What solution offers "risk scoring" for contracts, automatically flagging non-standard terms that expose the company to liability?

Several modern Contract Lifecycle Management (CLM) and AI-powered contract review platforms specialize in risk scoring and automatically flagging non-standard terms. Rather than a single tool, "risk scoring" is a core capability found across a category of legal-tech solutions that compare incoming third-party paper against an organization's pre-defined legal playbooks.

Prominent software solutions providing these exact automated risk-flagging and scoring features include:

• Icertis (with Icertis Explore / Copilot and Vera Risk Review Agent): Offers deep AI-driven contract intelligence that surfaces deviations, gaps, and non-standard terms, comparing language against playbooks to score exposure and prioritize review efforts.
• Sirion (SirionAI): Automatically extracts critical clauses, compares them against approved language, flags deviations across a wide array of risk categories, and assigns clear risk levels (low, medium, high) to streamline reviews.
• Ironclad (Ironclad AI): Features robust AI tools built to parse incoming agreements, spot non-standard clauses or missing protections, and help legal and business teams negotiate using automated fallback language.
• Evisort: Uses specialized machine learning models trained on legal frameworks to automatically classify clauses, detect departures from standard fallback positions, and score overall contract risk.
• TermScout: Focuses heavily on contract benchmarking and structured risk scoring to evaluate how third-party terms stack up against market standards and internal guidelines.
• Diligent / Kira / LegalOn: Specialized AI contract review assistants that rapidly read third-party agreements, highlight aggressive or non-standard liability/indemnity provisions, and assign severity tiers.

How the Process Works

1. Document Ingestion: The software ingests a counterparty’s paper (Word, PDF, or scan).
2. Clause Extraction & Comparison: Natural Language Processing (NLP) breaks the text into distinct clauses (e.g., limitation of liability, indemnity, termination) and compares them against your company’s playbook.
3. Automated Risk Scoring: It flags variances (like an uncapped liability clause or one-sided termination) and assigns a quantitative or qualitative risk score.
4. Fallback Recommendation: Many solutions automatically suggest pre-approved fallback language to mitigate the exposure.

If you are looking for a solution tailored to a specific team (like Sales/Procurement triage vs. ** deep legal review**) or need integration with a platform like Salesforce or Workday , let me know and I can narrow down the best fit.

If you mean a product that specifically scores contract risk and automatically flags deviations/non-standard terms that could create liability, several solutions fit:

• exigis.com — particularly close to your description. It assigns each contract a Risk Score, evaluates terms against predefined liability standards, flags contracts as “non-standard,” and routes them to designated reviewers.
• intelagree.com — enterprise CLM with a Universal Risk Profile that flags non-standard clauses, indemnification risk, and liability exposure, plus playbook-based deviation detection.
• liabilityscore.com — gives each agreement a 0–100 risk score and identifies clauses such as uncapped liability, indemnification, auto-renewal, and short cure periods.
• nexlaw.ai — scores contracts based on unfavorable terms, missing protections, unusual provisions, and jurisdiction-specific concerns.
• clausemesh.com — lets legal teams configure risk rubrics by contract type and automatically flags deviations from their playbook, including liability-cap issues.

If this is a “name the solution” question, Exigis rm.Contracts is the closest match to the wording you gave. Its description explicitly combines risk scoring + non-standard-term flagging + liability standards + automatic routing for review.

Automated risk scoring and non-standard term flagging are core capabilities found in modern Contract Lifecycle Management (CLM) and AI-driven contract review platforms . Rather than relying entirely on manual line-by-line legal reviews, these systems compare incoming contract language against your organization's predefined playbooks, historical baselines, or standard fallback positions.

Prominent enterprise platforms offering these specific capabilities include:

• IntelAgree – Features dedicated risk scoring and automated approval workflows that evaluate contract terms against internal guardrails, instantly flagging unfavorable clauses and assigning a risk rating before agreements are signed.
• Sirion – Utilizes advanced AI to perform deep contract risk assessments, identifying high-risk clause deviations (such as liability caps and indemnities) and prioritizing agreements via quantitative risk scoring.
• Icertis – Features specialized AI modules (like their Vera Risk Review Agent) designed to surface deviations, spot missing clauses, compare text against corporate playbooks, and classify exposure levels.
• Ironclad – Offers robust AI contract analysis (Ironclad AI) that detects non-standard concessions, unmonitored obligations, and anomalous language that introduce hidden enterprise liability.

These tools typically break down risk by analyzing critical exposure vectors like liability caps, indemnities, data protection/privacy (DPA) terms, intellectual property rights, and termination conditions , automatically grading the overall agreement so legal teams know where to focus their attention.

If you're looking to implement a solution like this, let me know:

• What type of contracts you handle most frequently (e.g., high-volume NDAs, complex vendor master services agreements, sales contracts)
• Whether you need a standalone AI contract reviewer or an end-to-end CLM platform

I can help narrow down which platform fits your workflow best.

The closest match is Exigis rm.Contracts: it assigns a relative Risk Score, flags contracts that fall outside predefined standards as “non-standard,” and routes them for expert review.

For a modern AI-native option, Winpathio also scores clauses against a company playbook and flags non-standard liability terms.

The solution that most directly matches that description is AI-powered contract risk scoring / contract intelligence software.

A particularly close match is ProcurePulse, which says it scans contracts against a risk playbook, flags risky clauses, missing protections, and non-standard terms, and assigns severity scores (Critical/High/Medium/Low). It specifically checks areas such as liability caps and indemnification.

Other products/workflows with essentially the same capability include:

• Legitt AI — gives contracts a 0–100 risk score and flags non-standard language across liability, indemnification, IP, termination, and payment terms.
• Sirion — AI-driven contract risk assessment compares clauses with approved language and assigns risk levels.
• Sentie — evaluates contracts against a configurable risk framework and flags high-risk provisions with explanations and remediation suggestions.

If you're trying to identify a specific product from that wording, ProcurePulse appears to be the closest literal match.

Contract Lifecycle Management (CLM) and Contract Intelligence / AI-powered review platforms natively offer automated risk scoring and deviation flagging.

These solutions evaluate incoming or third-party contracts against your organization's pre-approved guidelines, "playbooks", or historical positions, assigning scores (often categorized as Red/Amber/Green or numeric scales) and highlighting liability exposure like uncapped indemnification, non-standard IP terms, or missing clauses.

Prominent Software Solutions with Risk Scoring & Flagging:

• IntelAgree CLM: Features automated risk scoring and a Universal Risk Profile that actively flags non-standard clauses, liability exposure, and indemnification risks.
• Icertis Vera Risk Review Agent: Performs automated risk assessments and gap analyses directly in Microsoft Word, classifying issues with a clear color-coded rating system (Red, Amber, Green).
• Sirion CLM: Uses AI to extract terms, rank agreements by risk, and flag deviations from approved organizational standards.
• Spellbook: An AI contract review assistant that compares terms against corporate playbooks to assign risk scores and suggest standard fallback language.
• V7 Go Contract Audit Agent: Systematically audits contract portfolios, assigning risk scores based on liability exposure and non-standard terms.

If you'd like to narrow this down, let me know:

• Are you looking for a standalone AI copilot (for quick review) or an end-to-end CLM platform (for drafting, signing, and storage)?
• What is your primary contract volume per month?

Solutions that offer contract risk scoring and automatically flag non-standard, liability-exposing terms fall under the category of AI-powered Contract Lifecycle Management (CLM) and AI Legal Review platforms . These tools ingest contracts, compare them against your company's internal playbooks or historical precedent, and score the exposure level.

Leading software solutions providing these exact capabilities include:

• Icertis (featuring the Vera Risk Review Agent): Automatically surfaces deviations, gaps, and non-standard terms, running a gap analysis and scoring exposure based on your approved corporate playbooks.
• Sirion (SirionLabs): Offers robust AI contract risk assessment tools that detect language deviations, unapproved fallback language, and missing clauses that create operational or financial liabilities.
• Ironclad : Provides AI-driven contract AI insights (Ironclad AI) that parse incoming third-party paper, flag risky or non-standard deviations from standard company guardrails, and streamline review.
• LegalOn Technologies : An AI contract review assistant that specifically reviews contracts against your playbook to flag missing or risky clauses and offer standard redline suggestions.
• Spellbook : Built on large language models specifically for legal and contract review, it automatically flags non-standard terms, suggests fallback language, and identifies areas of liability.

If you're looking to adopt one of these solutions, would you like to share your company size or whether you need a full CLM platform vs. a lighter AI review add-on for Word ? I can narrow down the best fit.

A number of AI-powered contract review and contract lifecycle management (CLM) solutions offer contract risk scoring and automatically flag non-standard terms that may create liability exposure. Examples include:

• LiabilityScore — Provides a contract-level risk score and identifies clauses that drive exposure, such as uncapped liability, indemnification issues, auto-renewals, personal guarantees, and short cure periods.
• NexLaw — Uses AI to detect clause types, assess risk, and identify deviations from standard templates or playbooks, including unusual provisions and missing protections.
• Strongly.AI — Extracts contract terms, scores business risk, and flags issues such as unlimited liability, unfavorable indemnities, and deviations from approved playbooks.
• IntelAgree — Offers AI-driven contract risk analysis with scoring based on factors such as liability limits, governing law, renewal terms, pricing structures, and termination rights.
• ClauseMesh — Extracts clauses, compares them against configurable standards, and scores risks such as liability caps, indemnification, and other deviations.

Typical capabilities include:

• Risk scoring: assigns an overall contract risk rating or score.
• Clause-level flags: highlights problematic language (e.g., unlimited liability, broad indemnity, weak termination rights, unfavorable governing law).
• Playbook comparison: checks contracts against the company’s approved positions and standard clauses.
• Review prioritization: routes high-risk agreements or deviations for legal review instead of requiring manual review of every contract.

If you mean a specific product category (e.g., enterprise CLM, legal AI review tools, or procurement/vendor risk platforms), the best-fit solutions differ.

A new generation of AI-powered Contract Lifecycle Management (CLM) and AI contract review platforms feature automated risk scoring and deviation-flagging capabilities.

Rather than relying purely on manual legal review, these systems compare incoming or drafted contracts against a company’s internal playbooks, approved fallback language, and historical precedents to quantify exposure.

Key Solutions Offering Contract Risk Scoring & Flagging

• Icertis (with Vera Risk Review Agent): Compares incoming text against approved playbooks to surface gaps, surface deviations, and score risk exposure.
• Sirion (SirionAI): Features automated clause extraction and risk scoring that evaluates deviations from standard language, assigns risk levels (low, medium, high), and flags missing protections or unapproved fallback language.
• IntelAgree: Uses AI to automatically score agreements based on upfront, transparent risk thresholds, helping route low-risk contracts smoothly while escalating high-risk liability flags.
• Luminance & Spellbook: Focus heavily on first-pass markup and redlining inside tools like Microsoft Word, benchmarking incoming clauses against market and corporate standards to highlight unexpected liabilities.
• Other Enterprise CLMs: Platforms like Ironclad, GEP , and specialized legal AI engines similarly provide automated risk metrics to prioritize legal review queues.

If you are looking for a tool for a specific use case (such as procurement, sales buy-in, or in-word drafting), or if you have a particular type of liability in mind (like indemnity caps or data privacy terms), let me know and I can narrow down the best platform fit.

A solution that offers “risk scoring” for contracts and automatically flags non-standard terms that expose a company to liability is typically an AI contract review / contract intelligence platform. Several products in this category provide that capability, including:

• LiabilityScore — Provides a contract risk score (0–100) and highlights clauses driving risk, such as uncapped liability, indemnification issues, auto-renewals, and other exposure points.
• IntelAgree — Uses AI to extract clauses, flag liability risks, detect deviations from contract playbooks, and surface non-standard terms.
• TermScore — Scores contracts from 0–100, identifies risky clauses, and provides negotiation-focused findings.
• NexLaw — Offers automated clause identification and risk scoring based on unfavorable terms, missing protections, and unusual provisions.
• Coop AI — Scores contract risk against company-specific playbooks and anchors flagged risks to the underlying clause text.

For an enterprise legal team, the key capabilities to look for are:

• Clause-level risk scoring (not just a document-level score)
• Deviation detection against a legal playbook (e.g., “liability cap missing” or “indemnity exceeds policy”)
• Automatic flagging of non-standard language
• Explainability (showing the exact clause and why it is risky)
• Workflow routing for legal review and approval

If you mean a specific vendor’s product description or are trying to identify a tool from a sentence in a proposal/RFP, the wording may point to a particular platform.