Accelerate Legacy Development with AI-Assisted Engineering
We help enterprise teams deliver software faster, reduce costs, and modernize legacy systems using AI-assisted engineering workflows — without compromising control, security, or compliance.
Book a discovery callNo pitch deck. No commitment. A focused conversation about your context.
Traditional Development Is Too Slow for Today's Demands
If you lead engineering at an enterprise with significant legacy or rapidly evolving software, you are likely living some version of this:
- Your modernization roadmap has items postponed two, three, four quarters in a row — not because of priority, but because the risk of touching core systems is too high.
- Every change to legacy carries weeks of analysis, integration risk, and the possibility of breaking business logic that nobody fully understands anymore.
- Your engineers spend more time maintaining than building — and adding headcount doesn't fix it. The constraint is shared context, not labor.
- Compliance, audit, and security requirements keep increasing — while delivery expectations don't slow down.
- You've evaluated AI engineering tools and seen capability without structure: pockets of adoption, no governance, neither speed nor control.
The constraint isn't strategy. It isn't budget. It's the engineering operating model.
Why Traditional Approaches Keep Failing
The reason modernization keeps stalling isn't lack of effort. The standard playbook doesn't work in enterprise reality.
Traditional migration requires direct interaction with fragile legacy systems.
The bigger and older the system, the higher the risk of breaking integrations, losing context, and introducing inconsistencies. Projects either drag for years — or get postponed indefinitely.
Adding more engineers scales cost, not throughput.
The constraint is shared context, not labor. More people on a tangled legacy codebase compounds coordination overhead.
Generic AI tools help individual developers slightly faster.
Copilot, Cursor, off-the-shelf assistants — they don't change the system. They don't reconstruct context. They don't navigate dependencies. They don't satisfy enterprise governance requirements.
Vibe-coding with AI in regulated environments isn't safe.
Your security and compliance teams will (rightly) block it. The real solution isn't more AI in the same broken process. It's a different process altogether.
AI-First Engineering, Validated in Production
DFG doesn't add AI to development. We redesign the engineering workflow around AI — with humans in control of every critical decision. This is not a framework being piloted. It is a delivery model that has been operating in production enterprise environments for years, including regulated insurance software where the cost of failure is highest.
No system intrusion.
We don't modify your existing legacy systems. No manual refactoring. No data bridges. No risky direct interaction. AI reconstructs the operational context — and migration happens around that context.
Context as the asset.
Most legacy systems have minimal documentation. Our process generates structured documentation as part of delivery — often for the first time in the system's lifecycle. You don't just modernize the system. You finally understand it.
Human-in-the-loop at every critical step.
No AI output reaches production unchecked. Every architectural decision, every refactor, every migration step has an engineer in the loop.
All four numbers come from a single four-year engagement with an insurance company in the Fortune 500. The program was staffed with 15 engineers by design — AI-native delivery scales throughput, not headcount.
Documented in Production. Not Estimated.
Client: An insurance company in the Fortune 500. 15-year-old IBM and Struts-based core systems. Full regulatory exposure. Zero tolerance for downtime.
"We finally moved a system we hadn't touched in years — and came out with full documentation and a codebase we can actually evolve."
— Engineering Director, Fortune 500 insurance company
See if the same model fits your stack.
Book a discovery callThree Questions We Hear Before Every Engagement
Individual IDE tools accelerate individual developers. They do not manage legacy modernization in regulated environments, do not carry delivery accountability, and do not handle compliance at the system level.
Consistency comes from process, not tools. A structured workflow with defined checkpoints and human validation at every critical step — what we call ADLC — produces repeatable outcomes.
You won't have to. We work inside your infrastructure and your governance boundary. Every AI output is validated by an engineer. Full audit trail is observable.
Built for Enterprise Engineering Leaders in Regulated Industries
You'll recognize yourself if:
- You are a CTO, VP Engineering, or CIO at an enterprise or large mid-market company in insurance, HealthTech, financial services, or another regulated industry.
- You have 15+ year-old core systems your team is afraid to touch — and a modernization backlog growing faster than the team can address it.
- Your compliance, security, and audit requirements make experimentation expensive.
- You cannot hire your way out. You need to move faster with the capacity you already have.
- You need to show measurable progress in the next one to two quarters, not the next one to two years.
If three of these describe your situation, we should talk.
Book a discovery callOperators. Not Advisors.
We are operators, not advisors.
We don't write strategy decks and leave. We deploy AI-first delivery inside real engineering teams and stay until it works.
Proof in the hardest environment.
Regulated insurance. 15-year-old core systems. 80+ applications modernized over four years.
We respect enterprise reality.
Compliance, security, audit, governance — these aren't obstacles we work around. They're constraints we design within.
Human oversight is the model, not a feature.
Every critical step has an engineer in the loop. Accountability for delivery sits with us; control of every decision stays with your team.
Frequently Asked
Enterprise Software Doesn't Get Simpler. The Teams Managing It Are Already AI-First.
Book a discovery callNo pitch deck. No commitment. A focused conversation about your context.