Platform

Predict Risk. Prevent Loss.

RiskWise continuously ingests billions of signals, extracts the causal drivers of emerging risk, and predicts where they lead: litigation, regulatory action, product recalls, reputational damage. Months to years before they materialize.

14,000+

Legal sources monitored
continuously

Billions

Of signals across news, social,
legal, academic, and regulatory channels

6+ years

Of structured risk
intelligence history

Why RiskWise

Go beyond monitoring. Predict where risk leads.

Media monitoring tracks mentions and scores sentiment. Traditional risk intelligence solutions extrapolate from historical data. Neither can ingest the full evidence landscape and reason over it in real time.

RiskWise extracts causal drivers from heterogeneous sources, attributes them to specific entities through epistemic reasoning, and predicts where they lead. The result is intelligence that is forward-looking, explainable, and tied to outcomes your business actually measures.

Risk Index chart showing risk trajectory forecasted to reach 8.0 in April 2026

How It Works

An end-to-end intelligence pipeline built for risk

Every layer feeds the next. Every output is continuously evaluated.

Select any layer to explore further.

High-recall retrieval · Proprietary reranking

Reasoning

Driver Discovery

Causal risk driver extraction & hierarchy

Risk LLMs

Perceived & actual risk · Entity attribution

Intelligence

Risk Indices

Comparable, calibrated · Outcome-tied metrics

Litigation Forecasting

Evidence chains that precede mass tort by years

Company-Specific Insights

Entity-level attribution across exposure vectors

Deep Research Reports

Cited, customizable analyst-depth reports for underwriting and due diligence

Context Graph

Entity Relationships

Entity relationships · Risk propagation

Decision Traces & Precedent

Decision traces & precedent

Continuous Evaluation Risk Benchmarks Model Validation Learning

Agents Specialized agents operate at every layer →

Outcome Prediction

Calibrated to the outcomes you care about

Risk indices are only valuable if they predict something real. RiskWise ties every signal to the negative outcomes that define loss for your business, and tracks whether our predictions materialize.

Validated across opioid litigation (six month foresight), ultra processed foods (three year early warning), and generative AI risk (22 drivers identified pre ChatGPT).

Litigation predictor chart forecasting future mass tort risk based on early evidence chains

Future Litigation

Track the trajectory from early scientific concern to mass tort formation. Surface the evidence chains (research funding, regulatory signals, plaintiff activity) that precede litigation by years.

Recalls & Regulatory Action

Detect when risk drivers cross regulatory thresholds. Monitor consumer complaints, agency investigations, and compliance shifts to predict when action becomes likely.

Reputational Harm

Separate transient social media noise from durable reputation risk. Track when sentiment, media amplification, and risk driver intensity converge into material exposure.

Data Foundation

High-fidelity signal, not high-volume noise

RiskWise's hybrid retrieval pipeline combines high-recall search across heterogeneous sources with proprietary reranking models that transform broad coverage into targeted, high-precision signal.

Our Query Builder Agent validates coverage across data sources before a single document enters the pipeline. It constructs queries, evaluates results, identifies gaps, and iterates until coverage is verified.

Heterogeneous Data Sources

NewsSocial MediaAcademicRegulatoryEnterprise

MotionsBriefsCase Law

↓

Query Agent

Constructs · Evaluates
Iterates · Validates

iterative refinement

High-Recall Search

Coverage validation
Gap detection

↓

Proprietary Reranking LLMs

N specialized models
High-Recall → High-Precision

↓

✓ Verified, High-Precision Documents

Risk Understanding

From raw signal to entity-level attribution

Sentiment tells you the world is worried. It doesn't tell you whether that worry reflects genuine exposure. RiskWise separates perceived risk from factual risk, then extracts the underlying drivers and attributes them to specific entities.

Across 12,941 documents analyzed, only 6.8% contain genuine exposure evidence. RiskWise's job is to find that signal — and attribute it to the right entities at 0.97 accuracy, outperforming leading frontier models on every risk metric.

Select a risk topic to see how RiskWise traces it

Quantification

Comparable risk indices tied to real outcomes

Every risk, driver, company, and product is quantified with indices encoding both perceived risk and factual risk. Indices are calibrated, comparable across topics, and tied to outcome variables that match your definition of loss.

Insurers use them to price emerging exposure. Financial teams use them to find alpha before consensus forms. CPGs use them to decide when to reformulate.

RiskWise Risk Indices: 18-Month View

Risk Context Graph

How risk connects, propagates, and compounds

The Context Graph maps entities, drivers, evidence, and outcomes into a single queryable structure. Risk signal diffuses through corporate hierarchies, supply chains, and co-exposure relationships, so even low-visibility companies get reliable scores.

Propagation Pathways

Trace how risk cascades through subsidiaries, suppliers, and co-exposed peers. Quantify portfolio impact before contagion spreads.

Under-Covered Entities

Low-visibility companies inherit signal from parents, peers, and supply chains. Reliable scores even where direct evidence is sparse.

Decision Traces

Every assessment is persisted as searchable precedent. Query the reasoning behind any score and what happened in similar cases.

Emerging Exposure Hubs

Surface companies rapidly becoming central nodes in risk conversations. Act on forming vulnerabilities before consensus pricing.

Emergent Structure

Risks don't happen in isolation

Risks interact, amplify, and cascade across sources, industries, and time. Social media concern triggers research funding, which fuels litigation years later. The Context Graph surfaces these patterns and predicts where they lead.

Continuous Improvement

Every signal makes the system smarter

Risk intelligence degrades if it isn't tested against reality. RiskWise operates a closed-loop evaluation flywheel: every output is measured, every model is benchmarked, and every feedback signal improves the next cycle. Not a quarterly refresh. A system that compounds in accuracy every day.

Closed Loop

Every cycle compounds precision

01 · Ingest

Ingest & Attribute

Billions of signals filtered and attributed to entities and risk drivers in real time using proprietary thinking-tuned models.

02 · Evaluate

Evaluate in Production

Every model output is continuously evaluated against proprietary risk benchmarks with automated performance validation.

03 · Measure

Measure Against Outcomes

Predictions are tracked against real events — litigation filings, regulatory actions, recalls — closing the loop between signal and consequence.

04 · Improve

Retrain & Improve

Results feed back into model fine-tuning, search optimization, graph construction, and agent refinement.

Agentic Workflows

Specialized agents for every stage of risk analysis

Purpose-built AI agents, each trained on our curated risk dataset and validated against our evaluation framework. They don't just retrieve information. They reason over it, cite it, and deliver structured intelligence at a quality bar that matches senior analysts.

RiskWise Deep Research alert feed showing prioritized risk events

Research Quality

26%

Fewer errors than frontier AI alone, when powered by RiskWise data.

Insight Depth

33.8%

More insightful risk analysis vs. web-only research.

Error Reduction

40%

Fewer mistakes from purpose-built risk models on risk tasks.

Query Agent

Validates search coverage across heterogeneous data sources before downstream processing, ensuring every analysis starts from complete, relevant data.

Risk Driver Extraction

Surfaces the causal factors that create and amplify risk through iterative reasoning. Genuine causal decomposition, not keyword matching.

Risk Deep Research

Generates structured, cited research reports on new and evolving risks with the depth of a senior analyst and the speed of an autonomous agent.

Implications & Mitigators

Traces how historical decisions and graph pathways led to specific outcomes, turning precedent into actionable foresight.

Interoperability

Agent-native infrastructure

Risk intelligence shouldn't be locked in a dashboard. RiskWise is engineered as infrastructure for autonomous workflows, accessible to any agent, embeddable in any pipeline, interoperable with any system.

MCP

Model Context Protocol

RiskWise publishes risk signals, drivers, indices, and graph context through MCP servers. Any compatible agent can access our intelligence in real time.

A2A

Agent-to-Agent Protocol

Agents discover, delegate, and orchestrate across systems using A2A. RiskWise plugs into multi-agent workflows, from risk triage workflows to portfolio rebalancing to supply chain monitoring, without custom integration.

Explore How RiskWise Applies to Your Risk Landscape

We'll walk through a live analysis of emerging risks relevant to your organization.

Book a Demo