— Types of problems we solve
Real cases, told with honesty.
At Athrun Data Intelligencewe respect each client's confidentiality agreements: we don't publish names or figures without explicit authorization. What we can share is exactly the types of problems we solve and how we work. If you need references to evaluate working with us, ask — we provide them privately under NDA.
Legacy data migration and unification
ProblemA company with legacy systems, scattered spreadsheets, and reports that disagree across departments.
ApproachWe audit sources, design a single semantic model, build ingestion pipelines and governance dashboards.
Typical outcomeOne single source of truth for finance, operations and sales — with metrics that finally agree.
Cloud modernization and cost reduction
ProblemExpensive on-prem infrastructure, runaway cloud bills, unpredictable downtime.
ApproachWorkload mapping, phased migration plan across AWS/Azure/GCP, continuous FinOps and real observability.
Typical outcomeTypical 30-50% reduction in cloud spend + measurable uptime under agreed SLAs.
AI and agent adoption in business workflows
ProblemTeams overwhelmed by repetitive tasks or wanting to "use AI" without a clear use case.
ApproachROI-prioritized process selection, agent design with guardrails and evaluations, integration with existing systems.
Typical outcome24/7 agents covering specific tasks and measuring their own impact. See CyberFort Lab as a production example.
Continuous cybersecurity and regulatory compliance
ProblemExpensive reactive audits, blind spots between them, difficulty proving ISO/PCI/NIST/GDPR compliance.
ApproachDeploy CyberFort Lab for continuous AI-driven auditing, executive reports digitally signed with eIDAS legal validity.
Typical outcomeContinuous compliance instead of snapshots. Flat cost regardless of coverage scope.
Actionable executive dashboards
ProblemReports that arrive late, metrics no one uses, decisions based on intuition instead of data.
ApproachStakeholder interviews, actionable KPI definition, build in Power BI / Tableau / Looker with real drilldowns.
Typical outcomeCommittee meetings with live data on screen. Decisions made in minutes, not weeks.
Custom software that actually ships to production
ProblemProjects that drag on, MVPs that never reach real users, growing technical debt.
ApproachDedicated technical squad, biweekly sprints with demos, product metrics from day one, observable infrastructure.
Typical outcomeSoftware in operation, real users, known metrics, and a team that understands what is happening.
Your problem isn't in the list?
These are patterns we see repeat. But every company is different. Tell us what is happening and within 24 business hours we will respond with an honest first technical read — no commitment.
Tell us your case