How it works
Two workflows. One platform. Whether you are preparing for a SOC 2 audit or building oversight records for AI systems, AssuranceOps helps you collect, structure, and maintain defensible evidence.
From auditor request to evidence packet
Connect your systems, map requirements to evidence sources, and produce structured audit packets with integrity metadata and control narratives.
Connect systems
Link GitHub, AWS, Okta, Drive, Jira, and other evidence sources
Map requirements
Upload auditor requests or define control-to-evidence mappings
Collect artifacts
Pull structured evidence with metadata, hashes, and provenance
Validate & review
Check freshness, assign ownership, and resolve exceptions
Export or maintain
Build audit packets or keep evidence current for continuous readiness
From AI use case to oversight record
Inventory AI systems, capture review and testing evidence, track monitoring and exceptions, and produce assurance records for boards and audit committees.
Inventory AI use cases
Catalog AI systems with purpose, scope, and stakeholders
Assign risk & review
Classify risk levels and define review requirements for each use case
Capture records
Collect approval decisions, testing results, and validation evidence
Track monitoring
Record post-deployment monitoring, drift detection, and exception events
Generate oversight packs
Produce board-ready and audit committee evidence summaries
What you get
Structured evidence objects
Every artifact includes control mapping, source metadata, timestamps, and integrity hashes.
Control narratives
Factual narratives that cite collected evidence IDs. No fabrication, only references to what was collected.
Exceptions and gaps
Clear documentation of missing evidence with alternatives and remediation paths.
Exportable packets
ZIP archives with an index, evidence files, narratives, and exceptions ready for auditor review.