Bringg, a last-mile delivery software company, has launched Bringg Performance AI, a suite of AI products that helps retailers and logistics providers decide what to do today, next week, and next quarter. The company says it answers questions such as why an operation performs as it does, which are often handled with spreadsheets and gut feel. The suite has three parts. The Analyst finds structural problems in delivery data, traces their root causes, and suggests actions. Capacity Advisor compares booked orders against resources to flag capacity gaps up to seven days ahead. Both are limited to design partners, with general availability expected in early 2027. Predictive Time on Site, available now, predicts stop times for each route using a customer's own delivery history. Raymour & Flanigan says it lifted its on-time delivery rate from 85% to 88% and cut severe lateness by 20%.

Bringg introduces Performance AI, intelligence that works at the decision point, not the dashboard. New Bringg capabilities work at varying time horizons to give operators the insights and tools they need to make smarter last-mile decisions. CHICAGO - Bringg, the last-mile performance leader, today introduced Bringg Performance AI, a suite of AI products that moves last-mile intelligence from the dispatch screen to the decision-making point, giving retailers and logistics... November 3, 2026 at 6:03 a.m. New Bringg capabilities work at varying time horizons to give operators the insights and tools they need to make smarter last-mile decisions. CHICAGO - Bringg, the last-mile performance leader, today introduced Bringg Performance AI, a suite of AI products that moves last-mile intelligence from the dispatch screen to the decision-making point, giving retailers and logistics providers the diagnosis and foresight to act today, next week, and next quarter. Execution tools tell a last-mile operation what to do right now: route, dispatch, track. The higher-value questions - why an operation performs the way it does and what to change before a problem reaches a customer - have gone largely unanswered by software and handled instead with gut feel, spreadsheets, and periodic consulting. Bringg Performance AI is built for those questions. It is also the first step toward the open last mile Bringg is building over the coming years, but the products available today stand on their own operational value. "For years the industry treated software as the differentiator. It isn't anymore because new AI features are released every day," said Guy Bloch, CEO of Bringg. "What's scarce is intelligence capabilities that work at the decision-maker's altitude. Not another dashboard to read, but a diagnosis, a recommendation, and the confidence to act. That's what Bringg Performance AI gives our customers today, and it's the foundation for what we're building next." Performance AI at launch Bringg Performance AI spans three decision horizons: next quarter, next week, and today. The Analyst is a diagnostic layer that sits above day-to-day execution. It continuously examines an operation's delivery data, surfaces structural problems - such as chronic under-utilization, systematic planning bias, and carrier-selection inefficiencies, traces each to a root cause, and presents a short list of actions and trade-offs. Not a dashboard and not general analytics: every finding maps to a decision someone owns. Current availability limited to design partners, general availability expected early 2027. Capacity Advisor identifies potential capacity constraints by comparing booked orders against available resources and driver schedules for the upcoming week. For each finding, it recommends an adjustment, such as adding, shifting, or releasing resources, which planners review and approve within the existing workflow. Insights include: which teams and days are at risk of overbooking or underbooking, and skill shortages, where complex deliveries like installations or item handling exceeds the available crew. Current availability limited to design partners, general availability expected early 2027. "Capacity Advisor surfaces geolocation and capacity problems up to seven days out, so we're correcting them before they ever reach a customer's doorstep," said Brian Harvey, Product Manager, Raymour & Flanigan. "We used to size our daily resource needs on gut feel - now we plan against real numbers, which has trimmed our contractor usage and kept us from overbooking." Predictive Time on Site is a merchant-specific model that is available now, trained on each customer's own delivery history, that predicts each route's specific stop times instead of using flat time-on-site assumptions. Predictions use order attributes like item weight, destination, and day of week, to feed route plans directly, and are retrained when monitoring detects drift. Built for operations where stop duration varies widely, including big and bulky delivery and grocery. "Machine-learning time-on-site estimates moved our on-time delivery rate from 85% to 88% and cut severe lateness by 20%," said Brian Schwarz, Senior VP of Operations at Raymour & Flanigan. "At our delivery volume, that's thousands of homes a year where we hit the window we promised, and that's the part customers remember." About Bringg Bringg is the last-mile performance solution that turns every delivery into a business advantage for leading retailers and logistics providers. From checkout to doorstep, Bringg connects delivery execution to the revenue, cost, and risk outcomes behind profitable growth. A modular platform, suite of AI capabilities, and embedded expertise give operators the control to move the metrics that matter: cost, speed, capacity, and customer experience. Bringg also leads the open last mile, a shared delivery infrastructure model that puts the economics once reserved for the largest retailers within reach of every shipper. The result is last-mile performance that drives outcomes and scales with every delivery. Bringg. Scale Beyond. Media Contact: Tara Tate | Marketing at Bringg | [email protected]