Evidence intake
Connect or upload contracts, spend exports, proposals, quotes, meeting notes, emails, benchmarks, and market research.
Data & AI
Fact base development
with your data.
Fact base development turns internal inputs (contracts, spend, supplier history, approvals, meeting notes) and external inputs (benchmarks, quotes, market research, web research, analyst notes) into a negotiation fact base your team can use for strategy.
Internal and external inputs for the negotiation fact base
If you want nuance, provide constraints and evidence (contracts, RFPs, cost models, spend exports). If you do not have them yet, use AI to generate the data request list.
Context
What's changing, when it renews, and what good looks like (price, term, scope, SLAs).
- Current terms
- Renewal date / deadline
- Target / acceptable / walk-away
Evidence
We can ingest the artifacts and numbers your team already trusts.
- Contracts, order forms, and redlines
- RFPs, proposals, quotes, and benchmarks
- Cost models, usage, and spend exports (PO/invoice)
Constraints & approvals
Capture non-negotiables and approval gates so outputs are realistic.
- Legal clauses and risk flags
- Finance constraints (cash flow, prepay rules)
- Security requirements and approvers
How evidence becomes a trusted fact base
Negotiation data is useful only after the team can see what is known, what is missing, what conflicts, and which analyses are reliable enough to shape the strategy.
AI extraction
Structure commercial facts, supplier signals, constraints, source references, and analysis-ready assumptions.
Human validation
Review gaps, conflicts, assumptions, and completed analyses before they influence strategy or approvals.
Strategy update
Use the validated fact base to create targets, options, levers, concession logic, and stakeholder-ready briefs.
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.
Common procurement questions (and what to provide)
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.
| Question | Best source | How AI helps |
|---|---|---|
| What's our supplier spend, volume, and leverage? | Your PO/invoice history, spend cube, supplier master, renewal calendar. | Summarize patterns, highlight concentration/renewal risk, and propose leverage questions and trade packages. |
| What does the market say about price and terms? | 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. |
| What does the supplier actually want? | Meeting notes, email threads, call transcripts, stakeholder context. | Extract signals and hypotheses, then generate the next-best questions to validate intent and constraints. |
| Do they have a cash-flow issue (or is it a tactic)? | 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. |
| Are we working with them across other categories? | Supplier master + contract inventory + category mapping (enterprise integrations help here). | Surface cross-category context, bundling opportunities, and stakeholder alignment questions. |
If you do not have the data yet
Use AI to generate a targeted prep checklist: what to request from Finance, Legal, IT/Security, and the supplier plus the exact questions to ask.
Integrations (as needed)
Enterprise deployments can align the app with your CRM/SRM and procurement systems so spend, contract inventory, and supplier context are easier to reference during prep.
Security question?
If your team needs to understand storage, processing, and retention, start with the Security overview.
Turn the fact base into negotiation intelligence
Once the evidence is assembled, use these pages to connect procurement data to copilots, supplier analytics, scenario modeling, and decision briefs.
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