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NextB2B长什么样?B2B版WorkBuddy能否给找钢网带来新生机?

亿邦智库黄斌 2026-09-14 20:43
亿邦智库黄斌 2026/09/14 20:43

邦小白快读

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你可重点了解找钢网联合腾讯发布的NextB2B产品的核心价值、使用方式与发展阶段,这类产业智能体工具未来会逐步改变B2B贸易的交易模式,和泛贸易行业从业者的日常工作息息相关。

1. 核心功能上,它是首个基于腾讯WorkBuddy打造的B2B全流程AI智能体解决方案,覆盖采购、销售、内勤、运营全场景,可解决找货难、业务增长慢、经营管理效率低三类核心问题,能自动完成采购寻源比价、客户跟进报价、交易风险监测、内勤事务处理、经营报表生成、行情监测等工作,未来可实现智能体自动匹配交易。

2. 使用与收费上,基础版本定价2万元,增值功能按需单独收费,Token消耗据实充值;用户安装腾讯WorkBuddy客户端后,即可在发现应用板块找到入口使用,覆盖金属能源、化工塑料、汽摩配件、电子元器件等多个行业。

3. 当前该产品还处于辅助人工完成交易的阶段,距离智能体自主完成交易还有一定距离,需要更多企业接入生态才能发挥更大价值。

品牌商可重点关注NextB2B发布折射出的B2B领域交易趋势、智能工具价值与定价参考,为自身数字化布局、经营提效提供方向。

1. 行业趋势上,未来B2B交易将从传统的人找货模式转向Agent匹配Agent的A2A模式,智能体将成为新的交互入口,原有平台的流量入口价值将逐步向能力供给层转移;大模型应用下半场的核心竞争力是产业纵深能力,通用技术能力无法构建长期壁垒。

2. 经营提效上,这类全流程AI智能体可覆盖采购寻源比价、自动报价跟进客户、全链路交易风险监测、内勤事务自动处理、经营报表自动生成等场景,能有效降低跨岗位协同成本,减少经营风险。

3. 产品定价参考上,面向B端的智能体产品普遍采用基础版本+增值模组+按需充值的分层定价结构,品牌商研发自有数字化工具时可参考该逻辑,平衡标准化服务与个性化需求的收费设计。

B2B领域卖家可重点关注NextB2B释放的交易模式变化信号、效率提升路径、生态合作机会与潜在风险,提前布局抓住智能体时代的增长红利。

1. 增长机会上,未来统一标准下的A2A交易网络成型后,接入网络的销售智能体可7*24小时在线,自动发现匹配全行业商机、跟进客户报价,交易效率将获得非线性提升,同时每笔交易的履约数据会沉淀为智能体信誉评级,成为新的信任背书。

2. 可落地的提效工具方面,卖家可直接使用NextB2B这类产品,实现采购端自动比价、交易全链路风险监测(覆盖工商、诉讼、舆情、逾期应收、货权等维度)、内勤事务自动处理、经营日报自动生成等功能,降低经营成本与风险,其基础版定价2万元,接入门槛较低。

3. 合作与风险提示:有行业能力的卖家可通过腾讯WorkBuddy开放平台提交申请,接入NextB2B生态共享流量;如果未及时跟进智能体转型,未来可能在新的交易网络中失去曝光机会,原有平台流量优势将逐步弱化。

泛贸易流通、大宗商品领域的工厂可重点关注NextB2B落地带来的数字化升级启示、业务拓展机会与智能系统搭建参考,助推自身生产经营效率提升。

1. 数字化升级启示:工厂可借助全流程AI智能体打通采购、销售、内勤、运营全链路,采购端实现自动寻源、供应商比价,降低原材料采购成本;销售端自动跟进客户、生成报价,同步监测全链路交易风险;内勤端自动处理订单、库存、对账、开票等事务,减少跨部门沟通成本,还可通过自动生成的经营日报、行情监测数据为生产决策提供参考。

2. 商业拓展机会:工厂可接入NextB2B所在的A2A交易网络,成为智能体可直接匹配的供应方,对接全行业采购需求,减少中间流通环节的成本损耗。

3. 系统搭建参考:工厂自建智能应用时,可借鉴通用AI底座+行业技能组件+场景专家模组的三层架构,把自身生产、交易环节的经验沉淀为可复用的标准化技能组件,对接内部ERP、CRM等系统,实现业务流的智能化改造。

To B数字化服务商可重点关注NextB2B落地折射的行业发展趋势、B端客户核心痛点与可复用的解决方案框架,找准智能体时代的业务定位。

1. 行业趋势判断:当前B2B领域的智能体界面布局正在逐步趋同,未来市场将进入全面竞争与价值重分配阶段,不少软件厂商将逐步演变为通用智能体的插件或API供给方;大模型应用下半场的竞争核心是产业纵深能力,仅靠通用AI能力无法构建壁垒,只有深入产业场景、沉淀真实交易数据与行业经验才能建立护城河,未来服务的价值锚点将从流量运营转向行业技能供给。

2. 客户核心痛点:当前B2B贸易类客户普遍存在找货效率低、获客增长难、经营管理成本高、交易风险难防控、内部多系统打通不畅、跨岗位协同效率低等共性问题。

3. 解决方案参考:可借鉴Skill封装-MCP连接-A2A协同的三层逻辑搭建产品,先把行业经验封装为可调用的标准化技能组件,再通过模型上下文协议对接客户内部系统实现业务可执行,最终接入统一交易网络实现跨主体智能体协同。

B2B类平台商可重点关注找钢网的转型实践、行业风向变化、生态建设方向与风险规避要点,找准智能体时代的平台定位。

1. 风险提示:当前智能体界面布局正在趋同,行业即将迎来全面竞争与价值重分配,超级科技大厂的通用AI能力会持续切割行业共性利润,如果平台固守原有流量入口定位,可能出现“平台给智能体打工”的局面,若不能沉淀足够的产业深度能力,将逐步被市场淘汰。

2. 头部平台转型参考:找钢网未选择自建独立AI平台,而是将自身积累的行业认知、交易数据、履约流程沉淀为可复用的技能组件、协议标准和智能工作流,接入腾讯WorkBuddy的通用智能体底座,从流量入口层转向能力供给层,以此触达更广泛的企业用户,构建智能体时代的能力壁垒。

3. 运营与生态建设方向:平台可启动智能体生态合作伙伴计划,开放接入端口吸引行业伙伴共建统一协议下的A2A交易网络;未来平台的护城河不再是网站入驻用户规模,而是付费调用平台行业技能的智能体规模;运营层面可围绕采购、销售、内勤、运营等核心场景打造专家智能体模组,为客户提供全流程智能服务。

产业经济、数字经济领域的研究者可重点关注NextB2B落地折射的产业新动向、商业模式创新方向与行业发展待解新问题,积累产业智能体发展的研究样本。

1. 产业新动向:此前行业提出的B2B向A2A演进的预言正式进入产品落地阶段,B2B产业互联网正迎来价值链重塑,智能体时代B2B交易的运行逻辑初步成型,即通过Skill封装将行业经验转化为AI可执行的标准化技能,通过MCP连接打通企业内部业务系统实现操作落地,通过A2A协同实现跨主体的智能体自动匹配交易,随之带来交易效率非线性提升、信任机制重构、价值链重新分配等变化,平台价值锚点将从用户注意力转向行业数据的深度与精度。

2. 商业模式创新:NextB2B采用基础版本+增值模组+Token充值的三层收费结构,平台商业模式从传统的收取流量费、交易佣金,转向技能组件调用收费,从服务自有网站用户转向为全生态智能体提供能力支撑。

3. 待解新问题:当前产业智能体仍处于辅助人工交易的阶段,距离智能体自主交易尚有距离,A2A网络运转需要足够多的主体接入、统一协议的广泛认可、配套信任与争议解决机制建立,这些都是行业发展面临的共性问题,无法靠单个企业独立完成。

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Quick Summary

General audiences can focus on the core value, usage, and development stage of NextB2B, an industrial AI agent product jointly launched by Zhaogang.com and Tencent. This category of industrial intelligent tools will gradually reshape B2B trading models and become closely tied to the daily work of practitioners across the broader trade sector.

1. Core functions: As the first full-process B2B AI agent solution built on Tencent’s WorkBuddy, it covers full-scenario workflows across procurement, sales, back-office administration, and operations. It addresses three core pain points: difficulty sourcing goods, slow business growth, and low operational management efficiency. The tool automates tasks including supplier sourcing and price comparison, customer follow-up and quotation, transaction risk monitoring, back-office administrative processing, operational report generation, and market trend tracking, with the long-term goal of enabling automatic transaction matching between AI agents.

2. Usage and pricing: The basic version is priced at RMB 20,000, with value-added features billed separately on demand and Token consumption charged via actual usage top-ups. After installing the Tencent WorkBuddy client, users can access the product via the discovery section. It serves a wide range of sectors including metals and energy, chemicals and plastics, auto and motorcycle parts, and electronic components.

3. Current development stage: At present, the product remains in the phase of assisting humans to complete transactions, and is still some distance away from enabling fully autonomous transactions by AI agents. Delivering greater value will require more enterprises to join the ecosystem.

Brand owners can focus on the B2B transaction trends, intelligent tool value, and pricing benchmarks reflected in the launch of NextB2B, to inform their own digital transformation and operational efficiency improvement strategies.

1. Industry trends: Going forward, B2B transactions will shift from the traditional “people searching for goods” model to an Agent-to-Agent (A2A) model, where AI agents become the new interaction entry point, and the value of original platform traffic entry points will gradually migrate to the capability supply layer. The core competitiveness in the second half of large model application development lies in deep vertical industry expertise; generic technical capabilities alone cannot form long-term barriers.

2. Operational efficiency gains: This category of full-process AI agents covers scenarios including supplier sourcing and price comparison, automated customer follow-up and quotation, full-link transaction risk monitoring, automated back-office processing, and automated operational report generation, effectively reducing cross-role collaboration costs and mitigating operational risks.

3. Pricing reference: B2B-facing AI agent products generally adopt a tiered pricing structure consisting of a basic version, value-added modules, and on-demand usage top-ups. Brand owners can reference this logic when developing their own digital tools, to balance pricing design for standardized services and personalized needs.

B2B sellers can focus on the signals of transaction model shifts, efficiency improvement pathways, ecosystem partnership opportunities, and potential risks indicated by the launch of NextB2B, to position early and capture growth dividends in the AI agent era.

1. Growth opportunities: Once a standardized A2A transaction network is formed in the future, sales agents connected to the network will operate 24/7, automatically identifying and matching cross-industry business opportunities and following up with customer quotations, driving non-linear improvements in transaction efficiency. Meanwhile, fulfillment data from each transaction will accumulate into an agent reputation rating, forming a new form of trust endorsement.

2. Actionable efficiency tools: Sellers can directly adopt products such as NextB2B to realize functions including automated price comparison on the procurement side, full-link transaction risk monitoring (covering dimensions such as business registration status, litigation records, public sentiment, overdue accounts receivable, and cargo rights), automated back-office processing, and automated daily operational report generation, reducing operating costs and risks. The basic version is priced at RMB 20,000, representing a relatively low access threshold.

3. Partnership and risk notes: Sellers with strong industry capabilities can submit applications via the Tencent WorkBuddy open platform to join the NextB2B ecosystem and access shared traffic. Those that fail to keep pace with AI agent transformation may lose exposure in the new transaction network in the future, as the value of traffic advantages on traditional platforms gradually erodes.

Factories in the broad trade circulation and bulk commodity sectors can focus on the digital upgrade insights, business expansion opportunities, and intelligent system construction references brought by the rollout of NextB2B, to boost their own production and operational efficiency.

1. Digital upgrade insights: Factories can leverage full-process AI agents to connect end-to-end workflows across procurement, sales, back-office administration, and operations. On the procurement side, this enables automated supplier sourcing and price comparison to reduce raw material purchasing costs; on the sales side, it supports automated customer follow-up and quotation generation, along with synchronized full-link transaction risk monitoring; on the back-office side, it automates order processing, inventory management, account reconciliation, and invoicing to reduce cross-departmental communication costs. Automatically generated daily operational reports and market monitoring data can also inform production decision-making.

2. Business expansion opportunities: Factories can join the A2A transaction network where NextB2B operates, becoming suppliers directly matchable by AI agents, connecting with procurement demands across the industry and reducing cost losses from intermediate circulation links.

3. System construction references: When building proprietary intelligent applications, factories can reference the three-tier architecture of a general AI base + industry skill components + scenario expert modules, codifying their own production and transaction experience into reusable, standardized skill components that connect to internal ERP, CRM and other systems to realize intelligent transformation of business workflows.

To-B digital service providers can focus on the industry development trends, core pain points of B2B clients, and reusable solution frameworks reflected in the rollout of NextB2B, to identify their business positioning in the AI agent era.

1. Industry trend judgment: The interface design of AI agents in the B2B sector is gradually converging, and the market will soon enter a phase of full competition and value redistribution. Many software vendors will gradually evolve into plugin or API providers for general-purpose AI agents. The core of competition in the second half of large model application development is deep vertical industry capability; generic AI capabilities alone cannot build barriers. Moats can only be established by diving deep into industry scenarios and accumulating real transaction data and domain experience, and the value anchor of services will shift from traffic operation to industry skill supply in the future.

2. Core client pain points: B2B trade clients currently face common challenges including low goods sourcing efficiency, difficult customer acquisition growth, high operational management costs, hard-to-control transaction risks, poor integration between internal systems, and low cross-role collaboration efficiency.

3. Solution reference: Providers can build products following the three-tier logic of Skill encapsulation – MCP connection – A2A collaboration: first encapsulate industry experience into callable, standardized skill components; then connect with clients’ internal systems via the Model Context Protocol to enable executable business operations; and finally access the unified transaction network to realize cross-party AI agent collaboration.

B2B platform operators can focus on Zhaogang.com’s transformation practices, shifting industry winds, ecosystem development directions, and key risk avoidance points, to identify their platform positioning in the AI agent era.

1. Risk notes: The interface design of AI agents is currently converging, and the industry is poised to enter full-scale competition and value redistribution. The general AI capabilities of large technology giants will continue to capture common industry profits. If platforms cling to their original positioning as traffic entry points, they may end up “working for AI agents”; without building sufficient deep industry capabilities, they will gradually be eliminated by the market.

2. Reference for leading platform transformation: Rather than building an independent AI platform, Zhaogang.com codified its accumulated industry know-how, transaction data, and fulfillment processes into reusable skill components, protocol standards, and intelligent workflows, and connected them to Tencent WorkBuddy’s general AI agent base. It shifted from a traffic entry layer to a capability supply layer, thereby reaching a broader base of enterprise users and building capability moats in the AI agent era.

3. Operation and ecosystem development directions: Platforms can launch AI agent ecosystem partner programs, opening access ports to attract industry partners to jointly build an A2A transaction network under unified protocols. In the future, a platform’s moat will no longer be the scale of registered users on its website, but the scale of AI agents that pay to call the platform’s industry skills. On the operational side, platforms can build expert agent modules around core scenarios including procurement, sales, back-office administration, and operations, to provide clients with full-process intelligent services.

Researchers in industrial economics and the digital economy can focus on the new industrial trends, business model innovation directions, and unresolved industry development issues reflected in the rollout of NextB2B, to accumulate research samples on the development of industrial AI agents.

1. New industrial trends: The previously predicted evolution of B2B toward A2A has officially entered the product implementation stage, and B2B industrial internet is undergoing value chain restructuring. The operating logic of B2B transactions in the AI agent era is taking initial shape: industry experience is converted into AI-executable standardized skills through Skill encapsulation; internal enterprise business systems are connected for operational execution through MCP connections; cross-party automatic transaction matching between AI agents is realized through A2A collaboration. These shifts will bring non-linear improvements in transaction efficiency, reconstruction of trust mechanisms, and redistribution of the value chain, with the value anchor of platforms shifting from user attention to the depth and accuracy of industry data.

2. Business model innovation: NextB2B adopts a three-tier fee structure of basic version + value-added modules + Token top-ups. The platform business model is shifting from traditional traffic fees and transaction commissions to fees for skill component calls, and from serving users on its own website to providing capability support for AI agents across the entire ecosystem.

3. Unresolved emerging issues: At present, industrial AI agents remain in the stage of assisting human transactions, and are still some distance from fully autonomous agent transactions. The operation of A2A networks requires sufficient participant access, broad recognition of unified protocols, and the establishment of supporting trust and dispute resolution mechanisms. These are common challenges facing industry development that cannot be addressed by a single enterprise alone.

Disclaimer: The "Quick Summary" content is entirely generated by AI. Please exercise discretion when interpreting the information. For issues or corrections, please email run@ebrun.com .

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【亿邦原创】2026年9月2日,找钢网集团与腾讯WorkBuddy团队在深圳腾讯WorkBuddy生态发布会上首次联合发布NextB2B产品,并于9月10日,在上海找钢网总部举办的“第二届贸易企业AI应用论坛暨NextB2B产品发布会”上正式面向行业发布,同步启动NextB2B生态合作伙伴计划。

01 NextB2B是找钢网为大宗商品B2B交易网站的智能体化作的一次有益探索

NextB2B是首个基于腾讯WorkBuddy打造的B2B全流程AI Agent解决方案,核心架构由采购、销售、内勤、运营四大企业智能体专家模组构成,以其全流程的智能服务来解决找货、业务增长与经营管理三类核心难题。其具体功能覆盖六大模块:采购寻源与供应商比价(根据产品型号、规格自动匹配);询价识别与报价生成(自动跟进客户并记录历史往来);风险监测(工商、诉讼、舆情、逾期应收、货权风险);内勤事务处理(订单、库存、资金、对账、开票及跨部门催办);经营信息整理与日报自动生成;以及按预定时间自动生成经营日报并持续监测市场行情和交易风险。几乎涵盖了大宗钢材交易的全部流程。

该智能体的收费模式采用了“基础版本+增值模组+Token充值”三层结构,基础版本标准定价为人民币20,000元,增值模组按需另行收费,Token消耗据实充值。重点覆盖行业包括电子元器件、电工电气、汽摩配件、化工塑料、农牧产品、货代物流、金属能源等。下载与使用方式:NextB2B作为“Buddy应用”内嵌于腾讯WorkBuddy生态中,用户需先安装腾讯WorkBuddy客户端(可通过腾讯WorkBuddy官网获取),在任务栏顶端“WorkBuddy”旁点击“发现应用”即可找到NextB2B入口。行业伙伴如需接入NextB2B生态,可通过腾讯WorkBuddy开放平台官网open.workbuddy.cn提交Buddy应用创建申请,完成审核后配置行业能力模块。

NextB2B的技术底座是由三层构成的,其底层是腾讯WorkBuddy的通用AI智能体能力(Agent Runtime、任务拆解、工具调用);中间层是找钢网提供的泛贸易流通行业通用的SKILL(技能组件)、MCP(模型上下文协议)、数据和工作流;上层是采购、销售、内勤、运营四大专家模组。

这一整体构架可以看出,找钢网将自己积累的行业认知、真实交易数据、客户沟通数据、履约服务数据与中台运营流程,系统化地“蒸馏”为可复用的Skill组件、MCP协议与Agentic工作流。其中,内置A2A(Agent to Agent)交易能力l,让企业Agent持续在线,自动发现、匹配并连接全行业商机。所有接入的企业共享同一张统一的全行业交易网络,在统一的ATP协议下互联互通。这意味着B2B交易的参与方有可能从“人找货”变为“Agent匹配Agent”,交易网络的密度和效率将获得非线性提升。业界则有大佬说的,B2B有可能变成A2A了的预言,至此落地。

02 NextB2B映证了产业智能体对B2B产业互联网平台的价值链重塑

年初,业界就有大佬说的,B2B有可能变成A2A了的预言,至此落地。9月10日,亿邦动力董事长郑敏与农信互联集团董事长薛素文的“千峰对话”,恰好与NextB2B的发布形成了深刻的理论呼应。

在那场对话中,郑敏提出了一个尖锐的判断:智能体界面布局正在趋同,最左侧功能栏(公网问答、私域助理、技能、专家、连接器生态),右侧对话框——这与当年门户网站和零售电商网站的演化路径一模一样。界面定型之后必然是全面竞争和市场价值重新分配。“如果说现在有点儿‘商户给平台打工’的感觉,接下来是不是会有‘平台给智能体打工’的局面?”

薛素文对此完全认同。他进一步指出,软件行业的“断头论”正在成为现实——许多软件厂商逐步去掉自家登录界面,转而成为通用智能体的插件或API。“关键还是你这个‘专家’是不是某个领域的‘真专家’。”

NextB2B恰好是这一判断的产品化验证。找钢网没有选择自建一个独立AI平台,而是将自身积累的行业Skill、MCP和工作流“接入”腾讯WorkBuddy的Agent底座。用户不再需要打开找钢网的网站或App,而是在WorkBuddy的对话框里调用NextB2B的能力完成采购寻源、报价跟进、风险监测。这正是“平台变成Skill”的典型形态——找钢网从价值链的入口层,主动降维到能力供给层,但换来的是触达更多企业用户的可能性。

薛素文的核心观点是:“大模型的上半场拼的是模型能力,下半场拼的是产业纵深,高地不在云端,在产业现场。产业互联网平台必须继续向下扎,扎到操作系统这一层。”NextB2B的四大专家模组,本质上就是找钢网将“产业纵深”封装为Agent可调用的操作层——采购寻源不是简单的信息检索,而是基于真实交易数据训练的匹配逻辑;风险监测不是通用舆情抓取,而是嵌入B2B交易场景的逾期应收、货权风险模型。

郑敏进一步警示:“超级科技大厂会不停研发出更锋利的刀片,从面上在一层一层地向下片共性利润。产业互联网公司只有加速度往下扎,做出产业厚度。否则,刀片片到现有价值面的时候,产业互联网平台就被片没了。”NextB2B的发布,可以视为找钢网“往下扎”的一次主动卡位——用行业数据和交易经验构建Agent时代的能力壁垒,而非被动等待被“片没”。

03 产业智能体的基本运行逻辑与规则优势是否就成定型?

NextB2B所设计的产业智能体,基本运行逻辑可以归纳为“Skill封装—MCP连接—A2A协同”三层递进。其中,第一层,是Skill封装。将行业Know-how从人的经验转化为AI可执行的标准化技能组件。找钢网把找货、比价、报价、风控、对账等环节蒸馏为Skill,每个Skill对应一个可独立调用的业务能力。

第二层,是MCP连接。通过模型上下文协议将AI能力与企业的ERP、CRM、财务系统对接,让Agent不仅能“理解”还能“执行”。NextB2B通过MCP将AI嵌入B2B企业的真实业务流,订单、库存、资金、开票等操作可被Agent直接调用。

第三层,是A2A交易协同。当足够多的企业Agent接入统一交易网络,Agent之间的自动发现、匹配和交易将成为可能。NextB2B规划的ATP协议下的A2A交易网络,本质上是在构建一个“Agent版”的B2B交易基础设施——买方的采购Agent与卖方的销售Agent直接对话完成询价、比价、下单,人的角色从“操作者”变为“监督者”。

这一智能体的架构在于:交易效率的非线性提升(Agent 7×24在线,毫秒级匹配替代人工比价);信任机制的重构(每一次交易履约沉淀为Agent信誉数据,形成可验证的信任评级);价值链的重新分配(平台从“流量入口”变为“能力供给”,价值锚点从用户注意力转向行业数据的深度和精度)。

NextB2B的发布,是将这种内部能力外部化的一次关键尝试——从“自己用AI”走向“让行业用AI”。而它对产业互联网平台的真正启示在于:也许,在智能体时代,平台的护城河不再是有多少用户在你的网站上,而是有多少Agent在付费调用你的Skill。

结语:一切才刚开始,基本框架还有待继续发展

找钢网与腾讯WorkBuddy的这次联手,放在产业互联网的演进坐标上看,意义不在产品本身,而在于它打开了一扇门。门后是一条尚未被充分开垦的路:B2B贸易的Agent化。

过去几年,消费互联网的AI化路径已经清晰——推荐算法、智能客服、对话式购物助手,本质上是让AI服务于“人的决策”。但在B2B交易平台为代表的产业互联网领域则不完全相同。它的决策链条更长、参与角色更多、信任成本更高、履约环节更复杂。一单钢材贸易背后,是询价、比价、锁价、付款、提货、物流、开票、对账等十几个环节,涉及采购、销售、财务、内勤、物流多个岗位。消费端的AI助手可以帮你选一件衣服,但B2B的AI Agent要能替你完成一整套交易流程。

NextB2B的发布,是找钢网寻找新机会的一次系统性尝试。四大专家模组、MCP连接、A2A交易网络的规划,构成了一个完整的Agentic B2B交易架构雏形。但坦率地说,这仅仅是开始。目前的NextB2B还停留在“辅助人做交易”的阶段,距离“Agent自主完成交易”还有相当距离。A2A网络的真正运转,需要足够多的企业Agent接入,需要统一协议的广泛认可,需要信任机制和争议解决机制的同步建立。这些都不是一家企业、一个产品能独立完成的。

亿邦智库将持续关注人工智能、产业互联网发展与企业数据要素竞争力提升,并报道相关发展的新成果与新案例。联系邮箱为:huangbin@ebrun.com



本文首发于 亿邦动力 官方网站

文章来源:亿邦智库

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FAQ回顾

NextB2B是什么?

NextB2B是找钢网联合腾讯WorkBuddy团队打造的、首个基于WorkBuddy生态的B2B全流程AI Agent解决方案,核心包含采购、销售、内勤、运营四大企业智能体专家模组,覆盖大宗B2B交易全流程功能,可帮助企业解决找货、业务增长与经营管理三类核心难题,服务多类泛贸易流通行业。

企业如何接入使用NextB2B?

NextB2B作为Buddy应用内嵌于腾讯WorkBuddy生态中,普通用户需先安装腾讯WorkBuddy客户端,在“发现应用”板块即可找到入口使用;行业伙伴可通过腾讯WorkBuddy开放平台官网提交接入申请,审核通过后配置行业能力模块即可加入生态。

NextB2B的收费模式是怎样的?

NextB2B采用“基础版本+增值模组+Token充值”的三层收费结构,其中基础版本标准定价为20000元,增值模组可根据企业实际需求另行选购付费,服务使用产生的Token消耗按照实际用量据实充值。

产业智能体会给B2B交易模式带来哪些改变?

产业智能体将推动B2B交易从传统“人找货”模式转向“Agent匹配Agent”的A2A协同模式,企业智能体可7×24小时在线完成毫秒级商机匹配,重构交易信任机制,推动平台从流量入口转向行业能力供给,实现交易效率的非线性提升。

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