Keep Obligations Covered and Decisions Defensible
Compliance work isn’t just about tracking requirements, it’s about applying them consistently and proving they’re addressed. Resolver uses AI to standardize requirement mapping, reduce duplicate work, surface gaps, and help draft controls, so your team can move faster with control designs that manage risk efficiently while maintaining a clear, auditable record of every decision.
Creating the Right Controls at Scale Is Harder Than It Should Be
As requirements grow across frameworks and teams, compliance teams need to continuously create and maintain controls. But without clear guidance and consistency, control creation becomes time-consuming, uneven, and difficult to scale.
Aligned Controls. Complete Coverage. Defensible Execution.
Keep your control environment structured, efficient, and audit-ready. Reduce unnecessary work, address gaps faster, and maintain a clear record of how obligations are covered.
- Maintain alignment across frameworks: Ensure controls are applied consistently across requirements, even as frameworks and obligations evolve by applying standardized structures and mappings.
- Eliminate redundant work: Reduce repeated mapping and duplicate controls by reusing what already exists across the organization. Identify overlap across requirements and connect them to common controls instead of rebuilding coverage each time.
- Stay ready for scrutiny: Keep a clear, traceable record of decisions, mappings, and evidence so reviews and audits don’t require manual reconstruction.
Clarity on exposure. Control over your risk posture.
Understand how your control environment actually reduces risk. Identify where exposure remains, where effort is wasted, and where to act, so you can make decisions with confidence and defend them when it matters.
See your true exposure
Understand which risks are genuinely mitigated and where coverage breaks down based on real data and gap analysis, not assumptions.
Cut through control noise
Identify overlapping controls and focus effort on the ones that materially reduce risk exposure.
Stand behind your decisions
Explain your risk posture clearly to executives, auditors, and regulators, without manual reconciliation.
Pinpoint where you are actually exposed
Connect risks, controls, and incidents to understand how exposure is actually being managed. Identify where controls exist, where they fall short, and where no coverage is in place – based on real activities, not static mappings.
- Risk-to-Control Mapping: Connect risks, controls, incidents, and actions to see exactly where exposure exists.
- AI Gap Analysis: Identify risks with no controls or weak mitigation before they lead to real-world impact.
- Risk Event Linkage: Validate control performance using real incidents and near-misses.
Build controls that are aligned and reusable
Standardize how controls are defined and applied across the organization. Reuse existing controls where possible and create new ones quickly when needed.
- AI-Powered Control Recommendations: Surface existing controls that align with similar risks to reduce duplication and speed up alignment.
- AI-Assisted Control Generation: Generate structured draft controls aligned with industry best practices for uncovered risks, while keeping full human review and approval.
- Centralized Control Library: Maintain reusable, standardized controls across the organization.
Get a clear, defensible view of control coverage
Bring risk, control, and compliance data together to create a single view of control coverage and performance. Understand where coverage is strong, where gaps remain, and communicate it clearly, without stitching together reports manually.
- Integrated Data Model: Combine risk, control, and incident data to surface patterns, gaps, and areas of concern.
- Outcome-to-Risk Traceability: Link control outcomes such as test outcomes and failures back to risk exposure to clearly show how risks are being mitigated.
- Unified Reporting & Dashboards: View control coverage across risks and requirements in one place without pulling data from multiple systems.
Key Features of Resolver’s Risk Control Management Solutions
Integrated Risk, Control, and Risk Event Data
Bring all relevant data into one place to create a consistent view of exposure.
Traceable Data Relationships
Maintain clear links between risks, controls, risk events, and outcomes to support analysis.
AI-Powered Gap Analysis
Continuously surface risks that are not fully mitigated so teams can act earlier.
AI-Powered Control Recommendations
Identify controls already used across the organization to reduce duplication.
Centralized Control Library
Standardize and reuse controls across teams to maintain consistency.
AI-Assisted Control Generation
Generate structured control drafts to address uncovered risks quickly.
Real-Time Reporting
Access up-to-date insights without building reports manually.
Audit-Ready Data Structure
Maintain consistent, defensible records of control coverage.
Workflow Automation
Coordinate control-related activities without manual follow-ups.
No-Code Configuration
Adapt workflows and data structures without engineering support.
Know your risk coverage without second guessing
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Frequently Asked Questions
- How does Resolver support audit readiness?
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Resolver maintains linked records across requirements, controls, outcomes, and evidence so teams can show coverage clearly without manually pulling documentation together.
- What happens when a requirement is not covered by an existing control?
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AI-powered gap analysis flags the missing coverage, and AI-assisted control generation can produce a structured draft control to accelerate remediation while keeping final review and approval with your team.
- Does AI make compliance decisions for us?
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No. AI supports interpretation, analysis, and draft generation, but people stay in control of all reviews, approvals, and final decisions.
- How does AI help without adding complexity?
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Resolver’s AI highlights gaps, surfaces overlapping requirements and controls, and recommends or generates draft controls based on your data, so teams can move faster without starting from scratch. All outputs are transparent, reviewable, and require human approval, with full traceability linking every AI-assisted insight back to underlying risks, controls, and decisions for audit readiness.