NTP Product Lineup

We will introduce the process of overwhelming value creation brought by FDE through specific success stories from the manufacturing site. At a mobility vehicle manufacturing site, FDE was stationed on-site to integrate and analyze quality data. As a result, a visible achievement of a 15% reduction in defect rates was accomplished. By directly listening to the voices from the field and immediately reflecting the issues into the model, an on-site implementation approach enabled value creation in a short period. We will provide a detailed report that includes the success stories of a mobility company.

• Other information systems

This is an example of a refresh of IT infrastructure that significantly reduced the burden of "data preparation," a major factor hindering the utilization of data. By implementing Databricks, we eliminated data silos that were scattered across various departments and established an integrated data platform. As a result, data scientists and analysts can now utilize data through self-service, successfully reducing preparation time by 80%. Currently, a culture where over 300 employees regularly use data has been established. We have published a roadmap for building an efficient data infrastructure in our materials.

• Other information systems

We will introduce a practical case of FDE that ensures rapid product development and competitive advantage in overseas expansion. In our global new business, we established a system to dispatch FDE to the local area to engage in direct dialogue with customers. We developed an MVP (Minimum Viable Product) in just a few weeks, reducing the time to market by 20% compared to conventional methods. The ability to launch quickly is a strength of the FDE model, which allows for immediate reflection of on-site feedback. Please check the materials for the secrets of speedy new business development.

• Other information systems

We will detail the three-tiered support solutions provided by NTP, tailored to the phase of AI utilization in companies. We offer a roadmap that includes "1.0" for foundational development, "2.0" for rapid implementation through FDE, and "3.0" for self-sustainability through the establishment of an AI Center of Excellence. By consistently supporting the transformation of business, data, and organization at each phase, we help companies move beyond just proof of concept. In an era where AI technology is becoming commoditized, the true differentiators are "implementation capability" and "reduction of time-to-value." We are also offering guidance on the "AI-Ready Assessment" to help companies understand their current position.

• Other information systems

We will explain the strategic shift needed to break through the "barrier to AI utilization" that many Japanese companies are facing. Currently, the AI utilization efforts of many manufacturing companies are limited to the automation of routine tasks (Level 1.0). However, to build true competitive advantage, it is essential to transition to "Level 2.0" and beyond, where AI is integrated into core business activities such as decision-making and strategic planning. By steering towards proactive AI utilization, we will present specific steps to achieve sustainable business growth and revenue expansion. For more details on the maturity model of AI utilization that expands revenue, please download the materials and check them.

• Other information systems

Even if expensive SFA and CRM systems are implemented, we will unravel the fundamental reasons why they do not take root in the field and fail to deliver the expected results. The main factors behind the failure of traditional sales DX lie in three significant barriers: "input burden," "individualization," and "system fragmentation." The input tasks in the field become a burden, and the lack of data accumulation ultimately leads to a vicious cycle of relying on individual memory and spreadsheets. To achieve essential DX, it is necessary to redesign operations and systems in a way that does not create resistance in the field, even before selecting tools. Details on the "DX traps" that sales organizations are prone to and strategies to avoid them can be found in the downloadable materials.

• Other information systems

This introduction discusses the role of a "GTM Engineer," who integrates sales, marketing, and customer success through technology to design revenue systems. A GTM Engineer is not just a tool manager; they are a "revenue architect" who builds autonomous workflows using APIs and LLMs (large language models). The goal is to transform traditional labor-intensive sales styles into technology-driven approaches, achieving productivity equivalent to that of 100 people with just one individual. Elevating personalized sales processes into highly reproducible systems is key to accelerating growth in the manufacturing industry. The definition and role of GTM engineering aimed at maximizing revenue are explained in detail in the materials provided.

• Other information systems

We will explain an advanced design philosophy that derives optimal solutions by combining the best tools from each area without relying on a massive single system. In modern GTM engineering, CRM systems like Salesforce and HubSpot serve as data hubs, while the iPaaS "n8n" acts as the glue to connect various systems. For example, it is possible to implement autonomous workflows that automatically collect customer signals from external sources and generate personalized proposal emails using LLM. This composable design enables flexible scalability and rapid on-site support that adapts to changes in the business. Examples of automated workflows using advanced AI and API integrations can be found in the materials.

• Other information systems

In a specialized trading company in the chemical industry, we will detail a successful case of how AI was utilized to reduce the workload on-site and enhance sales efficiency. In this project, we first conducted a business assessment of all employees and quantified the reality that "non-core tasks," such as creating estimates and processing orders, accounted for approximately 80% of total work hours. By replacing these bottleneck administrative tasks with an AI agent, we created an environment where sales representatives could focus on deepening customer relationships and generating business opportunities. The key to success is to prioritize digital transformation (DX) in areas with high return on investment (ROI) based on numerical evidence rather than intuition. For detailed examples of specific AI applications that significantly reduced administrative burdens, please download the materials and take a look.

• Other information systems

Instead of waiting for long-term, large-scale system development, we will explain a strategy that starts from areas where the field can immediately experience benefits. To accelerate DX with the cooperation of the field, it is important to accumulate immediate "Quick Wins," such as automating CRM input with voice AI. For example, a system where AI automatically summarizes meeting recordings into minutes and stores them in CRM dramatically reduces the burden on the field and promotes positive changes towards DX. Additionally, by building a knowledge base that allows AI to learn from past insights, even young employees can make strategic proposals like veterans, making it a shortcut for embedding AI as a "capability enhancement tool" in organizational transformation. Check the points for initiating DX that will please the field and specific strategies for Quick Wins in the downloadable materials.

• Other information systems

The true value of AI implementation goes beyond mere labor cost reduction. We will explain the impact it has on both revenue growth (top line) and cost reduction (bottom line). In case studies within the manufacturing industry, we have achieved annual revenue increases of 1-3% through the reactivation of dormant customers and improved order accuracy. At the same time, we have reduced administrative labor by 30-50% through automation of CRM input, significantly improving overall organizational productivity. By preventing cases from being neglected through AI alerts and utilizing customer signals at the right timing, we build a "proactive" foundation that minimizes opportunity loss and maximizes order probability. For detailed KPI metrics that achieve both revenue improvement and labor cost reduction simultaneously, please download the materials for more information.

• Other information systems

We will introduce NTP's support style, which is not just about drawing strategies or simply implementing tools, but designing the future from the "Physical" of the field. NTP's strength lies in its ability to thoroughly enhance the resolution of the field, select appropriate technologies, and implement them with a sense of speed and partnership. In the complex domain of manufacturing, we identify the true bottlenecks hidden in the field and provide comprehensive support from the design of AI agents to the automation of organizations. We start with an "AI-Ready Assessment" to diagnose the current situation and present a roadmap to ensure a solid ROI. For details on our DX support services that quickly connect strategy to implementation, please check the document download.

• Other information systems

Conventional AI has primarily focused on data analysis and decision-making support, but we have now entered an era where AI directly interacts with the physical space. Physical AI (Acting AI) is a set of technologies that enables AI to understand physical environments and autonomously control and optimize equipment and robots. Unlike traditional AI that only produces digital outputs, by combining LLM, physical simulations, and robotics, it achieves flexible actions without programming and the ability to adapt to unknown environments. Please check this document to see the full picture of this "acting AI," which will shape the future of manufacturing. Download the white paper that condenses the fundamental knowledge of AI and make use of it right away.

• Other information systems

We will explain the three core elements of how physical AI interacts with the real world and advances learning and optimization. The heart of the system lies in the cycle of "Sensing," which accurately reads dynamic environments using sensors and cameras; "Thinking," which predicts and determines the optimal next move on a digital twin; and "Acting," which directly controls robots and equipment. This loop operates in real-time, enabling direct intervention in the physical layer. By understanding advanced architecture, let's elevate your automation to the next level. Detailed materials explaining the components and implementation mechanisms of physical AI can be obtained here.

• Other information systems

The structural challenges faced by the manufacturing industry, such as labor shortages and the disruption of skill transfer, are difficult to resolve with traditional rule-based automation alone. In today's manufacturing environments, the loss of tacit knowledge due to the retirement of skilled workers and the urgent need to adapt to frequent changeovers associated with small-lot production are pressing issues. Physical AI provides flexible judgment and control in response to the increasingly complex behaviors of these environments, dramatically promoting labor reduction. Against the backdrop of a societal labor shortage, we will clarify in detail why this technology is gaining attention now, along with its background and necessity. Please view our report summarizing the industry's challenges and the need for AI utilization, available for free right now.

• Other information systems

One of the global trends in physical AI is the incredible speed of hardware mass production in China and the introduction of implementation examples. In China, the commercialization of humanoid robots is accelerating, with production numbers increasing exponentially from 1,000 units to 10,000 units in just a few months. The phase of skill verification has now ended, and we have moved to a stage of scalable value provision. With low-cost and mass production as their weapons, there are many lessons that Japanese manufacturing can learn from the strategies of Chinese companies that are rapidly advancing social implementation. Details of China's leading robot implementation trends are available in the downloadable materials.

• Other information systems

We will explain the specific shipping performance and market expansion of major Chinese robotics companies that are experiencing rapid growth toward 2025. Companies like AGIBOT, which boasts a shipping share of approximately 39%, and Unitree Robotics, which has entered the market with a shocking low price of around $6,000, are making remarkable strides. Additionally, UBTech Robotics is deploying the industry-specific humanoid "Walker S2" for automotive factories and has secured large orders. Through these specific examples, you can grasp the actual business scale at which physical AI is operating. Please download the case study materials that cover specific figures such as shipping numbers and order amounts for each company.

• Other information systems

The U.S. physical AI strategy is not just about standalone hardware, but rather focuses on building systems that combine AI platforms and digital twins. At Amazon's logistics centers, the humanoid robot "Digit" has achieved commercial viability. Not only is the introduction of standalone robots involved, but integrated and optimal control has been realized by linking with higher-level systems such as warehouse management systems (WES) to simulate the entire site in a virtual space. We will provide a detailed explanation of the essence of the U.S. platform strategy that seamlessly connects physical and virtual spaces. Let's check out examples of building an AI ecosystem that supports massive logistics in detail through free materials.

• Other information systems

We introduce the next generation of manufacturing sites, where Japan's leading robot manufacturer FANUC and AI computing powerhouse NVIDIA are taking on new challenges. Efforts are underway to build a photorealistic virtual factory using NVIDIA Isaac Sim, efficiently generating AI training data through tens of thousands of simulations. By accurately reproducing the learning outcomes in virtual space as real robot trajectories, highly flexible and precise tasks that were previously difficult have become possible. This is an advanced use case that leads human-robot collaboration to the next stage, including operations through natural language. Details of AI utilization cases through the highest level of technical collaboration in the country can be found in this document.

• Other industrial robots

We will explain our (NTP) achievements in building an advanced failure prediction model that combines equipment data with spatial data. In addition to IoT sensor data such as equipment vibration and pressure, we integrated surrounding environmental data, such as pedestrian flow and material placement obtained from LiDAR and cameras, along a time axis. As a result, we successfully visualized the "impact of environmental changes on equipment," which had previously been difficult to capture, significantly improving the accuracy of abnormal signal detection. The case of digital twin implementation through a near-real-time dashboard directly contributes to stable operations on-site. Please download our support achievement document summarizing the actual implementation scheme and results for free right now.

• Sensors
• Other safety equipment

We will clarify the true nature of the so-called "barrier to AI implementation," which many Japanese companies are facing, where they cannot progress beyond the PoC (proof of concept) stage. Although data is being accumulated through IoT, there are many cases where decisions vary by site, and the data is not in a format that can be handed over to AI. Additionally, the "limitations of retrofitting" where existing equipment and rules do not assume collaboration with AI is also a significant challenge. We will discuss the importance of developing a data integration platform necessary to break through these barriers and achieve "autonomous control (physical AI)" that goes beyond mere visualization. Let's obtain a free resource that provides solutions to eliminate the bottlenecks in successfully implementing AI in your company.

• Other core systems

We would like to introduce NTP's unique support system that sublimates complex manufacturing processes into a "Sensing→Thinking→Acting" loop. The effectiveness of physical AI is ensured by "on-site completion" support from FDE (Field Deployment Engineers) who are well-versed in actual business operations. With a sense of speed that eliminates "translation loss" between strategy and implementation, we provide comprehensive support from understanding the current situation to KPI design, and the construction of a modern data infrastructure utilizing Databricks and Fivetran. We propose the value of our co-piloting consulting aimed at making the field AI-Ready. We are currently offering a free document summarizing the details of our co-piloting support services and the steps to achieve AI-Readiness.

• Other core systems

As the first step towards AI implementation, we are pleased to offer a free program to diagnose your company's "data structure," "business flow," and "organizational structure." We will evaluate the current state of IoT implementation, identifying gaps in data and infrastructure within the physical AI loop across three axes. Through the assessment, we will define how physical actions directly contribute to ROI and productivity improvements on-site, and we will formulate specific steps towards scalable implementation. Please utilize this as the "first step" to maximize your existing assets and achieve results in the shortest distance possible. The assessment guide, which explains the process from current diagnosis to improvement, is available for download here.

• Other core systems

This document explains the DX strategy for transforming on-site data into profits and increasing sales. It includes the three levels of proficiency in AI-Ready, the reasons why traditional SFA/CRM implementations fail, a new approach called "GTM Engineering," and case studies of AI-Readiness in chemical trading companies. It also contains information about our free AI-Ready assessment (current status diagnosis). Please make use of it. 【Contents】 ■ Current state of AI utilization: Explanation of the strategic shift from defense to offense ■ Limitations of traditional sales DX: Three barriers that lead to failure with just tool implementation ■ GTM Engineering: Definition and role of a new approach to designing revenue ■ Case studies and successful models: AI-Readiness and Quick Wins in chemical trading companies ■ Expected return on investment: Impact on top line and bottom line ■ NTP's solution: Comprehensive implementation support services closely tied to the field *For more details, please download the PDF or feel free to contact us.

• Other core systems

This document explains the utilization of Physical AI in manufacturing sites. It includes the core architecture of Physical AI, reasons why Physical AI is needed in the field today, global trends in Physical AI, case studies from Chinese and American companies, as well as domestic use cases. Additionally, we introduce our support achievements, such as advanced failure prediction through the integration of equipment data and spatial data. We encourage you to read it. 【Contents】 ■ What is Physical AI: An overview of AI that drives manufacturing sites ■ Global Trend: Implementation of hardware in China ■ Global Megatrend: System orchestration in the United States ■ Advanced domestic use cases: Integration of precision work and virtual environments ■ NTP's solution: Making sites "AI-Ready" starting from the field *For more details, please download the PDF or feel free to contact us.

• Other core systems

This document is a guide for transforming organizations and foundations to be AI-Ready. It includes the design of the shortest path to a "state where AI functions," practical AI development integrated into on-site operations, the construction of a modern data stack, and support achievements for industry-specific challenges. Our specialized consultants will work closely with your front line to unravel your challenges. Let's start together by organizing your information structure. Please feel free to contact us for inquiries or consultations. 【Contents】 ■ Consulting | AI-Ready Assessment and Organizational Design ■ Engineering | AI Development that Creates Business Value ■ Engineering | Building a Modern Data Infrastructure that Supports AI ■ Case Studies | Support Achievements from Strategic Planning to Implementation ■ Next Step | Taking the First Step Towards Your "AI-Ready" Together *For more details, please download the PDF or feel free to contact us.

• Other core systems

This document is an explanatory material about designing GTM strategies that walk together on the "shortest path" to monetization and engineering that enhances the "order rate" at the forefront with technical expertise. It introduces monetization through target identification, messaging, and on-site execution, as well as "RevOps," which centrally manages sales data from all customer touchpoints, and showcases achievements from market development to overwhelming sales growth. Our specialized consultants will work closely with your front line to unravel challenges. Let's start together by organizing your information structure. Please feel free to contact us for inquiries or consultations. 【Contents】 ■ Consulting | GTM Strategy Design: Walking together on the "shortest path" to monetization ■ Engineering | GTM Stack Construction & RevOps: A seamless data infrastructure ■ Engineering | Sales Engineering: Enhancing the "order rate" at the forefront with technical expertise ■ Case Studies | Achievements: From market development to overwhelming sales growth ■ Next Step | Taking the first step towards your "AI-Ready" together *For more details, please download the PDF or feel free to contact us.

• Other core systems

This document is an explanation of our DX support services that unravel the "messy challenges" of the manufacturing site and build the foundation for digital transformation (DX). It explains approaches to business process reform (BPR), the construction and renewal of systems that optimize the entire value chain from scratch, and the implementation of modern platforms that enhance decision-making on the ground. Our specialized consultants will work closely with your frontline to unravel challenges. Let's start together by organizing your information structure. Please feel free to contact us for inquiries or consultations. 【Contents】 ■ Consulting | Unraveling the "messy challenges" of the manufacturing site and building the foundation for DX ■ Core Engineering | Robust system development that supports the site in a seamless manner ■ Data & AI Infrastructure | Data-driven infrastructure through data lakehouses ■ Proven Track Record | Implementation and transformation track record in the manufacturing industry ■ Next Step | Taking the first step towards making your company "AI-Ready" together *For more details, please download the PDF or feel free to contact us.

• Other core systems

"Although we have sensor data, it cannot be used on-site," and "We tried a PoC but couldn't achieve accuracy, and management approval has not been granted" — equipment maintenance often comes to a standstill at this "one step away." This case study reveals the steps taken to overcome three challenges hindering equipment maintenance in aging plants: 1. The risk of unexpected shutdowns due to aging, 2. The retirement of skilled maintenance personnel and the loss of tacit knowledge, and 3. The barrier of lacking a data infrastructure that halts PoC efforts. We will outline a four-step process centered around the Databricks Data Lakehouse (digitizing records → data integration → assetizing "intuition" → automating maintenance planning). [Recommended for those who:] - Want to implement equipment maintenance but are struggling with data infrastructure development - Have not achieved accuracy in their PoC and have not received management approval - Face challenges in inheriting tacit knowledge due to the retirement of skilled maintenance personnel - Have sensor data but are not fully utilizing it.

• Business Intelligence and Data Analysis
• EAI/ETL/WEB application server
• Other information systems

Preventing quality irregularities and enhancing traceability are the most critical challenges in modern manufacturing. NTP's manufacturing DX support services strengthen quality management. To ensure robust product quality assurance, the digitization of inspection data and the establishment of tamper-proof traceability are essential. Our quality management system builds a framework that automatically records and manages various inspection results throughout the manufacturing process. In the event that a defect occurs, we can quickly trace back to the cause, minimizing the expansion of damage. By accumulating reliable quality evidence, we dramatically enhance customer trust. You can download the introduction materials for our manufacturing DX support services that implement reliable traceability here.

• Other production management systems