, and the data is only useful if it maps to goals the whole company shares. This engagement delivered both, and left the business with an operating system built to carry its next stage of growth.


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