试点项目交付周期Pilot delivery cycle
AI4Materials
Magnetic Materials
Cross-scale Platform
把磁性材料研发，从高成本试错，升级为 AI 驱动的跨尺度协同系统 Upgrade magnetic-materials R&D from high-cost trial-and-error to an AI-driven, cross-scale operating system
木乔智科围绕磁性及磁相关材料，构建集基础模型、物理模拟、机器学习势能、高性能计算、自动化工作流与工程交付于一体的平台，服务高校课题组、科研机构、产业客户与战略合作伙伴。 WoodBridge Intelligence builds an integrated platform for foundation models, physics simulation, ML interatomic potentials, HPC, workflow automation, and delivery for universities, research institutes, industrial teams, and strategic partners.
适用于投资人展示、校企合作沟通、产业客户拜访与科研联合项目洽谈。 Designed for investor conversations, academic partnerships, industrial outreach, and joint R&D discussions.
平台能力总览
Platform Overview
从原子级建模到研发决策输出 From atomistic modeling to R&D decision output
01
材料数据与知识引擎
Data & knowledge engine
02
物理驱动 + 数据驱动模型
Physics + data-driven models
03
多尺度仿真与主动学习闭环
Multi-scale simulation loop
04
产业级交付与部署
Production-grade delivery
典型价值方向 Typical value themes
- 缩短候选筛选和验证周期Shorter screening and validation cycles
- 降低实验与计算试错成本Lower experimental and computational waste
- 提升模型可解释性与决策置信度Better explainability and decision confidence
特定任务建模效率提升空间Potential efficiency gain in selected tasks
分层合作与业务转化路径Layered engagement model
软硬件协同的一体化交付Integrated software + compute delivery
* 指标用于展示典型项目目标或内部测试口径，实际结果取决于材料体系、数据质量与项目范围。
* Metrics illustrate typical project targets or internal benchmarks. Actual outcomes depend on material systems, data quality, and project scope.
公司定位Positioning
不只是仿真服务商，而是面向磁性材料研发的 AI 基础设施构建者More than a simulation vendor — an AI infrastructure builder for magnetic-materials R&D
木乔智科的核心目标，是把材料研发中分散的数据、模型、算力、工作流和专家经验组织成一个可复用、可迭代、可部署的系统。我们关注的不只是“算得出来”，而是“能否真正帮助合作方更快做决策、更稳做验证、更低成本走向产品化”。 Our goal is to organize the fragmented pieces of materials R&D — data, models, compute, workflows, and domain expertise — into a reusable, iterative, deployable system. We focus not only on computing results, but on helping partners make better decisions faster and more reliably.
面向外部沟通，木乔智科的价值表达可以归纳为三层：第一层是技术突破，第二层是研发提效，第三层是业务与成果转化能力。官网因此需要同时承接科研可信度、产业理解和品牌专业度。 Externally, WoodBridge’s value proposition can be expressed in three layers: technical breakthrough, R&D acceleration, and commercialization capability. The website therefore needs to support scientific credibility, industrial relevance, and professional brand presentation at the same time.
A
科研可信度Scientific credibility
磁性材料、复杂体系建模、跨尺度计算与 AI 方法的交叉积累Experience at the intersection of magnetics, complex systems, cross-scale simulation, and AI
B
产业可落地性Industrial relevance
从问题定义、试点验证到平台交付与私有化部署的完整路径A full path from problem framing and pilots to platform delivery and private deployment
C
品牌与沟通能力Brand & communication
可同时服务投资人、学校、研究机构、企业和生态伙伴Able to speak to investors, universities, institutes, industrial teams, and ecosystem partners
技术能力Technology
技术表达要从“会做什么”，升级为“系统如何构成竞争壁垒”The story should move from “what we do” to “how the system creates defensible advantage”
01
面向磁性材料的基础模型能力Foundation-model capability for magnetic materials
围绕磁性及磁相关材料建立专用知识表示、候选生成与参数预测能力，为复杂研发任务提供上层智能引擎。Build specialized knowledge representation, candidate generation, and parameter prediction for magnetics-oriented material systems.
02
物理驱动 + 数据驱动联合建模Physics-informed + data-driven modeling
把第一性原理、分子动力学、自旋相关模拟与机器学习方法串联，兼顾物理一致性、计算效率和工程可用性。Combine first-principles methods, molecular dynamics, spin-related simulations, and ML into one coherent stack.
03
机器学习势能与主动学习闭环ML potentials with active-learning loops
针对复杂多元体系构建高精度、可扩展的 ML 势能训练流程，支撑更大尺度、更长时间尺度的模拟任务。Train scalable ML interatomic potentials for complex systems and unlock larger-scale, longer-horizon simulations.
04
跨尺度仿真与高通量筛选Cross-scale simulation & high-throughput screening
覆盖从电子结构、原子相互作用、自旋动力学到参数扫描、候选排序与设计建议输出的完整链条。Span electronic structure, atomistic interaction, spin dynamics, parameter sweeps, candidate ranking, and design recommendations.
05
自动化工作流与平台工程化Workflow automation & platform engineering
支持任务编排、数据沉淀、结果回流、可视化输出和持续迭代，让一次项目合作可以沉淀为长期能力。Turn one-off projects into reusable capability through orchestration, data loops, visualization, and continuous iteration.
06
从科研到部署的双场景适配Built for both research and deployment
既能服务探索性研究，也能支持企业内部部署、私有化交付、算力生态适配和长期维护。Serve both exploratory research and enterprise deployment, including private delivery, compute adaptation, and maintenance.
软硬件能力Software & Hardware
把“技术能力”讲完整：不仅有模型，也有算力、工具链和交付能力A complete story includes not just models, but also compute, tooling, and delivery
软件与模型能力Software & model capabilities
- 材料数据治理、结构化知识库与实验/计算数据沉淀Materials data governance, structured knowledge bases, and data accumulation
- 基础模型、参数预测、候选筛选与可解释分析Foundation models, parameter prediction, candidate ranking, and explainability
- DFT / MD / Spin-Lattice Dynamics / MLIP 一体化流程Integrated DFT / MD / spin-lattice dynamics / MLIP workflows
- 自动标注、主动学习、训练监控与结果追踪Automated labeling, active learning, training monitoring, and traceability
- 中英文双语报告、可视化展示与对外资料输出Bilingual reporting, visualization, and external presentation materials
算力与部署能力Compute & deployment capabilities
- 支持多集群、多任务、批量并发与大规模训练/推理Multi-cluster, multi-job, and large-scale training/inference support
- 可适配 GPU 训练环境与不同算力生态Adaptable to GPU training environments and diverse compute ecosystems
- 支持平台订阅、私有化部署与联合开发模式Support for SaaS-style access, private deployment, and co-development
- 可围绕客户数据安全、权限隔离与内部流程做定制Customizable around data security, permissions, and internal enterprise workflows
- 可衔接企业研发体系、科研平台和外部合作网络Connectable to enterprise R&D systems, academic infrastructure, and partner ecosystems
业务模型Business Model
官网需要把“怎么合作、怎么付费、怎么扩展”说清楚The site should clearly explain how clients engage, pay, and expand with you
P0
评估与路线设计Assessment & roadmap
快速理解材料体系、业务目标和数据基础，输出可行性判断、技术路线与试点建议。Rapid assessment of system, business goals, and data readiness with a clear feasibility plan.
P1
工艺优化与试点验证Optimization & pilot validation
围绕已有体系做模型验证、参数优化、流程搭建与小规模试点，形成可复用方法。Validate models, optimize parameters, and build a reusable workflow in a pilot setting.
P2
联合研发与平台交付Joint R&D & platform delivery
进入中长期合作，包括联合研发、平台模块交付、私有化部署与成果转化设计。Move into long-term engagement through joint R&D, modular delivery, deployment, and commercialization.
适合高校 / 研究机构For universities / institutes
联合课题、方法开发、论文与项目申报支撑、科研平台共建Joint research, method development, publications, grant support, and platform co-building
适合产业客户For industrial teams
目标材料筛选、配方优化、流程提效、部署与长期服务Target screening, formulation optimization, process efficiency, deployment, and long-term support
适合投资与战略伙伴For investors / strategic partners
看清技术壁垒、商业闭环、行业切入口与平台化增长路径Understand technical defensibility, business loops, market entry points, and platform scale-up paths
应用场景Applications
把场景说具体，外部合作方才会快速对号入座Concrete application stories help partners immediately locate the fit
永磁与稀土磁性材料Permanent magnets & rare-earth materials
支持配方筛选、磁性能预测、元素替代与性能—成本平衡分析。Support formulation screening, magnetic-property prediction, element substitution, and performance-cost tradeoff analysis.
铁镍及相关功能材料Fe-Ni and related functional materials
适用于微观结构演化、磁致相关行为、工艺参数优化与性能窗口探索。Useful for microstructure evolution, magneto-related behavior, process optimization, and design-window exploration.
高熵氧化物与复杂多元体系High-entropy oxides & complex multicomponent systems
适合处理高维成分空间、复杂相行为与多尺度耦合问题。Well suited to high-dimensional composition spaces, complex phase behavior, and multi-scale coupling problems.
科研平台与联合实验室Research platforms & joint labs
可作为联合项目基础设施，承接模型开发、数据平台、算力流程和对外展示。Can serve as shared infrastructure for model development, data systems, compute workflows, and external communication.
对外可信度表达Credibility Signals
比起堆很多信息，更重要的是让外部一眼看到“这家公司靠谱”More important than volume is helping visitors instantly see that the company is credible
团队背景Team strength
强调 AI + 材料 + 产业化的交叉背景，以及科研与工程并重的团队组合。Highlight an interdisciplinary team spanning AI, materials science, and commercialization.
技术成果Technical outcomes
可展示论文、专利、软件著作权、关键方法突破与代表性平台能力。Show publications, patents, software IP, method breakthroughs, and platform capabilities.
合作进展Partnership progress
可逐步补充已公开的合作单位、联合项目、讲座活动与生态伙伴信息。Gradually add public collaborations, joint projects, talks, and ecosystem partnerships.
品牌资料Brand materials
官网应与 BP、公司简介、演示视频、FAQ、对外邮件模板保持统一口径。The website should align with the deck, company one-pager, demo video, FAQ, and outbound messaging.
发展进展Milestones
把公司阶段讲清楚，有助于增强投资人与合作方判断A clear stage narrative helps investors and partners understand momentum
2024
公司建立与底层能力搭建Company formation & core-stack buildout
完成团队搭建、技术路线聚焦与磁性材料 AI 建模底层能力沉淀。Built the initial team, focused the roadmap, and established the core AI-for-magnetics stack.
2025
产品化推进与外部验证Productization & external validation
推进平台形态、试点合作和对外沟通资料，逐步形成更标准化的服务能力。Advanced productization, pilot collaborations, and more standardized external-facing materials.
2026
品牌升级与生态连接Brand upgrade & ecosystem expansion
强化官网、BP 与合作页面的一致性，更适合投资人、学校、企业和战略伙伴场景。Strengthen consistency across the website, deck, and partner materials for broader stakeholder use.
常见问题FAQ
补上 FAQ，能显著降低首次沟通门槛A strong FAQ lowers friction for first contact
两者都做，但表达方式不同：对高校和研究机构强调方法、模型、联合课题与平台共建；对企业强调效率、成本、部署与结果可用性。Both. For academia we emphasize methods, joint projects, and platform co-building; for industry we emphasize efficiency, cost, deployment, and usable outcomes.
可以。P0 阶段就可以帮助梳理问题、数据基础和可行性路径，必要时从公开文献、计算数据与试点任务开始搭建最小闭环。Yes. The P0 phase can help define the problem, assess data readiness, and start from literature, computed data, or a minimal pilot loop.
建议优先补充：正式 logo、团队照片、公开合作单位 logo、代表性论文/专利、演示视频、下载版公司简介，以及针对投资人或学校的独立落地页。Priorities include an official logo, team photos, public partner logos, publications/IP, a demo video, a downloadable one-pager, and dedicated pages for investors or academic partners.
联系我们Contact
把官网变成真正可转化的入口Turn the website into a real conversion surface
无论你是投资人、学校老师、研究机构负责人，还是产业客户与生态伙伴，都可以通过这里发起第一轮沟通。建议在正式上线前，把邮箱、微信二维码、公司简介下载链接和演示视频入口都补齐。 Whether you are an investor, professor, institute lead, industrial team, or ecosystem partner, this section should support a clean first outreach. Before launch, add your final email, QR codes, downloadable one-pager, and demo-video link.
邮箱Email
contact@muqiao.ai
官网域名Website
www.muqiao.ai
适合的来访主题Good first-touch topics
投资交流 / 联合课题 / 技术试点 / 平台合作
Investor intro / joint project / technical pilot / platform partnership