Sphere × Anthropic Claude

Claude-Powered Legacy Modernization

Your most critical systems are also your most untouchable ones. Too complex to rewrite, too risky to leave as-is, too valuable to abandon. Claude Code reads them like no tool has before. Sphere rebuilds them without losing what made them valuable.

Start With A Free Assessment

As-is specs before rebuild starts

Specs and delivery move in parallel

Automated validation before cutover

Why use Claude for Legacy Modernization

Legacy modernization breaks when teams rebuild from partial understanding. The hard part is finding the workflows, rules, dependencies, and compliance behavior buried across the system before they surface as production defects.

Claude is useful in legacy modernization because it helps turn the current application into something a team can modernize from: clearer system understanding, faster reverse engineering, earlier documentation, and stronger specifications before implementation begins. That is where AI changes the shape of the project.

Analyzes large codebases as one connected system
Surfaces hidden workflows and edge-case logic
Pulls business rules into usable specifications
Speeds up reverse engineering and documentation
Creates a stronger base for phased delivery

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What you get with AI-powered Modernization

AI-powered modernization gives the team something standard modernization often struggles to create early: a usable specification of what the legacy system actually does. From there, modernization moves through a cleaner path from reverse engineering to forward engineering to validation. Sphere takes that understanding and runs a structured, spec-driven delivery program.

2 outputs from one analysis pass

Current-state understanding and modernization specifications are created together, so discovery produces assets the delivery team can use immediately.

3 linked stages

Reverse engineering, forward engineering, and testing run as one connected workflow instead of separate handoff-heavy phases.

100K lines of code in working context

Claude can work with large amounts of code and codebase context, which makes it useful for legacy systems spread across many files and components.

1 spec-first modernization path

The project starts from what the system does, not from assumptions about how it should be rebuilt. That reduces guesswork at the point where modernization risk is highest.

Earlier test generation before release

Validation starts earlier because the modernized system is built against extracted behavior and generated specifications, not only late-stage manual interpretation.

What We Do

Sphere covers the full modernization path. The work starts with understanding what the system actually does today and moves into a structured delivery process that gives your team a clear target state, cleaner implementation flow, and lower transition risk.

System Discovery & Documentation

Claude agents map the full system as a product before any architectural decisions are made. Every module, every dependency, every workflow that exists only in the code – documented before the rebuild starts.

Module-by-module functional documentation
Business logic and dependency mapping
Undocumented workflow discovery
Integration inventory and risk surface
Institutional knowledge captured before key staff move on

Architecture & Stack Configuration

Sphere defines the target state and configures the delivery environment to match. In a Claude-native workflow, the architecture doesn't just specify what to build – it determines which specialist agents and tools are live before the first sprint.

Target architecture design
Stack selection guidance
Cloud model (AWS, Azure, GCP)
Delivery environment and agent configuration
Technical risk prioritization by module

Implementation & Refactoring

Claude Code drives implementation feature by feature through a repeatable loop. Sphere engineers review output, handle edge cases, and write the next spec while implementation runs in parallel.

Spec-driven feature delivery
Multi-agent orchestration
Human review at every gate
Parallel spec and build progress
Refactoring and debt remediation

Compliance & Risk Pattern Transfer

Legacy systems embed decades of regulatory logic that often exists nowhere but in the code. Sphere identifies, validates, and rebuilds those patterns as verified behavior – not copied lines.

Regulatory compliance pattern transfer
Security vulnerability remediation
Audit trail and reporting integrity
GDPR, HIPAA, SOC 2 alignment
Exception-handling logic validation

Validation & Equivalence Testing

Every critical path in the old system is tested against the new one. The rebuilt product proves it behaves identically where it must and demonstrably better where it should.

Automated equivalence test suite generation
Regression testing across all workflows
API and UI validation (Playwright + curl)
QA agent integration throughout delivery
Missing coverage identification

Post-Launch & Continuous Modernization

The rebuilt system stays modern. Feature additions, performance work, and subsequent modernization phases all run through the same spec-driven loop – so the new codebase doesn't become the next legacy problem.

Post-launch bug resolution
Performance monitoring and tuning
Feature additions on retainer
Documentation maintenance
Next-phase modernization planning

How Legacy Modernization Runs

1. Free Assessment

Sphere reviews your system: codebase size, language stack, integration surface, regulatory requirements. You leave with a realistic scope, a phased roadmap, and an honest picture of what the engagement involves.

2. Product Extraction Sprint

Claude agents document the full system as a product. Functional requirements for the target state written and validated with your team. Architecture defined. Delivery environment configured. Nothing moves to implementation until what must survive is confirmed in writing.

3. Phased Implementation

Feature by feature through the spec-driven loop. First phase typically live in 6–12 weeks. The legacy system keeps running throughout. You see working software before the full program is committed.

4. Go-Live & Handover

Equivalence validation. Production deployment. Full documentation package. Test coverage the original never had.

5. Ongoing Support

Monthly sprint cycles for feature additions, performance work, and next-phase modernization – through the same loop, with the same team.

Upgrade Legacy Systems with Claude

Use Claude to speed up code analysis, documentation recovery, refactoring, and migration planning across complex legacy environments.

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Industries
We Serve

Financial Services & Banking

Banks spend 70–75% of IT budgets on legacy maintenance. Core banking, mainframe batch processing, loan origination, regulatory reporting. Sphere preserves the compliance patterns and audit integrity that regulated institutions cannot compromise.

Financial Services practice

Insurance

Policy administration, claims processing engines, pricing models built on rule sets no one has fully documented. The average audit reveals 3–4x the cost that appears on the surface.

Insurance practice

Healthcare

EHR integrations, legacy patient data workflows, clinical systems with compliance requirements that compound every year. HIPAA-aligned delivery from the first sprint.

Healthcare practice

Private Equity Portfolio Companies

Post-acquisition technical assessment reveals the legacy burden on the balance sheet. Sphere runs modernization as a value creation workstream – with defined timelines, defined ROI benchmarks, and the delivery velocity that PE timelines demand.

Private Equity practice

Manufacturing & Supply Chain

ERP integrations, production scheduling systems, legacy inventory logic modernized to current APIs – without disrupting floor operations while the transition runs.

Manufacturing practice

Hear from

our clients

Hear from our clients

Lee Ebreo

VP of Engineering at Credit Ninja

These things would not have been achievable if we did not build our own in-house system and if we did not partner with Sphere to help us achieve our goals.

Selah Ben-Haim

VP of Engineering at Prominence Advisors

Our experience with Sphere and their team has been and continues to be fantastic. We keep throwing new projects at them, and they keep knocking them out of the park (including the rescue of a project that was previously bungled by another vendor).

Ben Crawford

Senior Product Manager at Enova Financial

I would expect to be delighted. It's been a really positive experience, working with Sphere, and I would expect you to have the same.

Mark Friedgan

CEO at CreditNinja

Sphere consistently prioritizes the needs of their clients, demonstrating both agility and teamwork. As an offshore team, they have been an integral part of our organization and we plan to continue growing with them.

René Pfitzner

Co-Founder at Experify

Sphere provided excellent full-stack development manpower to augment our team and help push our product forward. They are easy to work with, tech-savvy and proactive.

Bruce Burdick

Chief Information Officer at Integra Credit

We've been working with Sphere and its excellent consultants since our founding. I've found that they are true partners in the success of our business.

Jemal Swoboda

CEO at Dabble

The resources and developers that Sphere Software provides are skilled and have the required technical expertise, but more importantly, they have helped us build a culture of excellence within our team.

Arthur Tretyak

Founder and CEO at IntegraCredit

With Sphere, we were able to migrate in half the time it would take to train an additional FTE… and for a fraction of the cost. Our experience with Sphere has been exceptional.

Lee Ebreo

VP of Engineering at Credit Ninja

These things would not have been achievable if we did not build our own in-house system and if we did not partner with Sphere to help us achieve our goals.

Selah Ben-Haim

VP of Engineering at Prominence Advisors

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Sphere in Numbers

We understand that actions speak louder than words and numbers but here are some key facts about us.

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Years of Excellence

Projects Delivered

Countries

Globally diverse, community-focused

Clients

top 20 average 8+ years

Frequently Asked Questions

AI-powered legacy modernization uses large language models like Claude to analyze, document, and rebuild outdated software systems. Instead of relying on engineers to manually read through years of accumulated code, Claude processes the entire codebase as one connected system and extracts what it actually does. This produces functional specifications, dependency maps, and documented business logic before a single line of new code is written – giving modernization teams a verified foundation to build from rather than a set of assumptions.

Claude reads large codebases – up to 100,000 lines – in full context, treating the system as one connected product rather than isolated files. It identifies business rules, undocumented workflows, integration dependencies, and compliance patterns that are buried across modules and have never been written down. What typically takes a senior engineering team months to piece together, Claude surfaces in days – and produces it in a structured, reviewable format your team can validate before implementation begins.

Claude analyzes existing code structure, identifies technical debt, redundancy, and outdated patterns, and generates specifications for refactored output. It is particularly effective on codebases where documentation is missing or out of date – which describes most legacy systems that need refactoring. Sphere engineers review and validate each output at every stage, so Claude drives the analysis and generation while humans own the architectural decisions.

Traditional legacy modernization relies on human engineers manually reading through code, interviewing staff who may no longer be available, and building understanding incrementally over months. AI-powered modernization compresses that reverse engineering phase dramatically – Claude extracts system behavior, dependencies, and business logic faster and more completely than a manual process can. The practical difference is that implementation starts from a verified specification of what the system does today, not from partial understanding filled in with guesswork.

Sphere uses Claude to run a full product extraction pass before migration begins – documenting every module, workflow, and integration contract in the existing system. That documentation becomes the specification the new system is built against, phase by phase, while the legacy system stays live. The result is a migration grounded in what the system actually does, with equivalence testing at every stage to confirm the new system matches the old one where it must and improves where it should.

Claude-based modernization works across mainframes, monolithic enterprise applications, custom ERP systems, core banking platforms, claims processing engines, EHR integrations, and manufacturing scheduling systems. The common thread is systems where critical business logic exists only in the code – undocumented, partially understood, and too risky to touch without a complete picture first. If the knowledge is in the codebase and nowhere else, that is exactly the problem Claude is built to solve.

The first working phase typically delivers running software in 6–12 weeks, built against Claude-extracted specifications with the legacy system still live. Full modernization runs in phases rather than as a single rewrite – each phase validated before the next begins, so your team sees real output before the full program is committed. Timeline varies by codebase size, integration complexity, and regulatory requirements, all of which Sphere scopes during the free assessment.

Regulatory logic in legacy systems – HIPAA, SOC 2, GDPR, audit trail requirements – is often the hardest part to migrate because it exists only in code, sometimes across dozens of modules with no documentation. Claude identifies and maps those patterns during the extraction phase, producing explicit specifications that compliance teams can review before implementation begins. Sphere then rebuilds those patterns as verified, tested behavior in the new system – not copied lines, but confirmed logic validated against the original.

When engineers who built or maintained a legacy system leave, they take years of undocumented context with them – and that knowledge gap is one of the most common triggers for a modernization project. Claude extracts that institutional knowledge directly from the codebase before it becomes a crisis, turning implicit system behavior into structured documentation your team owns. The product extraction phase is specifically designed to run before staff transitions, not after.

Sphere builds an automated equivalence test suite that compares the rebuilt system against the original, workflow by workflow and API call by API call. Every critical path in the legacy system is tested against the new one before cutover – using Playwright for UI validation and automated regression testing across all workflows. The rebuilt system does not go live until it proves it behaves identically where it must and demonstrably better where it should.

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