Drivepoint raised a $7 million Series A in 2025, bringing its disclosed financing to more than $9 million to date. The round was led by Vocap Partners and included Good Friends VC’s consumer-founder syndicate, along with returning investors Bling Capital and Vinyl VC. Investors framed the raise as validation of Drivepoint’s traction with direct-to-consumer and multi-channel retail brands and as capital to accelerate product development and sales.
Austin Gardner-Smith remembers the month his first customer asked for something the spreadsheets could not deliver: a single place to run scenario planning across DTC, wholesale, and Amazon while still keeping the numbers flexible enough for a founder to tinker. Drivepoint looks to replace the brittle mix of Excel files, patchwork scripts, and delayed reports that many consumer brands rely on to make operational decisions. The aim was practical: reduce the hours finance teams spend reconciling data and increase the confidence around decisions that move inventory, marketing, and margins.
How Drivepoint models retail finance
Drivepoint presents itself as an AI-native, spreadsheet-friendly platform that stitches together retail channels, daily performance data, and forecasting models into one finance workflow. The product promises automated recurring forecast updates, scenario comparisons, and tear sheets that translate into profit-and-loss, balance sheet, and cash-flow projections. Integrations with retail and advertising platforms feed a modeling layer that is designed to be familiar to finance teams that prefer Excel while eliminating repetitive data plumbing.
Technically, the company pairs prebuilt retail reports and daily pacing algorithms with AI-driven forecast models intended to produce near-real-time projections. That combination is pitched as an alternative to either full migrations off spreadsheets or maintaining elaborate manual processes. The design reflects a deliberate tradeoff: preserve spreadsheet flexibility for founders and finance operators while automating the parts of the workflow that are most error-prone and time-consuming.
Funding and early outcomes
Investors in the Series A described the round as a signal that Drivepoint has demonstrated product-market fit among digitally native brands and can now scale sales into similar accounts. Emery Waddell of Vocap said, “Drivepoint is rapidly emerging as the default solution for intelligent finance in retail. The most forward-thinking retail brands are already running their finance operations on Drivepoint. Given the company’s track record of innovation, deep consumer brand expertise, and proven ROI for customers, it’s only a matter of time before the rest of the industry – including enterprise players – follows suit.”
Company materials cite measurable outcomes from early customers. Drivepoint reports an average 6.7 percent EBITDA uplift across customers in their first year on the platform. Case studies included in the materials present examples such as a direct-to-consumer brand that attributes $4 million in incremental EBITDA to scenario planning enabled by Drivepoint, another that credits a 3 to 5 percent gross margin improvement, and a small business that said automated modeling let a one-person finance team manage rapid growth. These figures are drawn from company-supplied case studies and investor communications rather than independent third-party audits.
Austin Gardner-Smith framed the goal in outcome terms and tied it to the new financing. He said, “On average, Drivepoint customers see 6.7% gains in EBITDA in their first year on the platform, which can unlock massive enterprise value for a retail brand. This capital will let us scale those outcomes and help even more brands grow with clarity and confidence.”
Drivepoint’s early go-to-market is focused on single-brand retailers and DTC companies that run multiple sales channels, including marketplaces and wholesale. The product’s spreadsheet-native surface appears built to reduce adoption friction among finance teams that are culturally attached to their models. The immediate commercial task is to translate those early case studies into repeatable wins at a larger scale and to meet procurement, security, and reporting requirements for bigger customers.
Drivepoint’s value proposition is concrete in the materials it distributes: stitch data pipelines, automate recurring forecasts, and hand operators timely pacing and scorecards. The longer test will be whether those claims verify consistently across a broader and more diverse set of retailers and whether the company can sustain unit economics as it chases larger enterprise accounts.
