Organizations are under constant pressure to ensure that security and compliance not only meet regulatory standards but are also agile enough to keep up with emerging threats. With traditional manual methodologies falling short in the face of evolving risks, more companies are turning to automation powered by artificial intelligence.
By leveraging AI-driven solutions, particularly when integrated with popular platforms like ServiceNow and Splunk, businesses can shift from periodic, cumbersome risk assessments to a continuous, automated framework that delivers real-time insights and defensible risk metrics.
One such revolutionary solution is provided by TrustCloud AI. As detailed in recent discussions on TrustCloud’s capabilities, the integration of their AI engine with ServiceNow and Splunk transforms how organizations manage their application and security risk. This article will explore the specifics of these integrations and demonstrate how TrustCloud AI delivers unparalleled control over risk assessments, substantially reducing residual risk and providing quantifiable, actionable data.
A quick look in the rear-view mirror
Last week, our CEO, Sravish Sridhar, announced that TrustCloud secured $15 million in new funding from ServiceNow Ventures, Cisco Investments, and others. In his words, the raise “validates the urgent need to modernize GRC for enterprise CISOs and unify CISOs and chief risk officers around a shared view of risk.” The new capital accelerates our mission to automate governance, risk, and compliance for every security team, no matter which system of record they live in.
Because we’ve built a Hybrid Data Fabric that is a data lake of security and GRC data from cloud and on-premises sources, TrustCloud aggregates and contextualizes telemetry data from both Splunk and ServiceNow. Specifically, security event data and Logs from Splunk, and CMDB data and process information from ITSM in ServiceNow. TrustCloud leverages this data to enable:
- Continuous Control Monitoring that puts control testing and evidence collection on autopilot
- Accurate, defensible application and infrastructure risk assessments that use objective data, not surveys
- Unified insight into the protection of critical data across your internal applications and infrastructure, as well as your third-party sources.
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Learn MoreTransforming risk assessments with automation
Traditional risk assessment approaches are hardly sufficient in the modern regulatory environment. Gone are the days when quarterly surveys, manual screenshots, and disparate audit sheets could provide a comprehensive view of an organization’s security posture. Today’s boards demand clear, defensible numbers outlining risk exposure and how digital controls are performing. In many cases, manual processes not only hinder productivity but also contribute to gaps in risk management, where every change and every alert must be tracked, analyzed, and correlated to evolving threats.
TrustCloud AI bridges this gap by offering two key transformational integrations with ServiceNow and Splunk:
- Continuous Control Monitoring inside your ServiceNow environment
- Automated cyber risk assessments and quantification using data in Splunk Enterprise Security
Let’s take a deeper look at each integration and examine how it enables organizations to not only streamline their risk assessment processes but also gain real-time visibility into residual risk, all while providing automated evidence that aligns with industry standards.
Two high-impact use cases you can activate today
1. Continuous Control Monitoring inside your ServiceNow environment
TrustCloud can pull information about your crown jewel applications and assets from CMDB, validate that the right protective controls are operating effectively, and feed into workflows in ITSM to streamline remediation. Every change auto-maps to the proper control and policy.
Why it matters
Before TrustCloud
- Quarterly surveys
- Manual screenshots
- Disparate risk, asset, and audit sheets
After TrustCloud
- Continuous, provable risk assessments
- API-pulled evidence attached to each control
- Single dashboard showing residual risk in real time
Real-world win
A Fortune 500 firm turned quarterly risk assessments into continuous control assurance of their digital crown jewel applications in under 6 months, reducing their residual application security risk by over 70%.
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2. Automated cyber risk assessments and quantification using data in Splunk Enterprise Security
Splunk Enterprise Security is a gold mine of logs, alerts, and asset context. TrustCloud converts that stream into programmatically quantifiable residual-risk scores aligned to many risk frameworks such as NIST and ISO. TrustCloud pulls high-fidelity alerts, context, and asset details from Splunk ES. Assurance AI filters noise, adds business context, scores residual risk in dollars, and pushes the number straight into your ERM dashboard.
Why it matters
Before TrustCloud
- Thousands of noisy alerts
- “Red-Amber-Green” reports that no one trusts
- Log exports and spreadsheets at audit time
After TrustCloud
- Prioritized gaps and findings, thanks to AI triage
- Risk tied to business impact that every exec understands
- Auto-generated evidence mapped to SOC 2, ISO 27001, CMMC and other standards
Real-world win
A global retailer turned Splunk alerts into automated control tests and fed residual-risk scores straight to its ERM dashboard, giving executives a single view of cyber exposure in dollars instead of red, amber, and green.
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Why now?
The pressure on organizations to modernize their security and compliance practices has never been greater. Boards of directors no longer accept vague reports; they want clear, defensible numbers that quantify risk and demonstrate control effectiveness. At the same time, regulators are shifting expectations away from annual or point-in-time audits, demanding continuous assurance that safeguards are active and reliable every day. Security teams, already overwhelmed by an explosion of tools and fragmented workflows, struggle to provide this level of visibility without adding more manual overhead.
This is where AI becomes indispensable. By layering an AI engine on top of existing platforms like ServiceNow and Splunk, organizations can automate complex governance, risk, and security workflows with precision. AI not only streamlines evidence collection and monitoring but also delivers quantitative proof that controls are functioning as intended. The result is a shift from reactive compliance to proactive resilience, where teams can meet board expectations, satisfy regulators, and reduce operational strain, all while making better data-driven decisions.
Boards are asking for defensible numbers. Regulators are demanding continuous assurance, not point-in-time audits. And security teams are drowning in tool sprawl. Using an AI engine on top of your ServiceNow and Splunk environments enables you to accurately automate numerous security and GR workflows and quantitatively prove that your controls are operating effectively.
Continuous control monitoring in ServiceNow
Many organizations rely on ServiceNow as a comprehensive IT service management (ITSM) solution, often using its Configuration Management Database (CMDB) to manage critical data assets. TrustCloud AI further enhances this environment by continuously pulling information about a company’s “crown jewel” applications and assets directly from the CMDB. The AI ensures that the right protective controls are in place and operating effectively, a process once entrenched in quarterly surveys and manual effort.
How it works
TrustCloud AI integrates with ServiceNow to provide continuous, provable risk assessments by:
- Data Extraction
The AI pulls data from the CMDB regarding essential applications and assets. This information includes configuration details, inventory lists, and associated controls. - Control Validation
Once the information is ingested, TrustCloud validates whether the appropriate protective controls are in place and operating as expected. Every change in the environment is automatically mapped to its corresponding control and policy. - Workflow Integration
The AI integrates verified control status into ITSM workflows. This means that remediation steps can be initiated automatically, ensuring that any necessary adjustments are immediately addressed in a structured and traceable manner.
This approach replaces outdated methods that relied on quarterly surveys, manual screenshots, and disparate risk management documentation with an automated solution that offers:
- Continuous, provable risk assessments
- API-pulled evidence attached to each evaluated control
- A single, unified dashboard that displays residual risk in real time
The impact: Before and after TrustCloud
The transformation provided by TrustCloud AI can be best described by comparing the state of risk assessments before and after its implementation:
Before TrustCloud:
- Organizations conducted quarterly surveys.
- Risk assessments relied on manual screenshots.
- Information and evidence were scattered across multiple risk, asset, and audit sheets.
After TrustCloud:
- Risk assessments become continuous and fully automated.
- Every control is supported by API-pulled, verifiable evidence.
- A single dashboard offers a real-time snapshot of residual risk, enabling proactive adjustments.
A Fortune 500 firm, for example, leveraged TrustCloud AI to transition from quarterly risk assessments to continuous monitoring of their digital crown jewel applications. In less than six months, they reduced their residual application security risk by over 70%. This dramatic improvement underscores the power of automation over traditional, fragmented processes.
Automated cyber risk assessments with Splunk enterprise security
While ServiceNow helps organizations manage their internal workflows and asset data, Splunk Enterprise Security provides an entirely different treasure trove: a wealth of logs, alerts, and contextual asset information. TrustCloud AI capitalizes on this data by converting it into programmatically quantifiable residual-risk scores that are aligned with major risk frameworks like NIST and ISO.
How TrustCloud leverages Splunk data
The working mechanism behind this integration involves multiple sophisticated processes designed to filter, contextualize, and quantify risk:
- High-Fidelity Data Extraction
TrustCloud AI pulls a rich stream of logs, alerts, and asset details from Splunk Enterprise Security. This ensures that no critical event is overlooked. - Noise Filtering and Contextualization
One of the challenges with Splunk is the sheer volume of data. TrustCloud employs Assurance AI that filters out noise, adds business context, and effectively focuses on the alerts that matter. - Quantitative Risk Scoring
The filtered data is then used to score residual risk in tangible dollar amounts, making it easier for executives to understand risk impact in terms that translate directly into business value. - Compliance Integration
Automatic mapping of generated evidence to compliance frameworks such as SOC 2, ISO 27001, CMMC, and more ensures that the risk assessments can stand up to rigorous audits.
With this approach, Splunk data, which was previously represented by thousands of noisy alerts and “Red-Amber-Green” status reports that were often ignored, transforms into prioritized gaps and findings. These are prioritized not merely as compliance checkboxes, but as quantifiable risks tied directly to business impact.
The impact of automated risk assessments with Splunk
Similar to the ServiceNow integration, the transformation using Splunk data is stark:
Before TrustCloud:
- Security teams were overwhelmed with thousands of noisy alerts.
- Risk reports were simplistic “Red-Amber-Green” models that lacked trust among executives and stakeholders.
- Audits required manual log exports and spreadsheets that were labor-intensive and error-prone.
After TrustCloud:
- Alerts are triaged through an AI-driven process, ensuring that only the highest priority risks are escalated.
- Risks are tied to business impact in a way that every executive can understand, often translated into financial metrics.
- Evidence is auto-generated and mapped to multiple recognized standards, reducing the overhead during audits.
This automation enables organizations to not only prioritize critical security gaps but also provides a compelling business case for remediation through quantifiable risk quantification. Decision-makers can now see the financial implications of each risk, ensuring that budget allocation and remediation efforts are aligned with business priorities.
Unlocking real-time risk: How automation changes the game
When compliance and security workflows rely on static reports or quarterly reviews, risk becomes out-of-date the moment it’s produced. By integrating AI-powered control and risk automation, built on telemetry from ServiceNow and Splunk, organizations gain a real-time pulse on their applications and infrastructure. That means continuous visibility into how controls are running, immediate risk scoring tied to actual business impact, and assurance without user delays or manual effort.
Environments already stretched thin by tool sprawl and manual processes, automation doesn’t just save time; it brings clarity and confidence. Teams move from reactionary fire drills to proactive mitigation: vulnerabilities surface faster, remediation is triggered automatically, and leadership sees risk translated into dollars, not vague traffic lights. That shift transforms security from a compliance burden into a strategic advantage.
Here are five ways automation reshapes app and security risk assessments
- Continuous Control Monitoring
Control checks auto-map from ServiceNow CMDB and Splunk logs into monitoring workflows, so every change is assessed as it happens, not weeks later in disconnected audits. - Objective, Data-Driven Risk Scoring
AI aggregates telemetry to compute residual risk in financial terms. Splunk alerts fuel quantified insights, replacing guesswork with board-ready metrics. - Zero Manual Evidence Collection
Forget spreadsheets or screenshots: evidence is pulled via APIs and tagged to specific controls automatically, simplifying audit prep and eliminating human bottlenecks. - Contextual Prioritization
Alerts and control gaps are ranked not just by severity but by business relevance, so remediation focuses on what truly matters, not just what’s easy to spot. - Hybrid Visibility Under One Roof
Data from both ServiceNow and Splunk lands into a unified dashboard, offering a consolidated, defensible view of infrastructure, application, and third-party risk.
Read the “Automating evidence collection for regulatory compliance: Tools & best practices” article to learn more!
Charting the next chapter with AI for GRC transformation
The playbook for risk management is being rewritten in code, APIs, and real-time telemetry. When every control is validated continuously and quantified in business terms, security leaders stop chasing compliance and start shaping strategy. The future belongs to teams that can:
Automate at the data layer, not the spreadsheet layer.
AI and API-based workflows collapse months of manual effort into minutes.
Prove accuracy on demand.
Continuous Control Monitoring provides the assurance that auditors, boards, and customers now expect.
Bridge first- and third-party siloes.
Streaming data from ServiceNow, Splunk, and your cloud stack into one fabric unlocks a single, defensible view of risk.assessments, replacing security questionnaires (The security questionnaire is dead!)
This isn’t a distant vision; it’s live today for ServiceNow and Splunk customers who plug into TrustCloud. If you’re ready to move from point-in-time checklists to code-speed confidence, let’s talk.
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Whether you sit in ServiceNow, Splunk, or both, our specialists can show you how to end manual evidence collection and translate every alert into a clear financial risk metric.
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Summing it up
organizations leveraging platforms like ServiceNow and Splunk are increasingly turning to automation to streamline their application and security risk assessments. By integrating TrustCloud’s AI-powered solutions, businesses can transform raw telemetry data into actionable insights, enabling continuous risk monitoring and proactive compliance management.
This shift towards automated risk assessments not only enhances operational efficiency but also strengthens security postures by providing real-time visibility into potential vulnerabilities. As regulatory requirements evolve and cyber threats become more sophisticated, adopting such advanced tools is essential for maintaining a robust and agile risk management framework.
Embracing automation in risk assessments is no longer a luxury but a necessity for organizations aiming to stay ahead in the competitive and compliance-driven market.
Frequently asked questions
How does TrustCloud’s integration with ServiceNow and Splunk transform traditional risk assessments?
Traditionally, risk assessments have often been manual, periodic, and highly reactive. TrustCloud disrupts that norm by directly tapping into ServiceNow’s change management and asset data, as well as Splunk’s security events and log telemetry. This integration enables continuous, real-time risk visibility: organizations can see control effectiveness and risk posture evolve as infrastructure and threats change, not just during scheduled audits. Instead of chasing scattered reports and pulling static data, security and compliance teams receive an always up-to-date snapshot of risk, enabling them to respond faster, more accurately, and with far less manual work.
In what way does automation improve the efficiency and accuracy of evidence collection for audits?
Audit prep often centers on gathering documentation, screenshots, logs, and and policy versions from multiple sources, a process prone to delays and human error. TrustCloud’s automation helps by pulling data directly from ServiceNow and Splunk, then matching it to corresponding compliance controls in real time. This means evidence is accurate, consistently formatted, and instantly available. With this automated pipeline, organizations eliminate the guesswork, reduce audit fatigue, and free up their teams from tedious gathering tasks, allowing them to focus on strategic improvements rather than paperwork.
How does real-time risk scoring through TrustCloud improve decision-making for security and leadership teams?
Static, periodic risk assessments always lag behind today’s fast-moving threat landscape. TrustCloud addresses that by using AI to interpret telemetry from ServiceNow and Splunk and convert it into live risk scores, key insights tied to business impact. This allows security leaders and executives to understand not just that a risk exists, but how critical it is, and whether it demands immediate action or monitoring. Having these scores updated in real time gives teams the ability to prioritize remediation clearly and credibly, making compliance and risk management an active, strategic conversation instead of an annual checkbox.
