Advenno built OrderFlow, a unified order management system that consolidates in-store, online, mobile, delivery, and catering orders into a single kitchen workflow. For Savory Restaurant Group's 48 locations, OrderFlow reduced errors by 67%, grew ticket size by 23%, and cut fulfillment times by 41%.
The Challenge
Savory Restaurant Group had scaled aggressively, growing from 12 locations to 48 across Texas, Oklahoma, and Louisiana in just four years. Each acquisition and new build brought whatever technology the local general manager preferred, creating a patchwork of five different POS systems across the portfolio. When third-party delivery exploded during the pandemic, the company onboarded DoorDash, Uber Eats, and Grubhub — but each platform required its own tablet at the counter, and orders had to be manually transcribed into the POS for kitchen preparation and accounting. During peak lunch rushes, a single location might have staff juggling the POS terminal, three delivery tablets, a ringing phone for catering orders, and a line of in-store customers — a chaos that predictably produced errors. The 14% order error rate wasn't just a customer satisfaction problem; it translated directly to $620K in annual comps, refunds, and wasted food. Average fulfillment times during peak hours had ballooned to 22 minutes, well above the 15-minute fast-casual benchmark that customers expected. Meanwhile, the digital ordering process offered no intelligent upselling — no suggested add-ons, no combo recommendations, no personalization — leaving an estimated $1.2M in annual incremental revenue uncaptured. The company's CFO calculated total annual revenue leakage from errors, missed upsells, and incorrect third-party commission reconciliation at $1.8M, making the technology gap one of the largest addressable P&L opportunities in the business.
- 14% order error rate resulting in $620K annual costs from comps, refunds, and food waste
- 5 different POS systems across 48 locations with no centralized management or reporting
- Three separate delivery platform tablets per location requiring manual order re-entry into POS
- 22-minute average fulfillment time during peak hours — 47% above the fast-casual benchmark
- No AI-powered upselling or personalization in digital ordering channels, leaving $1.2M in annual revenue uncaptured
- Catering orders taken by phone and handwritten on paper tickets with no digital record or tracking
Our Solution
Advenno built OrderFlow as a cloud-native platform using a microservices architecture designed for the high-throughput, low-latency demands of restaurant operations. The core innovation is a universal order ingestion layer that connects to every ordering channel through dedicated adapters — Square and Toast POS integrations for in-store, a white-label mobile app and web ordering portal for direct digital orders, API integrations with DoorDash, Uber Eats, and Grubhub for third-party delivery, and a purpose-built catering portal for advance large-order management. Every order, regardless of source, flows into a unified queue displayed on networked kitchen display systems (KDS) installed at each station. An intelligent routing engine analyzes each order's composition, prep complexity, station assignments, and promised delivery time to sequence the kitchen queue for maximum throughput — reducing bottlenecks at high-demand stations during rush periods. The AI upsell engine, trained on 2.3 million historical orders, analyzes the current cart, time of day, location-specific bestsellers, and individual customer history (for logged-in users) to suggest relevant add-ons that have generated a 23% increase in average ticket size. Real-time inventory tracking monitors stock levels across all locations, automatically removing sold-out items from every ordering channel simultaneously and alerting managers when reorder thresholds are approaching. A manager dashboard provides real-time operational metrics — ticket times, error rates, channel mix, labor efficiency — across all 48 locations from a single interface.
- Universal order ingestion from POS, mobile app, web, DoorDash, Uber Eats, Grubhub, and catering portal
- Intelligent kitchen routing engine that sequences orders by complexity, station, and promised time
- AI upsell recommendations trained on 2.3M orders that increased average ticket size by 23%
- Networked kitchen display systems replacing paper tickets at every prep station
- Real-time inventory tracking with automatic sold-out removal across all channels simultaneously
- Catering portal with advance scheduling, deposit collection, and automated kitchen prep timelines
- Manager dashboard with real-time metrics across all 48 locations from a single interface
Our Approach
Operations Immersion
We spent 2 weeks working inside 6 Savory locations during peak and off-peak hours, observing order flow from receipt through fulfillment. We documented 23 distinct failure points where orders went wrong, timed every step of the kitchen workflow, and interviewed 40 team members from cashiers to general managers to understand pain points from every perspective.
Channel Integration Architecture
Built a universal adapter layer that normalizes orders from 8 different sources into a single order schema. Worked directly with DoorDash, Uber Eats, and Grubhub technical teams to implement bidirectional API integrations that sync order status, eliminate manual entry, and reconcile commissions automatically against accounting records.
AI Upsell Engine Training
Analyzed 2.3 million historical orders to identify high-probability add-on combinations segmented by meal period, location, channel, and customer type. The recommendation model was A/B tested across 12 pilot locations for 4 weeks, with the winning variant showing a 23% ticket size increase versus the control group with no recommendations.
Kitchen Display System Deployment
Designed and deployed networked KDS hardware at all 48 locations, replacing paper ticket printers. Each KDS shows station-specific items with color-coded timing alerts, order source identification, and automatic progression as items are completed. Kitchen staff were trained through a gamified onboarding program that achieved 95% proficiency within one week.
Phased Rollout by Region
Rolled out OrderFlow in three regional waves — Texas (28 locations), Oklahoma (12 locations), and Louisiana (8 locations) — over 6 weeks. Each wave included on-site go-live support, a 72-hour command center for rapid issue resolution, and daily performance monitoring to catch and address any problems before the next wave.
The Results
OrderFlow eliminated the technology fragmentation that had been silently draining $1.8M from Savory Restaurant Group's annual revenue. Within four months of complete rollout, the order error rate dropped from 14% to 4.6% — a 67% reduction that eliminated $415K in annual comps and refunds. The AI upsell engine exceeded projections, driving a 23% increase in average ticket size that added $1.4M in incremental annual revenue across the 48-location portfolio. Average fulfillment time during peak hours fell from 22 minutes to 13 minutes, bringing Savory well within the fast-casual benchmark and earning noticeable improvements in customer satisfaction scores. The elimination of manual delivery platform re-entry didn't just reduce errors — it freed an estimated 12 labor hours per location per week, which managers redirected to customer-facing tasks and food quality. Third-party delivery commission reconciliation, previously a monthly nightmare requiring 40+ hours of accounting time, became fully automated with discrepancies flagged in real time. The manager dashboard gave regional and executive leadership unprecedented operational visibility, enabling data-driven decisions about staffing, menu optimization, and location performance. Savory's CEO credited OrderFlow as a key factor in securing a $15M Series B investment round, with investors specifically citing the operational technology platform as a competitive moat.
Return on Investment
Technologies Used
Integrations
OrderFlow is the single best technology investment we've ever made. Our kitchens went from chaos to clockwork, our ticket sizes jumped 23%, and I can see real-time performance across all 48 locations from my phone. It changed how we operate at every level.
Project Gallery
Lessons Learned
- Spending 2 weeks inside actual restaurant kitchens during peak hours was essential — many assumptions about workflow bottlenecks were wrong until observed firsthand
- The gamified KDS training program achieved 95% staff proficiency in one week versus the 3-week estimate for traditional training methods
- AI upsell recommendations needed careful tuning to avoid being annoying — subtle suggestions in context performed dramatically better than aggressive pop-ups
- Automating delivery commission reconciliation was an unexpected high-value feature that saved the accounting team 40+ hours per month
Summary
Advenno built OrderFlow, a unified order management system for Savory Restaurant Group's 48 fast-casual locations. The platform consolidates orders from POS, mobile, web, DoorDash, Uber Eats, Grubhub, and catering into a single kitchen workflow with AI-powered upselling. Results: 67% error reduction, 23% ticket size increase, and $1.8M in recovered revenue leakage.
Key Takeaways
- Universal order ingestion eliminated manual re-entry from three delivery platforms, saving 12 labor hours per location per week
- AI upsell engine trained on 2.3M orders drove 23% average ticket increase — the highest-ROI feature in the platform
- Kitchen display systems with intelligent routing reduced peak fulfillment time from 22 to 13 minutes
- Automated commission reconciliation replaced 40+ hours of monthly accounting work
- Phased regional rollout with on-site support ensured zero-downtime transitions for all 48 locations
Frequently Asked Questions
Key Terms
- Kitchen Display System (KDS)
- A digital screen used in commercial kitchens to display incoming orders, replacing paper ticket printers. KDS systems improve order accuracy, enable real-time tracking, and support station-specific routing.
- Order Ingestion Layer
- A software architecture component that receives orders from multiple channels (POS, mobile, web, third-party platforms) and normalizes them into a single standardized format for unified processing.
- Upsell Engine
- An AI-powered recommendation system that analyzes order composition, customer history, and contextual factors to suggest relevant add-on items that increase average order value.
Facts & Statistics
Sources & Citations
- National Restaurant Association 2025 Technology Report
- McKinsey: The Future of Restaurant Technology
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