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Seven Billion Architecture
ML OPTIMIZATION · MARGIN INTELLIGENCE

Predictive models that optimize complex supply & demand decisions.

We engineer production machine learning pipelines and constraint-based optimization engines that automate dynamic pricing, inventory allocation, and yield forecasting.

96.2%OTIF Delivery Rate
₹4.2 CrWorking Capital Saved
12 SolvedAI Recommendations
SOC 2 Type II Certified • VPC & Sovereign Cloud • Zero Data Retention
ENGINEERING DISCOVERY BRIEFING
Architect your solution.

Map your schema with our principal engineers. Receive a deterministic feasibility roadmap within 48 hours.

NDA-protected • 30-min call with senior engineers • No generic pitch
Pre-Integrated Across Your Enterprise Data Fabric
AI Manufacturing Analytics | Seven BillionRay / Anyscale
AI Manufacturing Analytics | Seven BillionMLflow
Scikit-learn
AI Manufacturing Analytics | Seven BillionONNX Runtime
Apache Kafka
AI Manufacturing Analytics | Seven BillionTimescaleDB
Kubernetes
AWS SageMaker
MEASURABLE OPERATIONAL OUTCOMES

Measure every yield curve before production.

Every optimization algorithm is bound to mathematical constraints and floor reality—not theoretical abstractions.

+18.4%
OTIF Delivery Lift
Restore on-time, in-full fulfillment rates across complex multi-facility distribution networks.
₹4.2 Cr
Working Capital Recovered
Dynamically adjust safety stock thresholds across warehouses based on real-time lead-time variance.
100%
Automated Exception Flagging
Surface supply shortages and production bottlenecks before they impact customer delivery windows.
DETERMINISTIC EXECUTION GRAPH

Autonomous workflows tailored to your enterprise schema.

Standard machine learning models fail in manufacturing and supply chain because they do not account for physical constraints—machine downtime, supplier lead-time variance, and shelf-life decay. We combine stochastic forecasting with mixed-integer linear programming (MILP) to generate actionable schedules.

Explore Workflow Architecture →
"The optimization engine solved our daily distributor allocation problem in 3 minutes. It previously took three senior planners 6 hours every morning."
Rajesh Sharma • Chief Operating Officer, Bharat Crunch Foods
seven-billion-opt://supply-demand-orchestrator
LIVE SIMULATION
Operator PromptResolve inventory deficit for Q3 Festive Season across Delhi & Mumbai fulfillment hubs.
Seven Billion Engine • 99.8% Confidence10 open critical exceptions identified. Generated 12 mathematically validated actions: expedite frying oil from Pune plant and reallocate 4,200 cartons from surplus Jaipur buffer.
SKU / Product LineDelhi DeficitOptimal SourceProjected OTIF
Classic Salted Crisps 150g-1,850 CasesReallocate from Jaipur HubResolved
Spicy Peri Peri Mix 200g-920 CasesExpedite Pune Plant Batch #4In Transit
Roasted Masala Peanut 100g-450 CasesLocal Distributor SwapMatched
Mathematical Optimization (MILP & LP)
High-performance linear and integer programming models using Gurobi, OR-Tools, and open solvers.
Google OR-ToolsGurobiSciPyPython
End-to-End MLOps Pipeline
Automated model retraining, feature store management, drift monitoring, and seamless canary rollouts.
MLflowKubeflowRayDocker
Real-Time Telemetry & IoT Ingestion
High-frequency streaming data pipelines processing factory sensors, PLCs, and telematics at scale.
TimescaleDBApache KafkaMQTTGrafana
Digital Twin & Monte Carlo Simulation
Simulate thousands of supply chain disruption scenarios to stress-test policies before production deployment.
SimPyNumPyC++PyTorch
PROPRIETARY ACCELERATORS

Proprietary Accelerators with Live Simulation

Experience our production-tested engines. Calibrated on enterprise supply chains with over 50,000 SKUs.

Demand & Supply Planning Accelerator

Multi-Echelon Optimization & Exception Management

Live Simulation • Bharat Crunch Foods Case
Try the Accelerator→
Demand & Supply Planning Accelerator
Open Exceptions
10 Critical
93% unserved forecast flagged
AI Recommendations
12 Solved
Expedite frying oil & reallocate
OTIF Recovery
+18.4%
Restored to 96.2% across hubs
Working Capital Saved
₹4.2 Cr
Idle safety stock reallocation
Interactive Model Available: Simulate factory bottlenecks, safety stock thresholds, and multi-echelon allocations live.
Launch Interactive Simulator →
ACCELERATOR
Dynamic Allocation Engine
Mixed-integer programming solver for multi-echelon inventory balancing under volatility.
96.2% OTIF Delivery
ACCELERATOR
Predictive Maintenance Forecaster
Sensor telemetry anomaly detection identifying equipment failure 72 hours before shutdown.
72h Early Warning
ACCELERATOR
Dynamic Pricing & Margin Optimizer
Elasticity-based price setting incorporating raw material input cost fluctuations.
+3.2% Margin Lift
EXECUTION BLUEPRINT

From schema audit to production in 6 weeks.

A battle-tested deployment framework designed to satisfy strict enterprise security clearances without slowing engineering execution.

01
Operational Audit & Constraint Formulation
Interview operations leaders, inspect plant constraints, catalog lead times, and construct mathematical objective functions.
Week 1–2
02
Algorithm Training & Historical Backtesting
Train optimization models against 2+ years of historical dispatch logs, benchmarking recommendations against human planner decisions.
Week 3–4
03
Pilot Simulation with Live Planners
Deploy accelerator in parallel with daily planning workflows, measuring user acceptance and constraint validity.
Week 5–6
04
Automated Execution & ERP Integration
Connect automated recommendations directly into SAP/Oracle purchase requisitions and warehouse transfer orders.
Week 7+
CASE STUDY · CONSUMER GOODS & MANUFACTURING
₹4.2 Cr
Working capital released while lifting OTIF delivery rate from 77.8% to 96.2%

How Bharat Crunch Foods eliminated supply chain blindspots across 6 manufacturing plants.

Rapid demand surges during seasonal peaks caused severe stockouts in regional distribution centers while excess inventory sat in central warehouses. Seven Billion deployed the Demand & Supply Planning Accelerator, which combined stochastic demand forecasting with mixed-integer allocation solving. The system resolved 10 daily critical bottlenecks in under 3 minutes, unlocking ₹4.2 Cr in idle working capital.

"The optimization engine solved our daily distributor allocation problem in 3 minutes. It previously took three senior planners 6 hours every morning."
Rajesh Sharma • Chief Operating Officer, Bharat Crunch Foods
FREQUENTLY ASKED QUESTIONS

Everything you need to know about deployment & security.

How does the Demand & Supply Planning Accelerator differ from ERP planning modules?−
Standard ERP planning modules rely on static formulas like safety stock reorder points that cannot adapt to real-time volatility. Our accelerator uses dynamic stochastic forecasting and mixed-integer programming (MILP) to evaluate 100,000+ combinations of routes, lead times, and capacity constraints in minutes.
Can the models handle unexpected supplier disruptions or sudden price spikes?+
How long does it take to calibrate the optimization engine on our historical data?+
Does the system require replacing our existing MES or ERP software?+
GET STARTED

The fastest path to custom AI built for your schema.

Schedule a 30-minute architecture discovery call with our principal engineers. We will map your highest-friction operational workflow and deliver an actionable technical blueprint.