证据采集
连接或上传合同、支出导出、提案、报价、会议记录、电子邮件、基准数据和市场研究。
Internal and external inputs for the negotiation fact base
如果您想要细微差别，请提供约束和证据（合同、RFPs、成本模型、支出出口）。如果您还没有，请使用 AI 生成数据请求列表。
背景
发生了什么变化，何时更新，以及看起来怎么样（价格、期限、范围、SLAs）。
- Current terms
- Renewal date / deadline
- Target / acceptable / walk-away
证据
我们可以获取您的团队已经信任的工件和数字。
- Contracts, order forms, and redlines
- RFPs, proposals, quotes, and benchmarks
- Cost models, usage, and spend exports (PO/invoice)
限制和批准
抓住不容谈判的因素和批准关口，使产出切合实际。
- Legal clauses and risk flags
- Finance constraints (cash flow, prepay rules)
- Security requirements and approvers
证据如何成为可信的事实基础
只有当团队能够看清哪些信息已知、哪些缺失、哪些存在冲突，以及哪些分析足够可靠到可以塑造策略时，谈判数据才真正有用。
AI 提取
将商业事实、供应商信号、约束条件、来源引用以及可供分析的假设结构化。
人工验证
在缺口、冲突、假设和已完成分析影响策略或审批之前，先进行审查。
策略更新
使用经过验证的事实基础来制定目标、选项、杠杆、让步逻辑以及可供利益相关方使用的简报。
Fact base output
Review facts, gaps, conflicts, assumptions, and completed analyses before strategy
The fact base is the handoff between raw data and negotiation judgment. It keeps AI-generated recommendations grounded in evidence that the team can inspect and approve.
AI drafts the first version from evidence and assumptions.
Humans review, edit, approve, and decide what to use.
Every round updates the strategy and memory loop.
Fact base
Northstar Packaging renewal
AI 84%In review
PrepareFact baseStrategyTacticsSimulationsMeetings
Used in outputs 38Needs review 6Conflicts 2
Pricing and commercials14 facts
Contract obligations9 facts
SKU-level pricing12 facts
Data coverage5 gaps
Completed analyses
10 readyRevenue comparison across packaging suppliers
Scope: this negotiation · Updated today
Term variation dollar impact analysis
Scope: this negotiation · Updated today
Cost-driver index and freight sensitivity
Scope: this negotiation · Updated today
Supplier profile and risk scan
Scope: this negotiation · Updated today
Gaps
Receiving-plant freight matrix still missing.
Conflicts
Two payment-term sources disagree.
Assumptions
Index exposure estimated from 8 SKU families.
常见采购问题（以及提供什么）
This is the prep gap in plain terms: the answer is usually in your internal systems, documents, and external market signals. AI helps you assemble it into a decision-ready brief and pressure-test options with game-theory scenarios.
| 问题 | 最佳来源 | 人工智能如何提供帮助 |
|---|---|---|
| 我们的供应商支出、数量和杠杆是多少？ | Your PO/invoice history, spend cube, supplier master, renewal calendar. | Summarize patterns, highlight concentration/renewal risk, and propose leverage questions and trade packages. |
| 市场对价格和条款有何看法？ | Benchmarks you trust, competing quotes, cost models/should-cost, analyst notes, peer comps, prior deals. | Turn evidence into assumptions + ranges, draft counter-arguments, and flag missing benchmarks to request. |
| 供应商真正想要什么？ | Meeting notes, email threads, call transcripts, stakeholder context. | Extract signals and hypotheses, then generate the next-best questions to validate intent and constraints. |
| 他们是否有现金流问题（或者这是一种策略）？ | Payment terms history, finance constraints, alternatives (prepay/discount), supplier signals. | Structure options (Net terms vs discount vs scope), draft talk tracks, and pressure-test concessions. |
| 我们是否在其他领域与他们合作？ | Supplier master + contract inventory + category mapping (enterprise integrations help here). | Surface cross-category context, bundling opportunities, and stakeholder alignment questions. |