IT Due Diligence

Independent Technical Assessment – Facts Before Decisions

IT Due Diligence

Independent Assessment – Facts Before Decisions

IT Due Diligence creates transparency where complexity and uncertainty dominate. Whether triggered by M&A transactions, pre-investment evaluations, architecture decisions, cloud migration planning, or vendor consolidation – independent, technology-agnostic assessment delivers the technical facts that enable confident decision-making.

Credible assessments require independence. Fully independent of platform vendors and licensors – purely results-driven. Findings are driven exclusively by what the code, architecture, and organization reveal. This objectivity makes the results defensible in front of boards, investors, and regulators who distrust technical sales pitches.

Software Intelligence

AI-powered analysis makes complex codebases transparent in days. Automated tooling combined with senior engineering expertise delivers objective, quantifiable results at scale.

Codebase analysis and dependency mapping: Automated scanning of source code, libraries, frameworks, and system dependencies produces architecture maps, component diagrams, dependency graphs, and coupling hotspot analysis. The actual architecture – often significantly different from what is documented – becomes visible and measurable.

Automated documentation generation: AI-generated architecture documentation, component descriptions, interface specifications, and data flow diagrams – derived directly from actual code. Particularly valuable for legacy systems where documentation was never created or has long since fallen behind.

Test generation and coverage analysis: Automated creation of unit, integration, and regression test suites for systems with poor or no coverage. Existing coverage is measured, critical untested paths are identified, and generated tests create the safety net required for safe refactoring and migration.

Reverse engineering and business logic extraction: Undocumented business rules extracted from legacy code into structured, human-readable formats – decision trees, calculation rules, process flows. These outputs serve as foundation for modernization specifications, compliance documentation, knowledge transfer, and AI training data preparation.

Health Checks

Focused assessments – typically 1–4 weeks – that create actionable transparency in specific areas of an IT landscape. Seven modular assessment domains, deployable individually or in combination.

Architecture and code quality: Structural analysis of code quality, maintainability, and technical debt. Risk quantification backed by structural metrics, in terms executives and investors can act on. Especially critical in legacy codebases where institutional knowledge is retiring.

Security and vulnerability analysis: Automated and manual security assessment covering dependency vulnerabilities, configuration weaknesses, authentication gaps, and data exposure risks. Findings are prioritized and documented with remediation guidance.

Performance and scalability evaluation: Load testing, bottleneck identification, capacity limits, and growth-constraint analysis. The factors that will limit scalability are identified before they become production incidents.

Cloud readiness: Migration readiness evaluation including data residency analysis (GDPR, Schrems II), deployment pattern recommendations for regulated environments, and effort estimation. Technical feasibility and regulatory constraints assessed together as one integrated evaluation.

Host/non-host integration analysis: Latency analysis, data consistency assessment, and protocol mismatch identification across mainframe–modern platform boundaries. Integration quality between host core systems and modern frontends evaluated end to end.

STP and process automation assessment: Straight-through processing rates measured and automation opportunities identified. Benchmarking against industry standards: STP cycle times under 5 minutes vs. the 72-hour industry average, with up to 70% operational cost reduction potential.

DevOps and delivery maturity: CI/CD pipeline assessment, release cycle bottleneck analysis, deployment frequency, and change-failure rate measurement. Paths from 18–24 month product launch cycles to continuous delivery mapped with concrete steps.

AI Readiness

Before investing in AI, organizations need clarity on where it will deliver genuine business value – and where it will not. AI readiness assessment evaluates preparedness across data, technology, and organizational dimensions, grounding strategy in reality.

Data maturity and AI-readiness evaluation: Data quality, accessibility, governance, and lineage assessed against production AI requirements. Gaps between the current data landscape and what AI systems actually need are identified with concrete steps to close them.

Use case identification and prioritization: Systematic evaluation of AI opportunities scored by business impact, technical feasibility, data readiness, and implementation effort. A prioritized roadmap that satisfies CFO-level scrutiny, with clear business-case backing for every initiative.

Technology stack assessment: Compute capacity, data pipeline maturity, model serving capabilities, MLOps readiness, and integration infrastructure evaluated against specific target use cases. Clear recommendations on where to build, where to buy, and what to address first.

Organizational Maturity

Technology is only half the picture. Whether delivery bottlenecks stem from people, process, technology, or organizational structure – the answer determines where investment creates impact.

Development process assessment: DevOps maturity, CI/CD practices, agile adoption quality, testing practices, release management, and engineering culture benchmarked against industry standards. Process bottlenecks and organizational friction that limit technical output are identified with actionable remediation steps.

IT organization and operating model evaluation: Team structures, skill distribution, capacity allocation, decision-making processes, and governance models assessed against strategic objectives. Build vs. buy vs. partner decisions, insource/outsource balance, and platform team effectiveness evaluated for alignment with business goals.

Vendor and sourcing strategy review: Vendor landscape mapping, contract structure analysis, concentration risk identification, capability gap assessment, and optimization opportunities. Post-merger IT integration assessments compare both organizations’ technology, processes, and teams, delivering integration strategy and sequencing.

What We Deliver

We combine AI-powered analysis tools, code-level engineering expertise, and two decades of enterprise assessment experience into a comprehensive IT Due Diligence practice. Our assessments cover the full spectrum – from individual codebases to entire IT organizations.

Software Intelligence at scale: We analyze millions of lines of code using AI-powered tools, producing structured documentation, architecture maps, dependency graphs, and extracted business logic in days. Automated test generation creates the safety net for safe modernization. All outputs feed directly into downstream activities – migration planning, compliance documentation, knowledge transfer, and AI training data preparation.
Seven-domain Health Check framework: We deliver independent, technology-agnostic technical assessments across architecture, security, performance, cloud readiness, host/non-host integration, STP automation, and DevOps maturity. Modular and composable – from a focused 1-week quick scan to a comprehensive 4-week M&A due diligence. Every finding is quantified and accompanied by prioritized remediation recommendations.
AI Readiness Assessment: We evaluate readiness across data, technology, and organization – identifying the highest-value use cases, assessing data maturity, and mapping infrastructure gaps against production AI requirements. The result is a prioritized implementation roadmap with clear ROI framing, designed as the foundation for Enterprise AI Solutions engagements.
Organizational and process maturity evaluation: We assess development practices, IT organization structure, operating models, and vendor strategies against industry benchmarks. Post-merger IT integration, sourcing optimization, and governance improvements are scoped with concrete implementation steps – actionable within weeks.
M&A technical due diligence: We deliver comprehensive assessments of technology assets, team capabilities, and technical debt within deal timelines. Findings are structured for investment decisions – technical risk quantified in terms boards and investors can act on.
Independent, conflict-free advisory: We are fully independent of platform vendors and licensors – purely results-driven. Our recommendations reflect exactly what the code, architecture, and organization reveal.