The Pentest Tax: The Hidden Cost Draining Your Security Team

Enterprise security teams are spending more time managing their penetration testing programmes than running them. Scheduling, scoping, chasing stakeholders, tracking findings in spreadsheets, and manually assembling audit evidence — the admin overhead is enormous, and most of it is invisible.

This report from OnSecurity, based on analysis of 14,000+ security engagements across 500+ organisations, quantifies the real cost of running a security testing programme without dedicated tooling — and shows what the shift to a platform-driven model looks like in practice.

What you will learn:

  • How ~20 days of admin overhead per engagement breaks down across scoping, scheduling and coordination
  • Why 76% of organisations testing multiple asset types face compounding complexity
  • The four characteristics of streamlined security operations that cut human effort by 30-50%
  • A practical checklist for programme structure, remediation tracking, compliance readiness and tooling
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Closing the Remediation Gap in Enterprise Security Programmes

Most security programmes produce findings. Far fewer have the infrastructure to make sure those findings actually get fixed. The result is the "report and forget" pattern — tests are conducted, reports are issued, and months later the same vulnerabilities reappear.

This case study from OnSecurity, based on analysis of 14,000+ security engagements across 500+ organisations, examines why remediation stalls, what it costs when findings sit unresolved, and what a closed-loop workflow looks like in practice.

What you will learn:

  • Why unresolved findings create compounding risk across multi-asset programmes
  • The operational shift from PDF-based reporting to platform-enabled remediation tracking
  • How leading teams achieve a 30% average improvement in MTTR and MTTF
  • What the five-step closed-loop remediation workflow looks like: Discover → Assign → Track → Retest → Close

Get the full case study to see how to operationalise remediation across your security programme.

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How Regulated Organisations Are Eliminating Compliance Overhead

Security teams operating under PCI DSS, ISO 27001, SOC 2 or Cyber Essentials Plus know the real challenge is not running penetration tests - it is proving they happened, documenting what was found, and showing remediation within a defined window. Most teams rebuild this evidence from scratch before every audit.

This case study from OnSecurity, based on analysis of 14,000+ security engagements across 500+ organisations, breaks down the compliance patterns that create the most overhead and shows what a continuously audit-ready programme looks like.

What you will learn:

  • Why evidence fragmentation is the top compliance time drain
  • Four failure modes that affect regulated organisations most
  • How platform-enabled testing programmes reduce manual effort by 30-50%
  • What practical, always-ready compliance looks like across fintech, healthtech and SaaS

Get the full case study to see a better model for compliance-ready security testing.

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The Complete Guide to AI-Powered Service Management

For enterprises managing complex after-sales operations — across online support, field engineers, and third-party service partners — fragmented tools and manual handoffs are no longer acceptable. This whitepaper introduces ShareService, a unified service management platform that connects every stage of the service lifecycle, from omni-channel intake and intelligent dispatch to on-site field execution, cost settlement, and CSAT analytics. Built on the ShareCRM PaaS infrastructure, ShareService embeds AI agents at each touchpoint: a 24/7 multilingual Online Support Agent that triages and creates work orders in real time, and a Field Service Agent that equips engineers with pre-visit briefings, on-site fault diagnosis, and parts recommendations — reducing return visits and driving consistent service quality at scale.

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Securing Autonomous AI Agents

As organizations integrate autonomous AI systems to process invoices, modify cloud infrastructure, and manage tasks, a new security challenge emerges. How do you grant software the ability to act autonomously while maintaining strict control over its capabilities? The solution lies in adapting identity architecture for non-human actors.

Inside this guide, you will discover:

  • The Three Types of Agent Identity: Understand the differences between service agents, delegated agents, and collaborative multi-agent systems.
  • Common Security Failures: Explore real-world scenarios, such as privilege escalation and un-traceable actions, caused by identity fragmentation.
  • Modern Authorization Models: Learn how to implement policy-based, context-aware decisions rather than relying on coarse Role-Based Access Control.
  • A Phased Implementation Roadmap: Follow a practical 12-month plan to inventory existing agents, improve credential hygiene, and establish dynamic authorization.

Download the guide to explore how to responsibly deploy AI agents without compromising your security posture.

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2026 State of Production Reliability and AI Adoption

Platform and IT engineers are constantly challenged to build reliable systems while keeping production running during critical failures. However, reactive incident management is consuming valuable engineering capacity and driving significant team burnout. In fact, the majority of engineering teams spend 40 percent or more of their time on incident management instead of innovation.

Read the full report to explore key findings, including:

  • The Cost of Alert Fatigue: Discover why nearly half of organizations experienced an outage linked to ignored or suppressed alerts in the past year.
  • Financial Exposure: Learn how infrastructure downtime costs 61 percent of organizations $50,000 or more per hour.
  • The AI Perception Gap: Understand why 74 percent of C-suite executives believe their organization actively uses AI for incident management while only 39 percent of practitioners agree.
  • Barriers to Adoption: Identify the top practical challenges to AI deployment, such as budget constraints, data quality issues, and security concerns.
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Success Story of ModelRocket and NeuBird.ai: Transforming Production Operations with Agentic AI SRE

As organizations scale their cloud infrastructure, engineers often spend countless hours diagnosing complex operational issues, which can delay development cycles and threaten SLAs. Model Rocket, an innovative technology solutions provider, faced these exact operational headwinds as their usage of AWS services expanded.

Download this customer story to learn how Hawkeye transformed Model Rocket’s operations, resulting in:

  • 92% MTTR Reduction: Drastically accelerated incident resolution by instantly identifying root causes.
  • 24/7 Expert Monitoring: Leveraged AI to provide continuous, automated root cause analysis across the entire AWS environment.
  • Enhanced Development Focus: Freed engineers from context-switching between operations and development, allowing them to focus on innovation.
  • Strengthened SLAs: Ensured consistent service reliability even during rapid development cycles.
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NeuBird AI SRE: Your 24/7 Incident Resolution Assistant

In modern IT environments, engineers are often overwhelmed by alert storms and fragmented data during critical incidents. NeuBird AI functions as a 24/7 SRE assistant, designed to augment your DevOps and engineering teams with real-time analysis, pattern detection, and context-aware recommendations.

Download this data sheet to learn how NeuBird can help your team:

  • Reduce Operational Noise: Collapse hundreds of raw alerts into a single, actionable incident with probable root causes identified.
  • Detect Root Causes Faster: Unify observability data, change events, and operational knowledge into one seamless system.
  • Automate Common Fixes: Safely execute remediation using runbook intelligence and strict execution controls.
  • Maintain Data Privacy: Analyze incidents using your private vector database without sending raw telemetry to external models.
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Agentic AI In Modern SRE Ops

Modern Site Reliability Engineering teams are not constrained by a lack of observability, but by the manual effort required after an alert fires. As production environments generate massive volumes of telemetry, the work required to interpret data across multiple platforms has dramatically increased, leading to higher levels of toil and delayed response times.

Download this eBook to explore how autonomous incident resolution is changing SRE operations, including how to:

  • Eliminate Manual Toil: Free your engineering teams from the hidden costs of reactive firefighting and repetitive triage.
  • Accelerate Incident Resolution: Move from alert to fix significantly faster with automated root cause analysis.
  • Build Trust In Automation: Implement secure, explainable, and governed AI workflows that align with your operational standards.
  • Integrate Seamlessly: Deploy autonomous agents across your existing hybrid and multi-cloud observability tools without ripping and replacing infrastructure.
View Now

2026 State of Production Reliability and AI Adoption

Platform and IT engineers are constantly challenged to build reliable systems while keeping production running during critical failures. However, reactive incident management is consuming valuable engineering capacity and driving significant team burnout. In fact, the majority of engineering teams spend 40 percent or more of their time on incident management instead of innovation.

Read the full report to explore key findings, including:

  • The Cost of Alert Fatigue: Discover why nearly half of organizations experienced an outage linked to ignored or suppressed alerts in the past year.
  • Financial Exposure: Learn how infrastructure downtime costs 61 percent of organizations $50,000 or more per hour.
  • The AI Perception Gap: Understand why 74 percent of C-suite executives believe their organization actively uses AI for incident management while only 39 percent of practitioners agree.
  • Barriers to Adoption: Identify the top practical challenges to AI deployment, such as budget constraints, data quality issues, and security concerns.
View Now

NeuBird AI SRE: Your 24/7 Incident Resolution Assistant

In modern IT environments, engineers are often overwhelmed by alert storms and fragmented data during critical incidents. NeuBird AI functions as a 24/7 SRE assistant, designed to augment your DevOps and engineering teams with real-time analysis, pattern detection, and context-aware recommendations.

Download this data sheet to learn how NeuBird can help your team:

  • Reduce Operational Noise: Collapse hundreds of raw alerts into a single, actionable incident with probable root causes identified.
  • Detect Root Causes Faster: Unify observability data, change events, and operational knowledge into one seamless system.
  • Automate Common Fixes: Safely execute remediation using runbook intelligence and strict execution controls.
  • Maintain Data Privacy: Analyze incidents using your private vector database without sending raw telemetry to external models.
View Now

Agentic AI In Modern SRE Ops

Modern Site Reliability Engineering teams are not constrained by a lack of observability, but by the manual effort required after an alert fires. As production environments generate massive volumes of telemetry, the work required to interpret data across multiple platforms has dramatically increased, leading to higher levels of toil and delayed response times.

Download this eBook to explore how autonomous incident resolution is changing SRE operations, including how to:

  • Eliminate Manual Toil: Free your engineering teams from the hidden costs of reactive firefighting and repetitive triage.
  • Accelerate Incident Resolution: Move from alert to fix significantly faster with automated root cause analysis.
  • Build Trust In Automation: Implement secure, explainable, and governed AI workflows that align with your operational standards.
  • Integrate Seamlessly: Deploy autonomous agents across your existing hybrid and multi-cloud observability tools without ripping and replacing infrastructure.
View Now

2026 State of Production Reliability and AI Adoption

Platform and IT engineers are constantly challenged to build reliable systems while keeping production running during critical failures. However, reactive incident management is consuming valuable engineering capacity and driving significant team burnout. In fact, the majority of engineering teams spend 40 percent or more of their time on incident management instead of innovation.

Read the full report to explore key findings, including:

  • The Cost of Alert Fatigue: Discover why nearly half of organizations experienced an outage linked to ignored or suppressed alerts in the past year.
  • Financial Exposure: Learn how infrastructure downtime costs 61 percent of organizations $50,000 or more per hour.
  • The AI Perception Gap: Understand why 74 percent of C-suite executives believe their organization actively uses AI for incident management while only 39 percent of practitioners agree.
  • Barriers to Adoption: Identify the top practical challenges to AI deployment, such as budget constraints, data quality issues, and security concerns.
View Now

Success Story of ModelRocket and NeuBird.ai: Transforming Production Operations with Agentic AI SRE

As organizations scale their cloud infrastructure, engineers often spend countless hours diagnosing complex operational issues, which can delay development cycles and threaten SLAs. Model Rocket, an innovative technology solutions provider, faced these exact operational headwinds as their usage of AWS services expanded.

Download this customer story to learn how Hawkeye transformed Model Rocket’s operations, resulting in:

  • 92% MTTR Reduction: Drastically accelerated incident resolution by instantly identifying root causes.
  • 24/7 Expert Monitoring: Leveraged AI to provide continuous, automated root cause analysis across the entire AWS environment.
  • Enhanced Development Focus: Freed engineers from context-switching between operations and development, allowing them to focus on innovation.
  • Strengthened SLAs: Ensured consistent service reliability even during rapid development cycles.
View Now

NeuBird AI SRE: Your 24/7 Incident Resolution Assistant

In modern IT environments, engineers are often overwhelmed by alert storms and fragmented data during critical incidents. NeuBird AI functions as a 24/7 SRE assistant, designed to augment your DevOps and engineering teams with real-time analysis, pattern detection, and context-aware recommendations.

Download this data sheet to learn how NeuBird can help your team:

  • Reduce Operational Noise: Collapse hundreds of raw alerts into a single, actionable incident with probable root causes identified.
  • Detect Root Causes Faster: Unify observability data, change events, and operational knowledge into one seamless system.
  • Automate Common Fixes: Safely execute remediation using runbook intelligence and strict execution controls.
  • Maintain Data Privacy: Analyze incidents using your private vector database without sending raw telemetry to external models.
View Now