From Two Analysts to a 24/7 Security Force
Learn how a global SaaS company cut 561+ hours of grunt work and achieved 70% faster detection — all without additional headcount.
Executive Summary
A global mid-market SaaS organization in the security and privacy industry, with a global footprint and $14M+ annual revenue, struggled with constant alert floods, manual processes, and no 24×7 threat coverage. With just two analysts managing 2,000+ assets, the team faced 561+ hours of repetitive grunt work each month, resulting in slow detection and high operational fatigue.
Secure.com was deployed to transform their security operations without increasing headcount. Leveraging Asset Discovery, Risk Engine, Workflow Automation, Alex - Transparent, Collaborative and context Aware Experience, Digital Security Teammates, GRC Automation, and the Unified Knowledge Graph, the customer reduced manual workloads, cut triage time by 75%, and achieved 70% faster detection (MTTD) with nearly 50% faster remediation (MTTR).
Company Profile
Firmographics
Technographics
AWS-centric cloud stack, SaaS productivity tools, siloed security platforms
2,000+ (servers, endpoints, SaaS, cloud)
Multiple disconnected point solutions for vulnerability management, compliance, and asset tracking
240+ alerts/day (~7,200 per month) before Secure.com
The Challenge
Despite having multiple point tools in place, the company's security operations were heavily manual
- 1,000+ hours/month spent on repetitive tasks such as asset inventorying, classification, and compliance checks.
- Delayed Mean Time to Detect (MTTD) — up to 3 months in some cases — due to fragmented visibility across systems.
- Disconnected workflows leading to bottlenecks in incident response and compliance processes.
- No unified asset register, making it difficult to correlate vulnerabilities, ownership, and business impact.
The security leadership knew they needed a platform that could deliver real-time visibility, context-driven prioritization, and automation at scale — without adding headcount.
The Secure.com Implementation Journey
During evaluation, the customer prioritized three things: time‑to‑value, context‑aware prioritization, and operational automation without losing control. Secure.com's agentless onboarding and role-aware setup produced immediate momentum; connectors began pulling telemetry within minutes, and early exposures were actionable on day one.
A hands‑on proof‑of‑value sealed the decision. In under 30 days, the team saw a >60% reduction in low‑value workload, ~75% faster triage, and ~70% faster detection (MTTD), all without adding headcount. Slack/Jira integrations kept people in their flow, Digital Security Teammates provided dependable after‑hours coverage with human approval for consequential actions, and No‑Code Workflow Automation generated an immutable audit trail that simplified compliance.
Alternatives fell short in combination: point solutions lacked a unified graph; SOAR demanded brittle scripting; GRC suites required months of configuration before value; and "rip‑and‑replace" propositions threatened disruption.
How Secure.com Solved the Challenge
Digital Security Teammate:
Onboarding began with a quick activation wizard where the team set up their Digital Security Teammate, personalizing its name and identity. From there, the wizard walked them through connecting their core systems — cloud accounts, identity providers, ticketing tools, and collaboration channels — using over 200+ pre-built integrations.
As soon as the connections were live, the Teammate automatically began learning their environment, mapping assets, ingesting policies, and identifying initial risks. Clear "next best actions" appeared on screen — from fixing misconfigurations to validating vulnerabilities — so analysts could see value and take action within minutes, not weeks.
Digital Security Teammates handled first‑pass triage, enrichment, investigations, compliance evidence, and reporting with human approval for sensitive tasks. They posted clear alerts and daily summaries via Slack/email using Knowledge Graph context. The queue settled, after‑hours coverage improved without new hires, and triage time fell by ~75%.
Asset Discovery:
A spreadsheet asset register took ~176 hours a month and still missed items. Agentless discovery found machines, identities, and cloud workloads and automatically classified them through the 200+ connectors. Everything rolled into a single, living model (the Unified Knowledge Graph), so investigators could see what exists, who owns it, and how it's connected. Manual asset work dropped by ~62%, and investigations got faster with fewer blind spots.
Contextual Risk Prioritization:
Scanners flagged many "critical" issues that did not reflect business impact, costing ~88 hours/month of review. The Risk Engine combined asset context, exploit likelihood, exposure, and threat intel to create one ranked fix‑first list. Manual triage largely went away and detection time improved by ~70%.
Holistic Security Management View:
Leaders wanted one place to see posture and progress. The Unified Command Board brought together compliance (ISO 27001, GDPR, CIS, PCI‑DSS), CVE heat‑maps, asset‑to‑vulnerability views, and a topology map, plus a live Security Score. Decisions were faster because everyone worked from the same picture.
AI‑Enabled Case Management:
The backlog was noisy and inconsistent. Case Management enriched events, removed duplicates, and applied the right playbook, with analyst approval before anything changed in production. The queue steadied and triage time dropped by ~75% as incidents moved through a clear path to resolution.
Alex - Transparent, Collaborative and Context Aware Interface:
Analysts no longer had to jump between dashboards or write complex queries. Alex answered plain‑language questions using evidence from the Knowledge Graph and could trigger one‑click actions in Slack/Jira. This reduced interruptions and, together with automation, contributed to ~50% faster MTTR.
Attack‑Surface Map & External Scan:
External risks and shadow IT became visible early. A real‑time map showed dependencies, misconfigurations, and likely lateral paths; external, agentless scans surfaced unknown assets and routed them to the right owners. The team fixed issues steadily instead of reacting late.
No‑Code Workflow Automation:
Scripts that often broke were replaced with reliable, drag‑and‑drop workflows. Remediation, change management, and compliance steps ran the same way every time and wrote an immutable, time‑stamped audit trail. Fixes shipped with less effort and supported the near‑50% MTTR reduction.
Unified Knowledge Graph:
The graph acted as the organization's memory. It normalized telemetry, resolved duplicates, and modeled relationships so there was a single, current view of what exists, who owns it, and how it connects, with history when things changed. It powered risk prioritization, Alex's answers, routing in Case Management/Workflow, and the attack‑surface view.
Security & Architecture + AI Transparency:
A resilient, multi‑tenant architecture with end‑to‑end encryption, an immutable audit ledger, and transparency traces for each AI recommendation made the system easy to trust. Leaders and auditors could follow the logic behind actions. This made adoption simpler and safer to scale.
Measurable Outcomes
Before & After Snapshot
See how Secure.com can help your team achieve enterprise-grade security without scaling headcount
Disclaimer:
Client identity and sensitive details have been anonymized for confidentiality and security reasons.