# nPlan - Supply Chain Planning Platform ## Complete Site Content for AI Crawlers > nPlan is a next-generation, cloud-based SaaS Supply Chain Planning platform. It powers up ERPs (SAP, TOTVS, Oracle, Dynamics) with integrated S&OP, S&OE, APS, MRP, and DRP. Official Siemens Xcelerator Marketplace Solution Partner. Website: https://www.nplan.digital Languages: English, Portuguese (BR), Portuguese (PT), Spanish Markets: Brazil, Latin America, Global Awards: Top 100 Open Startups, Top 5 Ind Tech Brasil --- # 1. PLATFORM MODULES ## 1.1 Demand Module Forecast and demand management with AI influence, collaboration tools, and statistical forecasting. - AI-driven demand forecasting with time series and external variables - Collaborative forecasting across sales, marketing, and operations - Statistical models with automatic best-fit selection - Demand sensing and bias correction ## 1.2 Inventory Module Automated inventory policy with ABC/XYZ segmentation, safety stock optimization, and financial simulation. - ABC-XYZ matrix with 9-segment differentiated policies - Safety stock calculation using 4 APICS formulas - Financial simulation of inventory investment - Stock health monitoring (coverage, turnover, aging KPIs) - Interactive calculator for safety stock computation (available on website) ## 1.3 Supply Module Integrated replenishment with BOM explosion, production and purchase order generation. - Multi-level BOM explosion - Automated production and purchase order generation - Supplier follow-up (FUP) tracking - Material pegging and traceability ## 1.4 Capacity Module Production planning with finite capacity constraint, labour/tool/storage constraints, and calendar simulation. - Finite capacity planning by resource, tool, and labor - Calendar simulation with shift patterns - Bottleneck identification and capacity leveling - What-if capacity scenarios ## 1.5 Orders Module Order management with multi-level synchronization, pegging, and automated order generation. - Multi-level order synchronization - Material pegging across production stages - Automated order generation from plans - Frozen/locked period management ## 1.6 Distribution Module Transport and distribution with logistics rules, transport constraints, and transfers management. - Distribution center replenishment planning - Transport constraint management - Logistics rules and routing - Inter-plant transfer optimization --- # 2. PRICING & PACKAGES ## Module Combos (pre-configured selections) - **nPlan for Forecast**: Demand module only - **nPlan for Operations**: Inventory + Supply + Capacity - **nPlan for Operations Advanced**: Inventory + Supply + Capacity + Orders - **nPlan for S&OP**: All 6 modules (Demand + Inventory + Supply + Capacity + Orders + Distribution) ## Packages ### Essentials ($) - Basic infrastructure, moderate volume - 2 users - 100 AI credits - Includes selected modules ### Pro ($$) - Advanced infrastructure, large volume - Up to 7 users - 500 AI credits - API Access - Single Sign-On (SSO) - Includes selected modules ### Premium ($$$) - Premium infrastructure with PRD and HML environments - Unlimited users - 2,000 AI credits - Everything from Pro, plus: - Private hosting available - Dashboard Creator - Advanced Automation - Intercompany / Multi-Plant capability - Includes selected modules All packages are modular: customers select which modules they need, then choose a package tier. Pricing is customized per customer via quote. --- # 3. CASE STUDIES — "Explore How We Transform Challenges into Solutions" ### 3.1 Elian (Textile | ERP: Consistem) Comprehensive supply chain planning solution integrated with Consistem ERP, optimizing inventory and capacity management to meet demand more efficiently. ### 3.2 Biotrop (Agro | ERP: Dynamics) Integrated planning solution focused on self-care products, with inventory and finite capacity management, integrated with Dynamics ERP. ### 3.3 Induscabos (Cables | ERP: TOTVS) Capacity and production planning system with raw material management and production mix optimization. Integrated with TOTVS ERP and Opcenter Scheduling to enhance operational efficiency. ### 3.4 Bartira (Wood/Furniture | ERP: Oracle) Solution for optimizing inventory policies and synchronized production planning to generate the master production plan. Integrated with Oracle ERP and Opcenter Scheduling. ### 3.5 Grendene (Textile | ERP: TOTVS) Production planning system with inventory optimization for capacity leveling and synchronized order management. Integrated with TOTVS ERP and Opcenter Scheduling. ### 3.6 Stellantis (Automotive | In-house ERP) Integrated planning and multi-plant capacity management solution ensuring efficient coordination across production sites. ### 3.7 Malwee (Textile | ERP: SAP) Integrated system for purchasing and production planning, both internal and outsourced, with inventory and finite capacity optimization. Integrated with SAP ERP and Opcenter Scheduling. ### 3.8 Sumitomo (Plastics & Rubber | In-house ERP) Integrated demand and supply planning solution connected to ERP and Opcenter Scheduling. ### 3.9 Fey (Metal-Mechanical | ERP: SAP) Production planning system with inventory optimization. Integrated with SAP ERP and Opcenter Scheduling. ### 3.10 Ciser (Metal-Mechanical | ERP: SAP) Integrated planning solution connected to SAP ERP, accelerating the planning cycle and optimizing inventory and service levels. ### 3.11 Polenghi (Food & Beverage | ERP: TOTVS) Capacity and production planning system with raw material management. Integrated with TOTVS ERP and Opcenter Scheduling. ### 3.12 Peccin (Food & Beverage | ERP: TOTVS) Material and production planning solution integrated with TOTVS ERP and Opcenter Scheduling, ensuring greater efficiency in supply chain synchronization. ### 3.13 Premier Pet (Food & Beverage | ERP: TOTVS) Integrated planning of demand, inventory, capacity, and transportation, including distribution to distribution centers. Integrated with TOTVS ERP and Opcenter Scheduling. ### 3.14 Dana (Automotive | ERP: Oracle) Demand, material, inventory, and production planning solution integrated with Oracle ERP and Opcenter Scheduling. ### 3.15 Unipac (Plastics & Rubber | ERP: SAP) Integrated S&OP planning system managing demand, inventory, capacity, and orders. Integrated with SAP ERP and Opcenter Scheduling. Over 350 scenarios simulated, 27% reduction in delays, 15% improvement in inventory health. ### 3.16 Mercur (Plastics & Rubber | ERP: TOTVS) Inventory, capacity, and production planning solution with raw material management. Integrated with TOTVS ERP and Opcenter Scheduling. **Summary**: 16 case studies across 8 industries, integrating with 5 different ERP systems (SAP, TOTVS, Oracle, Dynamics, in-house). Most implementations include Siemens Opcenter Scheduling integration for detailed production sequencing. --- # 4. CUSTOMER TESTIMONIALS ### Jades Romano — PCP Coordinator, Peccin (Food & Beverage) "Before NPLAN, our planning team spent days building spreadsheets just to plan one week of production. Today, in minutes, we generate complete scenarios showing the operational and financial impact of every decision — whether a line stop, product mix change, or cocoa price fluctuation. We tripled our volume and SKU mix with the same team, gaining speed, predictability, and data-driven intelligence. Integrated planning became a true competitive advantage." ### Antenor Neto — PPCP Manager, PremieRpet (Food & Beverage) "For years, spreadsheets were our allies in production planning. With NPLAN, we discovered a new and incredible world of possibilities. Generating dozens of scenarios with a single click and making immediate decisions is a major competitive advantage. The excellence and partnership of the consultants were essential for the outstanding results achieved. NPLAN is a milestone in the history of PremieRpet's PPCP." ### Marcelo Trindade — Supply Chain Manager, Unipac (Plastics & Rubber) "After searching and testing several established platforms in the market, we chose NPLAN because it best met our requirements for inventory management and factory complexity. Over 350 scenarios simulated in the last 6 months, 27% reduction in delays and shortages, 15% improvement in inventory health." **Key results reported by customers:** - Planning time reduced from days to minutes - 3x increase in volume and mix with the same team - 350+ scenarios simulated in 6 months - 27% reduction in delays and stockouts - 15% improvement in inventory health - Dozens of scenarios generated with a single click --- # 5. INDUSTRY SOLUTIONS ## 5.1 Pharma & Cosmetics Supply chain planning for pharmaceutical and cosmetics industries with traceability, shelf life and quality control. The pharmaceutical and cosmetics industry demands rigorous supply chain planning, where traceability, regulatory compliance, and shelf life control are fundamental requirements. NPLAN offers a complete platform to manage the complexity of these chains. **Key Capabilities:** - Demand Planning with Scenarios - Product Phase-In and Phase-Out - Inventory Policy by Warehouse - Stock Health Control and Simulation - Capacity Planning by Resource, Tool, and Labor - Supply with FUP and QA Approval - Shelf Life Planning - Sequencing and Setup Optimization - Data Traceability and Logging - Strategic/Long-Range Planning **Reference Clients:** Biolab, Amend, Mercur, Granado ## 5.2 Automotive Supply chain planning for the automotive industry with demand variation control, frozen periods and material pegging. The automotive industry operates with complex and highly synchronized supply chains, where demand variations, frozen periods, and material traceability are essential. **Key Capabilities:** - Demand Planning with Scenarios - Product Phase-In and Phase-Out - Demand Variation Control - Demand Anticipation - Frozen/Locked Period - Material Pegging - Capacity Planning by Resource and Labor - Supply with FUP and Alerts - Sequencing and Setup Optimization - Strategic/Long-Range Planning **Reference Clients:** Stellantis, Dana ## 5.3 Food & Beverage Supply chain planning for food and beverage industry with shelf life, traceability and quality control. The food and beverage industry faces unique challenges such as shelf life management, lot traceability, and rigorous quality control. **Key Capabilities:** - Demand Planning with Scenarios - Product Phase-In and Phase-Out - Inventory Policy by Warehouse - Stock Health Control and Simulation - Capacity Planning by Resource and Labor - Material Pegging - Supply with FUP and QA Approval - Shelf Life Planning - Sequencing and Setup Optimization - Data Traceability and Logging **Reference Clients:** Peccin, Polenghi, Premier Pet ## 5.4 Textile & Footwear Supply chain planning for the textile industry with multi-level synchronization, inventory segmentation and financial planning. The textile industry has supply chains with multiple transformation levels and a wide variety of SKUs. NPLAN enables synchronizing all chain levels, segmenting inventory policies, and integrating operational with financial planning. **Key Capabilities:** - Demand Planning with Scenarios - Product Phase-In and Phase-Out - Segmentation Inventory Policy - Stock Health Control and Simulation - Multi Level Synchronization - Capacity Planning - Material Pegging and Constraint - Supply with FUP and QA Approval - Sequencing and Setup Optimization - Financial Planning and Analysis **Reference Clients:** Elian, Grendene, Malwee ## 5.5 Agro Supply chain planning for agribusiness with raw material constraints, storage and demand-supply influence. Agribusiness operates with unique variables such as seasonality, raw material and storage constraints, and direct supply influence on demand. **Key Capabilities:** - Demand Planning with Scenarios - Inventory Policy by Warehouse - Stock Health Control and Simulation - Demand and Supply Influence - Raw Material Constraint - Supply with FUP and QA Approval - Shelf Life Planning - Storage Constraint - Capacity Planning by Resource - Material Pegging - Data Traceability and Logging **Reference Clients:** Biotrop ## 5.6 Metal Mechanical Supply chain planning for the metal mechanical industry with advanced MRP, production sequencing and capacity control. The metal mechanical industry deals with complex production processes, multiple manufacturing stages and high raw material dependency. **Key Capabilities:** - Demand Planning with Scenarios - Multi-Level MRP - Capacity Planning by Resource and Labor - Material Pegging and Traceability - Sequencing and Setup Optimization - Demand Variation Control - Frozen/Locked Period - Supply with FUP and Alerts - Inventory Policy by Warehouse - Strategic/Long-Range Planning **Reference Clients:** Fey, Ciser ## 5.7 Plastics & Rubber Supply chain planning for plastics and rubber industries with mold scheduling, batch optimization and material constraints. The plastics and rubber industry faces challenges such as mold scheduling, production cycle optimization, raw material constraints and a wide variety of SKUs. **Key Capabilities:** - Demand Planning with Scenarios - Mold Scheduling and Allocation - Capacity Planning by Resource - Production Batch Optimization - Sequencing and Setup Optimization - Material Pegging and Constraint - Stock Health Control and Simulation - Supply with FUP and Alerts - Product Phase-In and Phase-Out - Strategic/Long-Range Planning **Reference Clients:** Unipac, Mercur ## 5.8 Furniture & Coatings Supply chain planning for furniture and coatings industries with multi-level BOM, demand segmentation and capacity planning. The furniture and coatings industry combines manufacturing processes with high SKU variability, multi-level BOMs and seasonal demand. **Key Capabilities:** - Demand Planning with Scenarios - Product Phase-In and Phase-Out - Multi-Level MRP - Demand Segmentation by Channel - Capacity Planning by Resource and Labor - Sequencing and Setup Optimization - Inventory Policy by Warehouse - Stock Health Control and Simulation - Supply with FUP and Alerts - Strategic/Long-Range Planning **Reference Clients:** Bartira, Eliane --- # 6. ARTICLES & KNOWLEDGE BASE ## 6.1 Inventory Policy: How to Define Differentiated Inventory Policy with ABC-XYZ URL: /articles/inventory-policy A comprehensive guide to designing differentiated inventory policies by product segment using ABC-XYZ classification. **Core argument:** Defining an arbitrary, one-size-fits-all inventory policy and service level for every product (e.g., 30 days of stock or 95%/99% service level) is one of the most common and harmful practices in inventory management. Inventory policy must be differentiated, product by product or by segment. ### Six Service Level Drivers 1. Margin and Profitability — higher margin items justify higher service levels 2. Demand Predictability — stable items (X) need less safety stock than erratic (Z) 3. Carrying Cost — tied-up capital, warehousing, obsolescence 4. Stockout Cost — lost sales, customer dissatisfaction, contractual penalties 5. Strategic Importance — flagship products, contractual obligations 6. Supply Characteristics — lead time reliability, supplier risk ### ABC-XYZ Matrix (9 segments) - **ABC axis**: Segments products by financial value/impact (A = high value, B = medium, C = low) - **XYZ axis**: Segments products by demand predictability (X = stable, Y = variable, Z = erratic) - Combined matrix: AX, AY, AZ, BX, BY, BZ, CX, CY, CZ — each requiring different strategies ### Safety Stock Formulas (APICS) - **Fixed demand, variable lead time**: SS = Z × D̄ × σ(L) - **Variable demand, fixed lead time**: SS = Z × σ(D) × √L - **Both variable (dependent)**: SS = Z × √(L × σ(D)² + D̄² × σ(L)²) - **Both variable (independent)**: SS = Z × √(σ(D)² × L + D̄² × σ(L)²) Where Z = service level factor, D̄ = average demand, σ(D) = demand std dev, L = lead time, σ(L) = lead time std dev ### Common Mistakes 1. Classifying ABC by volume only (should use financial value) 2. Confusing variability with uncertainty (seasonal demand can be predictable) 3. Single service level target for all products (95% or 99% for everything is inefficient) 4. Underestimating C items (CZ is the biggest source of sleeping stock) ### 10 Steps to Optimize Inventory 1. Identify obsolete stock 2. Identify slow movers 3. Cancel open orders for excess items 4. Negotiate supplier returns 5. Targeted promotions for CY/CZ items 6. Reassess planned product launches 7. Donation or disposal as last resort 8. Review replenishment parameters 9. Align policy with commercial strategy 10. Continuous monitoring with coverage/turnover/aging KPIs **Important:** The inventory policy defined represents the desired objective. It is subsequently tested with the synchronized plan, which evaluates real constraints: raw material availability, production capacity, tools, labor, maximum inventory. This validation may adjust the policy based on what is operationally feasible. **Interactive tools on this page:** ABC-XYZ matrix with 5 visualization modes, strategy recommendation table, safety stock calculator with 4 APICS formulas, knowledge quiz. --- ## 6.2 MRO Planning: Best Practices for MRO Materials URL: /articles/mro-planning Structured approach to Maintenance, Repair and Operations materials planning. **Core argument:** In any industrial operation, MRO materials present a particular challenge. Unlike raw materials, these items have irregular demand, uncertain lead times, and a disproportionate impact on production continuity. A missing spare part can cause hours or days of downtime, with costs that exceed the item's value by orders of magnitude. ### Key Principles - **Criticality-based segmentation**: Items classified by consumption behavior and operational criticality (continuous/simple, continuous/critical, intermittent, critical) - **Differentiated policies**: Reorder point for regular items, min/max for intermittent, strategic buffers for critical items - **Automated replenishment**: Ensures execution discipline, eliminates manual decision dependency - **Risk-oriented planning**: Scenarios for supplier delays, equipment failure spikes, production volume changes ### How NPLAN Solves It - Clear visibility into items with excess stock and items at risk of stockout - Dedicated dashboards by criticality segment - Replenishment policies configured and executed automatically - Scenario simulation integrated into planning **Interactive tools:** MRO items table with criticality segmentation, inventory policy parameters by category. --- ## 6.3 Forecast Accuracy: Converting into Financial Results URL: /articles/forecast-accuracy How to translate forecast accuracy improvements into concrete financial impact. ### Market References - **IBF (Institute of Business Forecasting)**: ~0.2% increase in profitability per 1% improvement in forecast accuracy - **McKinsey & Company**: ~2% reduction in total inventory cost per 1% improvement ### Impact of Over-Forecasting - Excess finished goods inventory - Expired products and obsolete raw materials - Additional warehousing costs - Tied-up working capital ### Impact of Under-Forecasting - Stockouts and delayed orders - Order cancellations - Urgent production, overtime, and out-of-sequence setups - Express freight costs **Interactive tools:** ROI/Savings calculator on the website that simulates financial gains by company size. --- ## 6.4 Scenario Simulation: End-to-End Supply Chain Scenario Planning URL: /articles/scenario-simulation Why isolated scenario simulation fails and how end-to-end simulation enables faster, more consistent decisions. **Core argument:** In most companies, each planning step operates in a different tool. The result is a process that takes days, generates constant rework, and when it finally delivers a plan, the scenario has already changed. The problem isn't a lack of information — it's fragmentation. ### Key Concepts - Isolated tools simulate individual variables but miss cross-functional impacts - End-to-end simulation propagates changes across demand, inventory, capacity, supply, and distribution simultaneously - A change in demand should impact the entire chain instantly and traceably - Without automatic propagation, it's not simulation — it's reaction ### Scenario Comparison Metrics - Service Level - Projected Inventory - Resource Utilization - Backlog / Delay ### The S&OP-Execution Gap - S&OP works with aggregated data (product family, month) - Execution works with individual SKUs, production orders, specific dates - Without integration, decisions viable at aggregate level may not work in detail ### Operational Triggers for Scenarios Forecast accuracy, lumpy demand, production capacity, labor shortages, material availability, variable lead times, plant utilization, supplier performance, quality issues, schedule adherence. **Interactive tools:** End-to-end flow diagram, process comparison (fragmented vs integrated), scenario branching table. --- ## 6.5 AI Foundations: Why AI Agents Need a Supply Chain Engine URL: /articles/ai-foundations Understanding why AI alone cannot solve supply chain planning without a proper optimization engine. **Core argument:** Language models (LLMs) like GPT, Gemini, and Claude excel at text generation and natural language but cannot directly solve combinatorial supply chain problems involving finite capacity, interdependent lead times, and financial trade-offs. A 3-layer architecture is needed. ### The 3-Layer Architecture 1. **AI Agents Layer**: Customizable agents with datasets, tools, skills, and governance — the user interface 2. **Supply Chain Engine**: The mathematical brain with optimization, heuristics, statistics, and ML — instant simulation 3. **Data Layer**: Input data that needs to be processed, treated, and audited ### The Supply Chain Engine (4 pillars) - Mathematical optimization (linear programming, mixed-integer) - Heuristics (fast near-optimal solutions) - Statistical models (forecasting, seasonality) - Machine learning (pattern recognition, anomaly detection) ### NPLAN's Approach - GenAI is not treated as a decision engine but as a reasoning and intelligent interface layer - It operates on top of the mathematical engine's results - Makes planning more accessible, iterative, and connected - Corporate-grade security: data doesn't leave origin country, configurable privacy rules **Interactive tools:** AI techniques matrix by planning domain, 3-layer architecture diagram, naive vs recommended approach comparison. --- ## 6.6 AI Use Cases in Supply Chain Planning URL: /articles/ai-use-cases 16 practical use cases of AI applied to supply chain planning, organized by maturity and impact. ### Use Case Categories - Demand forecasting with ML (time series, external variables) - Anomaly detection in demand/supply patterns - Automatic parameter tuning (safety stock, reorder points) - Intelligent alerts and recommendations - Natural language queries on planning data - Scenario generation and evaluation - Copilot for planners - Automated report generation --- ## 6.7 nPlan + SAP Integration URL: /articles/nplan-sap Bidirectional integration between nPlan and SAP ERP for enhanced supply chain planning. ### Data Exchange - Master data, BOM, routing, demand, inventory positions - Production and purchase orders written back to SAP - Supports SAP ECC and S/4HANA - Data can be exchanged via API or file-based (TXT/CSV) for quick validation ### Why Companies Choose NPLAN over SAP IBP - Faster implementation - More flexible scenario simulation - Better suited for complex, multi-constraint environments - Maintains SAP as system of record while adding advanced planning capabilities --- ## 6.8 nPlan + Siemens Xcelerator Partnership URL: /articles/nplan-siemens Strategic partnership combining nPlan tactical/strategic planning with Siemens Opcenter APS detailed scheduling. ### Integration Value - Opcenter Scheduling: precision for shop floor operations (order sequencing, setup minimization, real-time rescheduling) - NPLAN: extends the planning horizon with S&OP, MPS, MRP, and scenario intelligence - Together: complete coverage from strategic planning to detailed scheduling ### NPLAN vs Opcenter Planning - Opcenter Planning corresponds to SUPPLY and CAPACITY modules of NPLAN - NPLAN goes further with DEMAND, INVENTORY, ORDERS, and DISTRIBUTION modules - NPLAN includes AI-based demand forecasting, inventory policies, and integrated planning --- ## 6.9 nPlan + Opcenter APS Integration URL: /articles/nplan-opcenter Deep technical integration between nPlan planning layer and Opcenter APS scheduling. Covers collaboration workflows, AI capabilities, visualization, and publication processes. --- ## 6.10 Planning vs Scheduling: Where to Start? URL: /articles/planning-vs-scheduling Decision framework to determine whether a company should start with planning or scheduling when digitalizing supply chain operations. **Interactive tool:** 7-dimension diagnostic quiz covering Demand, Capacity, Inventory, Raw Materials, Decision-Making, Communication, and KPIs. Each dimension scored to recommend starting point. --- ## 6.11 Supply Chain Planning Canvas URL: /articles/planning-canvas Visual diagnostic framework for mapping and diagnosing supply chain planning maturity. ### Structure - **Business Rules area**: Processes, Data, Systems, Indicators, Demand, Inventory, Planning, Capacity - **Information Technology area**: Volumetrics, Security, Architecture, Operations, Interfaces, API Integration The canvas is used during the assessment phase before any implementation project. It ensures all critical dimensions are covered. **Interactive tools:** 12 assessment dimension cards, downloadable PDF canvas. --- ## 6.12 Demand Consolidation Strategy URL: /articles/demand-consolidation Guide to consolidating demand from orders and forecasts in Supply Chain Planning. ### Key Topics - Basic consolidation rules (orders vs forecast) - Combination strategies (max, sum, replace) - Billing-based adjustments - Demand phasing across time buckets - M0 (current month) handling --- ## 6.13 From Excel to Supply Chain Planning in 12 Weeks URL: /articles/excel-to-scp Week-by-week implementation methodology for migrating from spreadsheet-based planning to a dedicated SCP platform. ### Implementation Phases - Weeks 1-3: Data preparation and ERP integration - Weeks 4-6: Configuration and model setup - Weeks 7-9: Testing and validation - Weeks 10-12: Go-live and stabilization --- # 7. PARTNERSHIPS ## Siemens Partnership - Official Siemens Solution Partner for supply chain planning - Available on the Siemens Xcelerator Marketplace - Integration with Opcenter APS for detailed scheduling ## Partner Program nPlan Partner Program for consultants, system integrators, and technology partners. Join the ecosystem to deliver supply chain planning solutions. --- # 8. FREQUENTLY ASKED QUESTIONS (FAQ) ### How does the platform integrate with my current systems? NPLAN offers native integration with major market ERPs such as SAP, Oracle, and TOTVS through robust APIs and standardized connectors. Our platform integrates essential planning data including sales orders, forecasts, item master, bills of material, routings, resources, production orders, and purchase orders. We also support complementary information such as calendars, maintenance scheduling, and storage capacity. Our cloud solution seamlessly integrates data, processes, and teams in a single collaborative environment. ### What security measures does the platform have? Security is our top priority. NPLAN is hosted on Microsoft Azure with high availability architecture, ensuring 99.9% uptime. We implement authentication via Active Directory and SSO with Google and Microsoft integration. Our platform undergoes regular security audits and penetration testing (Pentest) conducted by internationally certified specialized companies. We are 100% compliant with LGPD, GDPR, and PDPA, ensuring complete protection of your data. All data is encrypted both in transit and at rest, with strict access controls and continuous monitoring. ### How does the POC and Trial process work? The process starts with a POC (Proof of Concept), where our team works alongside yours using your real data to demonstrate concrete results and validate the platform's fit for your scenario. After validation, we offer the Trial — a temporary license focused on one module (Demand or Supply Planning), with limited data volume and integration via Excel spreadsheet upload. This way, you can experience NPLAN in your daily operations before making a purchasing decision. ### What are the upcoming platform developments? Our roadmap is continuously updated based on customer feedback and market trends. Planned, in-progress, and delivered features are publicly visible on the roadmap page. --- # 9. ERP INTEGRATIONS nPlan integrates bidirectionally with major ERP systems: - **SAP** (ECC, S/4HANA) — master data, BOM, routing, orders - **TOTVS** (Protheus, Datasul) — full integration - **Oracle** (JDE, Cloud) — master data and transactional - **Microsoft Dynamics** — inventory and demand - **Custom/In-house ERPs** — via API or file exchange --- # 9. KEY DIFFERENTIATORS - **End-to-end platform**: Single platform covering S&OP through S&OE - **Scenario simulation**: Generate and compare dozens of scenarios in minutes, not days - **AI-powered**: Machine learning for forecasting, GenAI as intelligent copilot - **ERP agnostic**: Works with SAP, TOTVS, Oracle, Dynamics, or custom ERPs - **Siemens integration**: Seamless connection with Opcenter APS for scheduling - **Modular**: Start with one module, expand as needed - **Cloud-native**: SaaS platform, no infrastructure management - **Fast implementation**: From Excel to SCP in 12 weeks - **Enterprise security**: Data sovereignty, configurable AI privacy rules