Trustero AI, a leader in Multi-Agent AI for governance, risk, and compliance (GRC) solutions, today announced a major relaunch of its Evidence Management system, delivering a fully unified, intelligent system that transforms how enterprises collect, map, and analyze compliance evidence.
For many organizations, compliance evidence is scattered across dozens of disconnected repositories, collected manually, and left static after upload. Trustero’s reimagined Evidence Management system solves this end-to-end, from automated collection and centralized storage to AI-powered analysis that turns raw evidence into actionable compliance intelligence.
The Problem: Scattered, Static Evidence is Costing Organizations Thousands of Hours
Modern enterprises manage compliance evidence across a growing number of systems, including SharePoint folders, cloud environments, ticketing tools, and more. Managing this sprawl manually creates audit risk, operational inefficiency, and significant staff burden. Traditional GRC platforms offer little relief, relying on slow, error-prone manual uploads with no analytical value once evidence is collected.
The Solution: A Unified, Intelligent Evidence System
Trustero’s enhanced Evidence Management system introduces three transformative capabilities:
- Centralized Evidence Collection. Trustero’s Receptors automate evidence collection from dozens of popular systems, including AWS, Jira, and more. The new Folder Scan capability syncs entire directories from existing repositories like SharePoint and Google Drive, eliminating manual uploads and giving compliance teams a single, trusted source of truth across all their evidence.
- AI-Powered Evidence-to-Control Mapping. Once evidence is collected, Trustero’s AI analyzes both the evidence and potential controls to automatically recommend the best match, removing the need for manual mapping This dramatically accelerates the compliance workflow and reduces the risk of mismatched or missing evidence during audits.
- Trustero Intelligence (TI) Copilot. The TI Copilot will bring an interactive AI assistant working with agents directly into the evidence workflow, enabling teams to query, correlate, filter, and analyze evidence using natural language. Key capabilities include:
- Correlation: Combine multiple pieces of evidence to generate new “derived evidence.”
- Row-by-Row Analysis: Perform automated counting and pass/fail analysis on tabular evidence.
- Random Sampling: Select random samples from population evidence data to generate new “derived evidence.”
- Natural Language Filtering: Slice large datasets instantly (e.g., “show only production environment data”).
- Semantic Search: Query evidence content using goal-based queries.
- Playbooks: Save any Copilot workflow as a reusable, scheduled playbook, such as a weekly executive risk report.
Additionally, Trustero’s unique versioning capability stores every version of collected evidence and automatically surfaces the version applicable to each audit’s specific time frame, ensuring accuracy and eliminating guesswork during audits.
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