RiskVantage AI
RiskVantage AI provides a contract negotiation platform that grades inbound agreements against a company's preferred, fallback, and walk-away positions using a deterministic knowledge-graph engine, then drafts redlines with domain-adapted small language models. The system ensures every risk decision is explainable and consistent, with no hallucinated outcomes, and can be deployed inside a company's own cloud for regulated data.
- Legal Technology
- Enterprise Software
- Artificial Intelligence
- Software Only
Funding
Founders
Founder details are not available yet.
Product
Problem
Legal teams reviewing inbound contracts rely on manual review processes that are time-consuming, inconsistent, and prone to missing hidden liabilities. Standard AI chatbots offer opinions rather than reliable risk assessments, leaving organizations unable to systematically enforce their negotiated positions across every agreement.
Solution
RiskVantage Negotiate grades each inbound agreement against the positions your team actually holds—preferred, fallback, walk-away—and drafts the redline back using deterministic reasoning rather than a chatbot's opinion. The platform separates decision-making from drafting: all risk evaluations are computed in a knowledge graph where positions, tolerances, and rules live in an ontology, ensuring every rule evaluates the same way every time with zero hallucinated risk decisions. Domain-adapted small language models handle the writing of redlines and responses, while the graph guarantees the underlying logic. The same playbook built for daily contracts automatically becomes the baseline for due diligence and integration when an acquisition is announced, enabling pre-built knowledge of what the company will accept.
Target Audience
Primary users are legal and procurement teams at mid-to-large enterprises, particularly those in SaaS-heavy industries, who negotiate high volumes of inbound contracts and conduct M&A integrations.
Features
- Knowledge-graph-based decision engine with ontology-defined positions, tolerances, and rules for fully deterministic risk evaluation
- Domain-adapted small language models for drafting redlines without making risk determinations
- Missing intake factors are treated as absent, producing the same evaluation every time rather than a probabilistic guess
- Playbook reuse across negotiation and M&A due diligence, with the same positions applied to acquisition contracts
- Automated identification of duplicate SaaS tools post-acquisition, saving 30–35% on spend
- Proactive flagging of hidden liabilities such as missed change-of-control consents
- Deployable inside a company's own cloud environment for regulated data
- Every finding reports the rule that fired and the tolerance rung reached, with blocking versus advisory flags