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Pinpoint. Protect. Fix.
BayeFix identifies the critical files in your legacy .NET or Java codebase, generates a test safety net before you touch anything, and gives your team a costed, prioritized roadmap to modernize — file by file, sprint by sprint.
Book an assessment →The Problem We Solve
Legacy modernization fails for three reasons:
Wrong starting point.
Teams either try to rewrite everything at once or pick modules based on gut feel instead of data. You've probably tried before — a rewrite that ran over budget, a consulting engagement that produced a PDF nobody acted on.
No safety net.
Even when you identify the right files, refactoring without comprehensive test coverage means you're trading known bugs for unknown ones. So the code stays frozen.
No business case.
Engineering knows the system is fragile. The CFO sees it as "working." Without quantified ROI — "fix this file, save $15K/quarter" — modernization budgets don't get approved.
BayeFix solves all three — in weeks, not months.
How BayeFix Works
Phase 1 The Trust Funnel — Pinpoint the Kill Zone
BayeFix doesn't demand full codebase access on day one. The Trust Funnel builds confidence incrementally:
- Which modules generate the most defects
- What percentage of bugs escape to production
- What technical debt costs you per quarter (dollar figure)
- How often "fixed" bugs reopen within 30 days
Outcome: "Is the team slow because of bad process or bad code?" — answered with data.
- Kill Zone Matrix — files with both high churn AND high coupling
- Bus factor — files maintained by a single developer
- Test co-evolution — are tests keeping up with code changes?
- Ticket-to-file correlation — proves which code causes which failures
Outcome: Surgical precision — which files to fix first — still without reading a line of code.
- Cyclomatic complexity per function with testability ranking
- Cloud-readiness issues (hardcoded IPs, local state)
- Security vulnerabilities and dependency risks
- ROI per fix — "Save $15K/quarter by refactoring this class. Payback: 1 month."
Outcome: A prioritized, costed, dependency-aware refactoring roadmap.
For regulated industries: deterministic analysis mode produces reproducible reports for OSFI, PIPEDA, HIPAA, PCI-DSS compliance evidence.
Phase 2 Protect — Generate Tests Before Migration
Before any migration begins, the BayeFix engine generates a comprehensive E2E test suite around the code you're about to change.
Smoke tests
One per endpoint, verifying basic health
Security tests
Unauthenticated access, cross-role authorization violations
CRUD lifecycle tests
Auto-detected from REST patterns
Business flow tests
Multi-step workflows covering real user journeys
The Execute-Refine Loop
Phase 3 Fix — Migrate With Confidence
With analysis pinpointing where and tests providing coverage, migration happens safely:
AWS Transform
For language-to-language migrations. BayeFix tells it which files to prioritize and the test suite validates every transformation.
AI Code Agents
Copilot, Claude, Cursor — for targeted refactoring of Kill Zone files. Generated tests catch regressions immediately.
Strangler Fig Pattern
For gradual replacement. BayeFix sequences the work based on dependency analysis so you don't cut load-bearing walls.
Your Own Team
With the roadmap, the tests, and the ROI justification in hand.
Assessment Deliverables
Kill Zone Report
- Files plotted on Churn × Complexity matrix with risk scoring
- Ticket-to-file mapping proving causality between Jira bugs and source code
- Bus factor analysis flagging single-developer knowledge risks
- Shadow cost calculation per module
Auto-Generated Test Suite
- E2E regression tests across smoke, security, CRUD, and business flow
- Runtime-calibrated against your actual microservices
- Ready to run in your CI/CD pipeline
CFO-Ready ROI Model
- Dollar savings per fix with payback period
- Quarterly shadow cost of inaction
- 3-year return projection
- Cost of fix vs. cost of continued firefighting
Prioritized Migration Roadmap
- Dependency-aware sequencing (don't cut load-bearing walls)
- Quick wins (this week), high-impact (this sprint), strategic (next quarter)
- Effort estimates per recommendation
- For regulated industries: reproducible compliance evidence
Common Questions
Do you need access to our source code?
Not initially. Stages 1–2 deliver significant value using only ticket metadata and git log statistics — no code content. If you proceed to Stage 3, we analyze only the high-risk files from earlier stages. All code is encrypted (AES-256) and auto-deleted after analysis.
We already have SonarQube.
Good — keep it. SonarQube shows you 3,000 issues. BayeFix tells you which 5 to fix first, proves why with ticket-to-file causality, quantifies the dollar impact, and generates the tests to make the fix safe. We're the prioritization layer on top.
What about .NET? Java?
BayeFix was built for enterprise .NET and Java codebases. Stage 1–2 analysis is fully language-agnostic. The engine supports .NET/C#, Java, JavaScript, TypeScript, Python, and Rust.
How is this different from hiring a consulting firm?
Speed and completeness. A Big Four engagement takes 3–6 months and costs $150K+ for a report. BayeFix delivers Kill Zone analysis, a generated test suite, and a costed roadmap in 3–4 weeks at a fraction of the cost. And we can implement the fixes — because we're engineers, not slide deck authors.
Can we run this on-premise?
Yes. The platform is containerized (Docker + Kubernetes) and the engine is a standalone CLI binary with no cloud dependency. On-premise deployment is available for regulated institutions.
How long does an assessment take?
Starter (metadata only): 1–2 weeks. Full Assessment (all 3 stages + test generation): 3–4 weeks from kickoff to delivered roadmap with test suite.
Stop guessing which code to fix. Start with the data.
No pitch deck. No pressure. We'll tell you honestly if BayeFix can help.
Book a 30-minute diagnostic call →