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Bring clarity to AI governance, manage risk, and turn assurance into your advantage.

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CognitiveView

AI governance. Continuous assurance.
Confidence across your AI lifecycle.

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Bright legal office with a six-step Legal AI Governance workflow: identify the AI system, define its use case, assess risks, implement controls, capture evidence and make a defensible assurance decision.

Legal AI Governance

Govern Legal AI.Assure Every Decision.

AI is transforming legal research, contract analysis, discovery, drafting and client services. CognitiveView helps legal organizations discover AI, assess risk, govern its use, evaluate performance, build evidence and make defensible AI readiness decisions.

Start AI ReadinessTalk to an Expert
  • AI Governance
  • AI Assurance
  • Legal AI

The Legal AI Shift

AI is entering the legal workflow.

Legal AI is moving from experimentation into everyday professional workflows. Research, drafting, contract review, discovery and client services are increasingly supported by AI.

  • Legal Research
  • Contract AI
  • E-Discovery
  • Legal Drafting
  • Legal Copilots
  • AI Agents
  • Client-Facing AI

Without a governance framework

The Governance Gap

AI adoption moves forward. Visibility and accountability fall behind.

  • Unknown AI
  • Unknown use
  • Unknown risk
  • Unknown controls
  • Unknown evidence
  • Unknown decision
Readiness is difficult to prove.

A connected path to assurance

With CognitiveView

Bring each AI system, risk and decision into one governed workflow.

  • Discover
  • Define
  • Assess
  • Govern
  • Evaluate
  • Evidence
  • Assure
  • Authorize
  • Monitor
Defensible AI readiness decisions.

But adoption creates a new governance question:

Can you prove the AI is ready to use?

Start AI Readiness

Legal AI Use Cases

Govern AI across the legal workflow.

Explore common legal AI use cases and see the key risks, governance considerations and how CognitiveView helps you move from risk to assurance.

The AI Assurance Workflow

From legal AI risk to assurance.

CognitiveView connects the activities that are often fragmented across legal, compliance, risk, security, privacy, IT and business teams.

  1. 01

    AI System

    Discover

    Identify legal AI tools, providers and the teams accountable for their use.

    Stage outcome
    AI inventory & accountable owner
  2. 02

    Use Case

    Define

    Set the intended purpose, permitted users and boundaries for client data.

    Stage outcome
    Documented purpose & scope
  3. 03

    Risk

    Assess

    Assess accuracy, confidentiality and the impact of AI on legal decisions.

    Stage outcome
    Prioritized legal AI risk profile
  4. 04

    Controls

    Govern

    Establish human review, access rules and safeguards for privileged information.

    Stage outcome
    Assigned controls & review owners
  5. 05

    Evaluation

    Validate

    Test source accuracy, output quality and safeguards against real legal tasks.

    Stage outcome
    Performance & control test results
  6. 06

    Evidence

    Document

    Connect assessments, test results and approvals in a traceable evidence record.

    Stage outcome
    Reviewable evidence & audit trail
  7. 07

    Assurance

    Review

    Review residual risks and evidence to determine whether the use is ready.

    Stage outcome
    Evidence-backed readiness decision
  8. 08

    Authorization

    Approve

    Approve the defined use with clear conditions, limits and an accountable sign-off.

    Stage outcome
    Scoped approval & usage conditions
  9. 09

    Monitoring

    Monitor

    Track changes, incidents and performance to keep the authorization current.

    Stage outcome
    Ongoing oversight & reassessment

From evidence to action

AI Readiness Decision

A decision backed by controls, evaluation and evidence.

Three possible outcomes
  • Ready

    The defined use meets the agreed readiness criteria.

    Authorize use and monitor
  • Ready with conditions

    Use can proceed within documented limits and safeguards.

    Assign conditions and review dates
  • Not ready

    Material risks or evidence gaps need to be addressed.

    Resolve gaps and reassess
See the Full Workflow

Legal AI Risk

Assess the risks that matter to legal AI.

Understand where legal AI can introduce exposure. Connect each risk to practical safeguards, clear ownership and evidence your team can review.

Built for Legal Teams

Your practice. Your business. One standard of trust.

Whether you advise clients or guide an enterprise, bring clarity to how AI is assessed, approved and monitored.

Research / Legal AI

Legal Research AI

Legal research, case-law analysis, precedent discovery, knowledge retrieval and research copilots.

Assess Use Case

From risk to assurance

01

Key Risks

  • Hallucinated authorities
  • Inaccurate legal analysis
  • Outdated information
  • Incomplete research
  • Lack of source traceability
02

Governance

  • Define intended use
  • Validate sources
  • Human review
  • Testing and evaluation
  • Ongoing monitoring
03

Outcome

  • Understand risk
  • Implement controls
  • Build evidence
  • Make a readiness decision
10 areas of legal AI riskIdentify exposure. Put safeguards in place.
  • Accuracy

    01

    Unsupported citations and incorrect analysis can undermine legal advice and decisions.

    Governance focus

    Verify sources and review outputs

  • Confidentiality

    02

    Client information and privileged material need protection throughout the AI workflow.

    Governance focus

    Set data boundaries and access rules

  • Privacy

    03

    Personal information in documents and prompts needs appropriate handling and retention.

    Governance focus

    Minimize data and control retention

  • Security

    04

    Unauthorized access and manipulated inputs can expose sensitive legal information.

    Governance focus

    Test access controls and safeguards

  • Human Oversight

    05

    Consequential legal work needs an accountable reviewer with authority to intervene.

    Governance focus

    Define review and escalation paths

  • Reliability

    06

    Changes to models or workflows can affect the consistency of legal AI performance.

    Governance focus

    Evaluate performance over time

  • Explainability

    07

    Teams need to understand how an output was produced and which sources support it.

    Governance focus

    Maintain traceable sources and rationale

  • Bias & Fairness

    08

    Uneven outputs can affect how people, matters and legal positions are evaluated.

    Governance focus

    Test across representative scenarios

  • Vendor Risk

    09

    Third-party tools introduce dependencies around data use, model changes and assurance.

    Governance focus

    Review providers and ongoing changes

  • Regulatory Requirements

    10

    AI use needs to align with applicable professional duties and regulatory obligations.

    Governance focus

    Map obligations to controls and evidence

Turn risk awareness into a readiness decision.

Assess your legal AI use case and connect risks, controls and evidence in one governance workflow.

Explore Legal AI Risk

For law firms

Give legal teams confidence to use AI responsibly.

Bring consistent governance to research, drafting and client work, with safeguards that protect the trust your practice is built on.

  • Protect client data and privileged information
  • Set clear policies and human review responsibilities
  • Build evidence for important AI decisions
Discuss AI governance for your firm

For corporate legal

Govern AI across the enterprise.

Connect legal with risk, privacy, security, compliance and procurement to make informed AI decisions across the business.

  • Assess internal tools and third-party AI providers
  • Align legal requirements with enterprise controls
  • Maintain oversight as AI use and risks evolve
Discuss your enterprise AI needs