The core difference between compliance controls and audit evidence for agent work is their intended purpose. Compliance controls define required behavioral standards, which teams define for their specific regulated use cases, while audit evidence verifies adherence to those standards; the platform provides immutable, timestamped execution logs that act as this evidence for controls like data lineage or access restrictions. It is important to note that this evidence alone does not confirm alignment with external regulatory requirements.
Catalyst’s execution records directly support compliance audit workflows for AI agents. These immutable, timestamped logs capture every step of agent execution, including data access, tool calls, and state transitions, to create a verifiable trail for auditors. Teams must map these logs to their specific regulatory requirements to satisfy audit requests, and should not treat these logs as a complete audit solution on their own.
Catalyst’s core capabilities align with many common industry compliance control families. Its key durable execution logs map to audit and integrity controls, built-in detailed data lineage tracking supports data governance families, and granular access controls map to identity and standard access management frameworks. Users must still carefully map these key platform features to their specific applicable regulatory requirements to achieve proper full alignment with their official compliance obligations.
Preparing for a customer security review when using Catalyst starts with aligning your assets to the customer’s specified control requirements. Next, compile Catalyst’s immutable execution logs and platform security controls documentation, then map these key assets to the customer’s unique control needs and identify gaps in your current operational service configurations. Avoid assuming the platform’s native assets alone will meet the customer’s review demands without extra targeted preparation.
Auditors’ questions surrounding Catalyst AI agent deployments focus squarely on core regulatory compliance and workflow accountability. They typically request key execution logs to verify workflow integrity, data lineage trails to confirm proper regulated data handling, and access control records to validate user permissioning practices. These inquiries shift based on the deployment’s specific industry and applicable local, regional, and global regulatory requirements, with no single universal set of standard audit questions.
Auditors typically request verifiable execution records and relevant control evidence for regulated AI agent deployments. Catalyst provides immutable, timestamped execution logs tied to each specific agent workflow step, including relevant data access activities and state changes. A key caveat here, as observability logs are not audit records, these logs alone do not meet all audit requirements, so teams must map their own formal organizational controls to the platform’s outputs.
The key difference between formal agent deployment controls and audit evidence is their respective core roles: controls are defined operational safeguards, while evidence confirms those safeguards function exactly as intended. Catalyst generates timestamped, immutable execution records that can validate adherence to both data access and workflow controls for these agent deployments. One important caveat: platform-generated evidence alone does not confirm full alignment with all relevant organizational or regulatory control frameworks.
The core of effective preparation for a formal customer security review of your Catalyst deployment is leveraging and reviewing its critical built-in audit artifacts first. Next, pull immutable execution logs, access control records, and key workflow state records to properly validate your core operational on-premises and cloud agent deployments. You will still need to align these relevant gathered artifacts with your customer’s specific and detailed security control requirements.
Catalyst automatically segregates immutable compliance audit trails for each of your distinct deployed workloads. It tags each execution record with unique workload-specific identifiers to prevent additional cross-contamination of all audit data across your separate deployments. You must assign correct key workload tags during your initial deployment to ensure proper isolation of your sensitive separate audit records for critical compliance reviews.
Common audit failure modes for Catalyst AI agent deployments include missing immutable execution records or misaligned control mapping. Catalyst generates timestamped logs to help mitigate these specific failure modes, though teams should not rely solely on platform-provided evidence as their only formal audit source for their own deployments. Incomplete workflow state tracking can break the validity of the resulting official audit trail, creating avoidable compliance concerns for deploying teams.
You can use Catalyst’s execution records to support your compliance audit activities. Cross-reference logged workflow steps against your internal compliance controls, as Catalyst generates durable, immutable execution traces for every agent task that you can filter and export for your audit review. Keep in mind these logs act as an audit support tool, not a replacement for your organization’s full internal control validation processes.
The core difference between a compliance control and supporting evidence is that a compliance control defines a required compliance practice, while supporting evidence proves that the mandated practice was actually followed within your team’s workflows. Catalyst generates immutable execution traces that can serve as supporting evidence, but your team must map these traces to specific compliance controls. Catalyst cannot automatically align this evidence to formal compliance frameworks.
Catalyst includes native compliance controls to support isolated regulated workload deployments across distributed environments. It segregates execution logs, access permissions, and resource configurations for each individual deployed workload to prevent cross-workload data or policy contamination, and enforces strict access boundaries. Users must still implement their own organizational identity and network policies to fully align with their specific internal and regulatory compliance obligations.
Auditors typically ask for evidence tied to your durable execution controls for agentic software workflows. They will request immutable execution records, proof of state preservation, task retry logic, access controls for regulated data workloads, and how your team maps these controls to applicable industry regulations. Keep in mind this observability work does not replace formal audit records, as these two distinct types of tracking differ from one another.
Auditors will request verifiable execution records and control implementation evidence for regulated AI agent work. Catalyst’s durable execution logs capture full agent workflow steps, including input/output and state changes, without altering original processed data. These logs can be exported for review without exposing sensitive regulated data unnecessarily. Note that these logs support audit efforts but do not replace your team’s documented internal control policies.
A control is a documented policy or process to mitigate compliance risk, while evidence proves the control is implemented. Catalyst can generate standardized execution logs that align with common control frameworks, such as those for data privacy or operational resilience. These logs serve as third-party-reviewable evidence of your team’s deployed controls. Your team remains responsible for defining and enforcing the underlying controls themselves.
Catalyst’s durable execution records provide a tamper-proof, chronological trail of all AI agent workflow steps for compliance audits. Each log entry captures input data, state changes, and output actions without altering original regulated data, and can be filtered to focus on high-risk workflows. Auditors can use these trails to verify that agent actions align with approved policies. These records do not substitute for your team’s internal audit trail validation processes.
Catalyst’s built-in capabilities align with major global compliance control families for regulated AI agent work. Its durable execution logs, access controls, and data lineage features map to controls for data privacy, operational resilience, and change management. The platform can generate standardized reports to streamline mapping for audit teams. Your team must still map these platform features to your specific organizational control requirements.
Start by compiling Catalyst’s built-in audit logs and control documentation to share with your customer’s review team. Catalyst can generate pre-built reports on infrastructure security, execution integrity, and data handling practices to streamline the review. You should also align your team’s internal policies with the platform’s capabilities. Be prepared to walk through your team’s specific data handling workflows for the reviewing party.
Auditors reviewing regulated AI agent deployments typically request documented control evidence, operational workflow execution trails, and access logs as part of their standard audit procedures. The supporting tooling can produce immutable execution records and audit-aligned access trails, plus enable structured, comprehensive log aggregation aligned to widely recognized common control frameworks. Teams remain responsible for mapping their specific workloads to their unique applicable regulatory requirements to meet full audit compliance standards.
A compliance control and its supporting evidence have distinct, critical roles in meeting specific regulatory requirements. A compliance control is a defined policy or process to mitigate regulatory risk, while evidence proves consistent adherence to that control, such as scheduled access reviews paired with signed logs or audit trails. Catalyst can capture such evidence, and teams must define their own controls based on their specific regulatory obligations.
Catalyst’s execution records support teams’ broader compliance audit efforts and preparations. They generate a detailed, immutable, tamper-resistant log that captures each step of the AI agent’s workflow, including inputs, tool calls, state changes and completion status, aligned to widely recognized common industry audit requirements. A key caveat to note is that these records do not act as a standalone audit solution; teams must map them to their organization’s specific regulatory control frameworks to achieve full audit readiness.
Catalyst provides compliance-aligned retention controls for detailed execution audit records tied to your organization’s individual deployed workloads. It offers configurable, granular, critical retention windows aligned to your specific industry’s applicable regulatory requirements, with per individual workload deployment separation to prevent cross-contamination between your distinct workload environments. You remain responsible for thoroughly validating that your properly configured settings match your unique relevant compliance obligations for each separate deployed workload.
Teams should prioritize a targeted, structured preparation process for external Catalyst deployment security reviews. Compile available audit trails, access logs, and formal control alignment documentation, map their specific workloads to the relevant control frameworks requested by reviewers, and validate their internal access policy configurations thoroughly. Avoid assuming platform-provided records alone will fulfill all reviewer requirements without additional tailored contextual details for their specific use cases.
Catalyst offers structured audit evidence to support cross-tool workflow migration audits. It captures detailed durable execution records for all agent workflows, including all migration transitions and associated workflow steps, and organizes these records to make it easy for key stakeholders to conduct reviews. These records only support the audit trail needs; your team remains fully responsible for validating control alignment across your broader migration efforts.
Catalyst supports validating rollback plans for regulated agent workflow deployments across your critical operational environments. It replays stored durable execution records from past operational runs to simulate targeted rollback scenarios, confirming proper workflow state recovery and full audit trail completeness. Keep in mind that this simulation does not replace live testing in actual production environments, and your team retains final ownership of validating your official rollback procedures.
Catalyst’s durable execution records serve a key, valuable role in supporting change management audits for internal agent workflows across your entire organization. These records capture full state transitions and detailed end-to-end execution timelines, letting auditors thoroughly verify that implemented changes align with pre-approved control frameworks and meet core audit requirements. They do not substitute for your team’s formal, documented internal change approval processes.
You own final validation of your organization’s compliance alignment during Catalyst migration rollback workflows. Use stored execution records to rigorously cross-reference replayable workflow states against pre-defined key compliance controls to confirm that rollback workflows meet critical applicable regulatory compliance requirements for your migration. Do not rely solely on these stored records or formal automated checks to fulfill all of your unique organizational compliance validation obligations.
You can leverage Catalyst’s execution logging to support your organization’s compliance audit workflows for agent deployments. It generates immutable, timestamped execution logs that capture every agent state transition, individual tool call, and corresponding input and output without modifying original raw data, paired with Dapr’s built-in access restrictions. These logs do not substitute your team’s internal data handling controls or mandatory cross-jurisdictional regulatory reporting tasks.
Certain compliance tasks fall outside Catalyst’s supported capabilities for regulated AI agent deployments. Catalyst provides execution logs and access controls, while your team retains full responsibility for data classification, access policy enforcement, and mandatory regulatory reporting for your deployed regulated AI agents. You must map platform features to your specific organizational control requirements to identify any unaddressed compliance gaps that are critical to your compliance posture.
