BLU GENAI
The AI connecting data to decisions
Blu is the purpose-built AI that sits across all six platform modules. Monitoring your operation, surfacing what needs attention, explaining its reasoning, and handling 80–95% of decisions automatically.
WHY BLU GENAI
Losing hours to everyday decisions? Blu handles it.
Planning teams are spending their best hours on work that should run itself. That's where Blu comes in, taking on the high-volume routine calls so your team's expertise goes where it makes the biggest difference.
Time returned to the team
When 80–95% of decisions run on automated planning, planners stop reviewing everything and start managing what matters.
Intelligence beyond your four walls
Blu draws on external signals conventional planning systems never see, so your team is always working with the full picture.
Confidence to act
Every recommendation comes with a clear explanation. Planning teams can trust it, verify it when they need to, and put their name on it.
WHAT BLU DOES
From conversation to orchestration
Blu shows the reasoning behind every decision it makes. Which signals drove it, why this quantity, and why now? Beyond explaining its thinking, Blu coordinates what happens next across your full planning operation. See it in action.
How it works
Forget general-purpose. Blu is purpose-built.
Our supply chain AI is designed from the ground up for the specific decision structures of planning operations. Built into proven workflows, and trained on the patterns and signals that drive supply chain performance.
Always on, always watching
Blu keeps a close eye on service levels, inventory positions, forecast accuracy, and supplier performance. All while watching external signals like weather patterns, freight conditions, and macroeconomic indicators, 24/7.
Only surfaces what matters
97.3% of Blu's automated recommendations are approved by users, and the number keeps climbing. The system continuously improves, learning which decisions need surfacing and filtering out the ones that don't.
Shows its thinking
Blu’s explainable AI tells you exactly what’s driving each recommendation, including which external signals are shifting demand or supply conditions. Data you can trust, decisions you can defend.
Handles the routine, automatically
Once Blu has monitored, surfaced, and explained, it acts. Handling the high-volume routine decisions automatically, so your team's expertise goes exactly where it should.
Proven Results
Better decisions, by the numbers
$18M
Decrease in average on-hand inventory
99.7%
Service level achieved
~99%
Forecast accuracy maintained
$4M
Transfer cost savings
AI-NATIVE BY DESIGN
Intelligence in every layer
AI runs through every aspect of our platform, our engineering, and our culture. Blu GenAI brings it to life, sitting across all six modules as the intelligence layer that ties them all together.
FAQS
Your questions, answered
Can’t find what you’re looking for? Reach out to our team and we'll get you the answers you need.
General-purpose AI is trained on broad datasets and adapted for specific use cases after the fact. Purpose-built AI is designed from the ground up for a specific domain, in this case supply chain planning. The difference shows up in the depth of domain knowledge encoded in the recommendations, the ability to incorporate supply-chain-specific signals like weather, freight markets, and supplier lead times, and the capacity to explain recommendations in supply-chain-literate terms that planners can act on with confidence.
In a well-configured supply chain AI environment, 80 to 95 percent of items can run on automated planning: forecasts generated, orders built, replenishment executed without manual intervention. The remaining 5 to 20 percent are the complex decisions, unusual patterns, and strategic calls that genuinely require human judgment. The goal isn't to replace planners — it's to return their time to the work that actually requires their expertise.
No. The most effective supply chain AI amplifies planning expertise rather than replacing it. When routine decisions run automatically, planners stop managing volume and start applying judgment where it genuinely matters: supplier relationships, strategic inventory positioning, cross-functional planning alignment, and response to conditions no model fully anticipates. AI changes what the planning role is capable of, not whether it's needed.
It depends on the system. General-purpose AI adapted for supply chain use typically can't explain its reasoning in supply-chain-specific terms. Purpose-built AI, designed from the ground up for supply chain decision structures, can decompose every recommendation into the specific factors driving it: which demand signals shifted, which external conditions changed, and what would be different if key assumptions moved. That explainability is what makes AI practical for planning teams who need to defend every decision they put their name on.
Blu draws on four data sources simultaneously. Your operational data: transaction history, inventory positions, supplier performance, and demand data from your ERP environment. External signals: weather patterns, freight market indices, and macroeconomic indicators like housing starts and industrial production data. Network and partner data: inventory positions across your distribution network and, through Connected Planning, signals from suppliers and buying group partners. And user interaction data: which recommendations were approved, overridden, or modified, so the system gets smarter with every planning cycle.
Blu is built for the reality that no model is perfect. Three mechanisms work together when conditions fall outside established patterns. First, phased autonomy: Blu escalates genuinely novel situations to planners rather than acting on low-confidence recommendations. Second, planner override: every recommendation can be reviewed, adjusted, and overridden, and the system learns from those decisions. Third, LifeLine backup: former supply chain practitioners proactively monitoring your operation provide the human judgment layer that sits alongside the platform's intelligence, particularly when conditions are genuinely unprecedented.
Customer Stories
Hear from the businesses making every decision count
“The ERP handles transactions. Blue Ridge handles the intelligence. That's the difference.”
Brad Smith
SVP, Procurement & Sales
Southwest Traders supplies national restaurant chains – Panera, Einstein, Starbucks, Panda Express – from a buying team of nine to eleven working on an AS/400 ERP. Blue Ridge cut order-build time from days to a few hours, held service levels at 99.95% across blue-chip customers, and let the company onboard new brands without adding to the planning team.
99.95%
Service level across national restaurant brands
~18.5
Days on hand
“Blue Ridge has been the most user-friendly, results-driven system that I've seen so far. Our whole planning and buying team absolutely loves it.”
Stephanie Hunn
Senior Manager, Planning
Before Blue Ridge, ISN was struggling to optimize fill rate and inventory turns simultaneously. The team evaluated multiple vendors and chose Blue Ridge for the onboarding, training, and ongoing system improvements baked into the relationship. They went live and saw measurable results from the first operating cycle forward – with the LifeLine team supporting every step.
~99%
Forecast accuracy maintained
50%
Improvement in fill rates over twelve months
“The goal wasn't just to reduce inventory. It was to have what we need, when we need it. That's exactly what Blue Ridge helped us do.”
David Mays
VP of Operations
West Virginia Electric Supply is an electrical distributor running eight branches on the Eclipse ERP. Centralizing inventory and moving to data-led replenishment let the team strip out the dead stock that had quietly accumulated for years – while service to contractors and customers held above 96% and the planning organization shifted from firefighting to forward-looking decisions.
70–80%
Reduction in dead stock
96.3%
Service level to contractors and customers
"Blue Ridge has the best interface and analytics you would need as a professional purchasing buyer"
Thelma Chavez
Director of Operations
Jackson Systems is a six-division HVAC distributor generating roughly $40M in annual revenue. Before Blue Ridge, the planning team reviewed every SKU manually – a process measured in days, not hours. Exception-based planning compressed that work, freed cash from excess stock, and pushed service levels into a range the team had never sustained before.
~$1M
Drop in inventory on hand
98.1%
Service level, up from 88%
