Threat Detection Engineering Services
Turn security telemetry into earlier, higher-confidence threat detection.
Solutioned LLC helps security leaders design, assess, and modernize threat detection programs that connect adversary behavior, telemetry, analytics, and response workflows.
More alerts do not automatically mean better protection.
Security teams are often surrounded by tools but still uncertain about their actual detection coverage. A SIEM may be ingesting millions of events. Endpoint tools may be generating alerts. Cloud platforms may be producing audit logs.
Yet leadership may still struggle to answer basic questions: What threats can we detect today? Which attacks would we miss? Which alerts are worth investigating? Which telemetry sources are underused?
Threat detection engineering closes that gap. It turns security data into a deliberate detection capability, aligned to real adversary behaviors, business risk, and the way your SOC or IT team actually investigates incidents.
For SMB and mid-market organizations, this is especially important. A mature threat detection program does not require enterprise-scale headcount on day one. It requires the right detection logic, the right telemetry, the right prioritization, and a practical roadmap that improves security outcomes without overwhelming the team.
Sources: IBM Cost of a Data Breach Report 2025; Verizon 2025 Data Breach Investigations Report - SMB Snapshot
Know what you can detect, what you cannot detect, and what to improve first.
Threat detection engineering gives security leaders a defensible view of their detection program. Instead of relying on tool dashboards or vendor assumptions, your team gets a practical map of detection coverage, telemetry gaps, alert quality, investigation workflows, and priority improvements.
The outcome is not just more rules. The outcome is a more disciplined detection capability: fewer blind spots, better signal, clearer prioritization, and stronger confidence when reporting cyber risk to executives, auditors, insurers, and the board.
Choose the detection engineering workstream that matches your current maturity.
Every organization starts from a different place. Some need a current-state assessment to understand detection gaps, while others need hands-on help designing better detections, improving SIEM logic, reducing alert noise, or strengthening response workflows.
These workstreams are designed to meet the client where they are and create a practical path toward stronger detection capability.
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We assess what your current tools, logs, and workflows can realistically detect today. The assessment reviews telemetry sources, alert logic, use cases, investigation paths, and coverage against relevant adversary behaviors. The result is a clear picture of current detection strengths, blind spots, and the highest-value improvements to pursue first.
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We translate threat behaviors into a prioritized detection roadmap aligned to MITRE ATT&CK tactics and techniques. This gives security leaders a defensible way to explain which threats are covered, which are partially covered, and which require additional telemetry, engineering, or process maturity. The roadmap is designed for practical execution, not theoretical completeness.
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Many modern attacks do not rely on obvious malware signatures. We help design behavioral detections that identify suspicious patterns such as credential misuse, command-and-control behavior, abnormal access, lateral movement, data staging, and unusual network activity. These detections can be rules-based, analytics-driven, or supported by machine learning where appropriate.
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We help clients improve the value of SIEM and security data lake investments by designing better detection use cases, correlation logic, alert criteria, dashboards, and investigation views. The goal is to reduce noise, improve actionability, and ensure that high-cost telemetry produces measurable security outcomes.
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We review existing alerts to determine which detections are actionable, duplicative, too noisy, poorly tuned, or disconnected from response workflows. This helps security teams reduce wasted investigation time and focus analyst attention on signals that are more likely to represent meaningful risk.
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A detection is only valuable if the team can investigate it. We help define the context, enrichment, evidence, and response steps needed for analysts or IT responders to act on alerts. This includes investigation playbooks, evidence requirements, escalation criteria, and reporting expectations.
Start when your security tools are producing activity but not enough confidence.
Threat detection engineering is often most valuable when leadership senses that the organization has security data but lacks a clear view of what that data proves. These are common situations where a focused detection review or roadmap can turn uncertainty into a prioritized action plan.
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This is common in growing organizations. Logs are being collected, but detection coverage is unclear. A detection engineering review helps determine whether your SIEM is supporting real security outcomes or simply storing events.
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Too many low-quality alerts can weaken response. We help identify noisy detections, overlapping rules, missing context, and opportunities to improve triage quality so teams spend less time chasing low-value signals.
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Detection coverage is increasingly part of cyber maturity conversations. We help translate technical detection capabilities into business-facing evidence that leadership can understand and act on.
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These threats require more than perimeter controls. We help identify which telemetry and detections are needed to recognize suspicious authentication, internal movement, command-and-control activity, data staging, and other behaviors that may precede business disruption.
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Growing companies often accumulate cloud services, SaaS platforms, endpoints, identity systems, and network changes faster than detection programs mature. We help create a practical roadmap that prioritizes high-impact improvements without assuming enterprise-level headcount.
Walk away with practical artifacts your team can act on.
The goal is not to produce a theoretical report that sits unused. A Threat Detection Engineering engagement should leave your team with concrete findings, prioritized recommendations, and artifacts that support execution, leadership reporting, and follow-on implementation.
A typical engagement may include:
Current-state detection coverage assessment
Telemetry and log-source inventory
MITRE ATT&CK-aligned detection gap analysis
Alert quality and triage review
Detection use-case backlog
SIEM or data lake detection design recommendations
Behavioral analytics and anomaly detection opportunities
Investigation workflow recommendations
Executive summary and technical findings report
Prioritized implementation roadmap
Use production security analytics experience to make models operational.
Solutioned LLC’s threat detection engineering practice is founder-led and grounded in hands-on experience designing detection ecosystems for global enterprise environments.
The founder’s background includes building fault-tolerant threat detection systems that combine deterministic expert systems with machine learning, modeling high-volume security events, developing malware and command-and-control detections, supporting SOC response workflows, and designing security architectures aligned to enterprise risk reduction.
That matters because threat detection engineering is not just a tooling exercise. It requires understanding adversary behavior, data pipelines, analytics, SOC operations, architecture tradeoffs, and how to communicate risk to business leaders.
Move from detection uncertainty to an actionable improvement plan.
A Threat Detection Engineering engagement should create forward motion, not just findings.
Solutioned LLC uses a focused discovery-to-roadmap process to understand your environment, map available telemetry to relevant threat behaviors, prioritize the highest-value detection improvements, and produce practical artifacts your security, IT, and operations teams can use to strengthen detection capability over time.
The process is designed to meet clients where they are: whether the immediate need is executive visibility, SIEM optimization, alert-quality improvement, detection roadmap development, or targeted implementation support.
We begin with a focused discovery session to understand business drivers, current tools, known concerns, and your operating model.
Step 1: Discover
We map available telemetry, existing detections, alert flows, investigation workflows, and relevant threat behaviors.
Step 2: Map
We identify the highest-value improvements based on risk, feasibility, tool availability, operational effort, and business impact.
Step 3: Prioritize
We develop detection logic, architecture recommendations, dashboards, use cases, workflows, or roadmap artifacts depending on the engagement scope.
Step 4: Design
We help the client move from findings to action through implementation support, advisory sessions, documentation, or follow-on architecture work.
Step 5: Enable
Answer the common questions before the engagement begins.
Security leaders usually need to understand scope, timing, access requirements, and how this work fits alongside existing tools or providers. These questions help clarify what a Threat Detection Engineering engagement is designed to do, and what it is not designed to replace.
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No. The engagement is platform-aware but not limited to one product. We can work with SIEM, EDR, identity, cloud, firewall, proxy, email, and data platform telemetry. The goal is to improve detection outcomes using the tools and data sources that make sense for your environment.
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It can be either. Some clients start with a detection coverage assessment and roadmap. Others need help designing detections, improving SIEM use cases, tuning alerts, or supporting implementation with internal teams.
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A focused assessment can often be completed in a few weeks. More detailed detection architecture or implementation support may run longer depending on the number of systems, data sources, stakeholders, and priority use cases.
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No. Threat detection engineering can complement MDR, MSSP, and SOC providers by improving the quality of the detections, telemetry, and workflows those teams rely on. It helps clients become better owners of their detection strategy instead of depending entirely on vendor defaults.
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Useful inputs include security tool inventories, SIEM use cases, alert examples, log-source lists, incident examples, cloud and identity platform details, network telemetry, and current security operations workflows. The engagement can be scoped to match the client’s comfort level and data-access requirements.
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Success can be measured through clearer detection coverage, reduced alert noise, improved investigation context, prioritized detection backlog, better executive reporting, and stronger confidence that key threat behaviors are either detectable today or represented in the roadmap.
Ready to understand your detection blind spots?
Solutioned LLC helps security leaders evaluate, modernize, and strengthen threat detection capabilities without forcing a one-size-fits-all platform or managed service model.