Legacy Migration Services

See what is holding you back.

The symptoms appear quickly — slow builds, mysterious outages, postponed releases. But the causes are deeper, entangled in outdated architectures, patterns, and half-documented workarounds that silently influence every deployment decision.

Technical debt doesn’t just show up in code. It extends across your systems, CI/CD processes, testing strategies, infrastructure, and even your team’s behavior.

We perform a full-spectrum audit that turns scattered pain points into mapped risk, a vital step when migrating legacy applications with minimal disruption.

• Visualize architectural dependencies, ownership boundaries, and defect chains with tools like CodeScene and Lattix.
• Analyze CI pipelines and test coverage using SonarQube and Launchable to identify security vulnerabilities in releases.
• Detect runtime hotspots and hidden service coupling using profiling tools like Pyroscope and Instana.
• Compare incident history and deployment metrics to identify recurring issues and their technical origins.
• Discuss directly with technical leads to uncover hidden debt patterns and constraints that are often overlooked.

Get a structured overview of the entire stack and the entire team. Our AI Solution Accelerator™ automates system-wide debt analysis and risk mapping. You get a clear picture of where the problems are, how they are spreading, and what needs to be changed first.

Stabilize the core. Clear the way.

Some parts of the code base resist every change, especially in projects involving legacy app migration services. Releases break at the same points. Engineers keep the context in their heads, not in the system.

We explore these friction zones and align them with how the system is used and how your team thinks.

That’s how we do it:

• Determine the radius of impact of unstable modules, including release blockers, rollback frequency, and high change frequency.
• Identify convergence points where legacy logic overlaps with critical paths and API interfaces.
• Prioritize remediation actions based on volatility, depth of dependency, and alignment with business processes.
• Decompose monolithic clusters using domain-aligned boundaries (DDD, hexagonal, or event sourcing patterns).
• Implement code transformations with automation tools such as OpenRewrite, AST matchers, and Semgrep.
• Gradually replicate legacy subsystems — queue layers, I/O operations, service brokers — to reduce risk in live environments.
• Capture tribal knowledge during refactoring to eliminate single points of failure and increase team autonomy.

All work is integrated into your current delivery rhythm. Our AI Solution Accelerator™ drives focused refactoring by combining deep code analysis and automation.

We develop quality practices that integrate seamlessly into your delivery processes — in small steps, within a narrow framework, and always observable. This is not a process for its own sake. It’s the framework your team can move with, without guesswork.

And that’s how we do it:

Define operational non-functional requirements (NFRs) with your team, including response time targets, recovery thresholds, defect budgets, and trace coverage.

• Refine the test suite with mutation tests, coverage heatmaps, and priority zones tied to system-critical processes.
• Integrate real-time linting and pre-merge enforcement with Semgrep, Danger, and a custom policy engine for seamless code quality assurance.s
• Rework CI to reduce cycle time and detect faulty tests before they reach production.
• Normalization of logs and traces for all new features, supported by OpenTelemetry and structured logging standards.
• Integrate validation during deployment and post-release sanity checks with canary deployments and observability hooks.
• Build team habits around the principle of “fix it where you touch it” — tying small cleanups to everyday tasks and commitments.

Our AI Solution Accelerator™ embeds targeted automated testing, real-time linting, and observability hooks into your delivery pipeline, making quality predictable, measurable, and integral to every commit.

Know where it breaks — before it breaks.

Incidents rarely start loudly. Most begin as quiet latency spikes, queue buildup, or background jobs that don’t recur. Left alone, these fragments become outages. And when observability is low, recovery becomes a game of guesswork.

We help teams build platforms that recognize stress early and manage it without escalation.

What we focus on:

• Track system reliability patterns, from alert fatigue to hidden retries — and isolate failure points.
• Instrument key workflows with distributed tracing and correlation IDs to track causality, not just symptoms.
• Set actionable SLIs/SLOs that relate to the impact on users, rather than just the state of the infrastructure.
• Optimize alerting pipelines with severity filters, escalation policies, and runbook hooks to minimize noise and false urgency.
• Profile GC behavior, I/O throughput, and service latency under load with tools like eBPF, Grafana, and k6.
• Capture and log system states before, during, and after release cycles to detect slow degradation.

Review incident retrospectives to identify both structural blind spots and procedural gaps. Our AI Solution Accelerator™ integrates advanced observability, real-time alert tuning, and actionable SLO enforcement.

Extend Your Team’s Reach

Engineering speed often slows at the review stage, the test suite, or the legacy zones no one wants to touch. The blockers aren’t a strategy — they’re a matter of time and cognitive load.

We embed AI into your development flow to reduce noise, highlight risk, and clear space for high-impact work.

What we deploy:

• AI-powered static analysis to detect hidden logic flaws, unreachable paths, and structural complexity.
• PR summarization and change scoring to surface dangerous diffs before they merge.
• Test suite extension based on observed gaps in coverage, edge case behavior, and runtime patterns.
• Analyze duplication and tight coupling across services with full awareness of context and architecture.
• Fine-tuned prompts for refactoring proposals that align with your coding standards and architecture vision.
• Internal knowledge search trained on your incident postmortems, changelogs, and service docs.

We keep your team focused where it counts — by letting machines handle the routine, the repeatable, and the easy-to-miss. Our AI Solution Accelerator™ combines static code analysis, risk-based PR scoring, and intelligent test expansion, uncovering hidden risks early and freeing your engineers to innovate where it matters most.