Appendix B: The Legal Tech Vendor RFP Matrix & AI-Ready’ Scorecard

This appendix provides two tools: a Vendor RFP Evaluation Matrix for scoring and comparing legal technology vendors on a consistent basis, and an AI-Ready Scorecard for assessing whether a vendor’s platform is architecturally prepared for the AI-augmented workflows described in Chapters 13-14.

Part 1: The Vendor RFP Evaluation Matrix

Evaluation Categories and Weightings

The weightings below reflect a balanced assessment. Adjust weightings based on your organisation’s specific priorities — a firm facing a regulatory deadline will weight compliance capabilities higher; a firm prioritising user experience will weight adoption factors higher.

Category	Weight	Subcriteria
Functional Fit	30%	Core feature coverage, workflow alignment, configurability, reporting capabilities
Integration	20%	API availability, native connectors (CRM, ERP, DMS), middleware compatibility, data export/import
User Experience	15%	Interface design, mobile access, learning curve, self-service capability
Security & Compliance	15%	Data encryption, hosting options (cloud/on-prem/hybrid), SOC 2/ISO 27001, data residency, privacy compliance
Vendor Viability	10%	Company size and funding, customer base, product roadmap, financial stability
Commercial Terms	10%	Pricing model, contract flexibility, implementation costs, ongoing support costs

Scoring Scale

Score	Definition
5 — Exceeds	Fully meets the requirement with additional capabilities beyond the specification
4 — Meets	Fully meets the requirement as specified
3 — Partially Meets	Meets the requirement with minor gaps or workarounds required
2 — Significant Gaps	Material gaps that would require custom development or process changes
1 — Does Not Meet	Requirement not addressed; no viable workaround

The Evaluation Scorecard

Category (Weight)	Vendor A	Vendor B	Vendor C
Functional Fit (30%)	[Score × 0.30]	[Score × 0.30]	[Score × 0.30]
Integration (20%)	[Score × 0.20]	[Score × 0.20]	[Score × 0.20]
User Experience (15%)	[Score × 0.15]	[Score × 0.15]	[Score × 0.15]
Security & Compliance (15%)	[Score × 0.15]	[Score × 0.15]	[Score × 0.15]
Vendor Viability (10%)	[Score × 0.10]	[Score × 0.10]	[Score × 0.10]
Commercial Terms (10%)	[Score × 0.10]	[Score × 0.10]	[Score × 0.10]
Weighted Total	[Sum]	[Sum]	[Sum]

Key RFP Questions by Category

Functional Fit:

Describe how your platform handles [specific workflow, e.g., multi-party contract negotiation with parallel review tracks]
Provide a demonstration of [specific feature] using our sample data/scenario
What configuration is required to support our [specific process requirement]?

Integration:

List all native integrations with [CRM/ERP/DMS platforms in use]
Describe your API architecture: REST/GraphQL, authentication method, rate limits, webhook support
Provide documentation for your data export capabilities: formats supported, scheduling, and completeness

Security & Compliance:

Where is data hosted? Can we specify data residency jurisdiction?
Provide your most recent SOC 2 Type II report and penetration test summary
Describe your data retention and deletion policies, including upon contract termination
How do you handle sub-processors, and what is your notification process for sub-processor changes?

Commercial:

Provide pricing for [X] users, [Y] contract volume, for a [Z]-year term
What costs are not included in the licence fee (implementation, training, integrations, premium support)?
What is your standard contract term, and what are the termination provisions?

Part 2: The AI-Ready Scorecard

Why AI-Readiness Matters

A legal technology platform purchased in 2026 will be expected to support AI-augmented workflows within 12–24 months of deployment. Selecting an AI-ready platform extends its useful life and maximises ROI. The AI-Ready Scorecard assesses a vendor’s preparedness across five dimensions.

The Scorecard

Dimension	Question	Score (1-5)	Notes
Data Architecture	Does the platform store data in structured, normalised formats with comprehensive metadata?

Data Architecture | Can data be exported in machine-readable formats (JSON, structured CSV) for AI training and RAG deployment? |API Maturity | Does the platform expose comprehensive APIs that enable external AI systems to read and write data? |API Maturity | Does the API support event-driven triggers (webhooks) for real-time AI workflow integration? |Native AI | Does the platform include native AI capabilities (summarisation, extraction, classification)? |Native AI | Can native AI features be disabled or replaced with the organisation’s preferred AI models? |Extensibility | Does the platform support custom AI model integration (bring-your-own-model)? |Extensibility | Can the platform serve as a data source for external RAG architectures? |Governance | Does the platform provide AI audit trails (inputs, outputs, model version, confidence scores)? |Governance | Does the platform support HITL workflows with configurable review checkpoints? |Total |/50 |

Scoring Interpretation

Score Range	AI-Readiness Assessment
40-50	AI-ready. The platform can support current and near-future AI workflows.
30-39	Partially ready. Some foundational capabilities exist; gaps should be addressed in the vendor roadmap.
20-29	Significant gaps. AI integration will require substantial workarounds or middleware.
Below 20	Not AI-ready. Selecting this platform will likely require replacement within 2-3 years as AI becomes essential.

The AI-Ready Scorecard is forward-looking insurance. A platform that scores well on functional fit today and strongly on AI-readiness will serve your organisation for years. Factor the AI-Ready score into your overall vendor evaluation — a slightly less feature-rich platform that is significantly more AI-ready is often the better long-term investment.