SIEM Solutions
Centralised log collection, detection and compliance reporting.
Overview
We design, deploy and tune a SIEM that centralises logs, correlates events and raises accurate alerts, with retention and reporting that support audits.
- CollectionCollectors and agents forward logs from servers, endpoints, firewalls, identity, cloud and applications.
- IngestionEvents are parsed and normalised.
- CorrelationDetection rules and threat intelligence open cases in ticketing or SOAR workflows.
- StorageHot and archive tiers under role-based access.
Technical scope
- Platform selection and sizing
- Log source onboarding: servers, endpoints, firewalls, identity, cloud and applications
- Parsing, normalisation and data-quality checks
- Correlation rules, use cases and dashboards
- Alert tuning and false-positive reduction
- Retention, archival and role-based access
- Compliance reporting packs
Architecture and how it works
Collectors and agents forward logs to an ingestion tier that parses and normalises events. A correlation engine applies detection rules and threat intelligence, alerts open cases in a ticketing or SOAR workflow, and data is kept in hot and archive storage.
Delivery process
- 01
Plan
Define log sources, use cases and retention needs
- 02
Deploy
Install collectors and connect sources
- 03
Parse
Normalise fields and validate data quality
- 04
Detect
Build and test correlation rules and dashboards
- 05
Tune
Refine thresholds and hand over with runbooks
Tools and deliverables
Documentation covers the log-source inventory, parsing and normalisation rules, correlation use cases, retention tiers and access roles. Tuning records show alert volumes and false-positive reduction, and compliance packs summarise events as audit evidence.
Deliverables
- Log source inventory
- Use-case catalogue
- Dashboards and scheduled reports
- Retention and access policy
- Operations runbook
Common questions
How are logs ingested and normalised?
Collectors and agents forward logs from servers, endpoints, firewalls, identity, cloud and applications to an ingestion tier that parses and normalises events into a common format. Data-quality checks confirm that fields are extracted correctly, so correlation rules can compare events from different sources reliably.
How does correlation produce alerts?
A correlation engine applies detection rules and threat intelligence across sources, so a pattern that spans several systems can be recognised as one incident. Alerts open cases in a ticketing or SOAR workflow, which gives each one an owner, a status and a record of the investigation from first alert to closure.
How is alert noise reduced?
Alerts are tuned by adjusting thresholds, exclusions and rule logic against real data. This reduces false positives and keeps analysts focused on genuine events, and each change is recorded, so detection quality improves over time without silently removing coverage for the attacker behaviour that matters most.
How are retention and access handled?
Recent data stays in hot storage for fast search and older data moves to archive, which balances investigation speed against cost. Role-based access controls who can view or export logs, and retention is set to match audit and regulatory requirements, so the evidence you need is available when it is asked for.