MongoDB launches AMP as an AI-driven platform to modernize legacy applications
Most legacy systems are a drag. They slow down innovation, pile up technical debt, and push enterprises into a corner where modern tools like AI can’t do their job. So, MongoDB did something about it. They rolled out AMP, an AI-powered modernization platform specifically built to help companies move away from outdated infrastructure and into something scalable, fast, and smart.
In practical terms, AMP is designed to take old applications, littered with hard-to-maintain code, brittle architecture, and frameworks no one wants to touch, and turn them into services ready for AI and automation. That’s necessary if you want to remain competitive. Shilpa Kolhar, MongoDB’s SVP of Product and Engineering, calls it out directly: legacy apps block AI integration and hold companies back. She’s right.
The point is straightforward. If the core engine of your business, the apps that support operations, decision-making, or products, can’t handle AI integration, you’re behind. AMP isn’t a patch. It’s a foundational shift. Companies that adopt it are essentially retooling themselves to compete on modern terms.
AMP employs a hybrid approach
AMP isn’t just automation, it’s automation with oversight. That matters. Most tools in the market either go fully automated and risk losing quality, or they’re 100% manual and painfully slow. MongoDB took a smarter route: combine AI with engineering teams that know exactly what they’re doing.
Here’s how it works. Organizations start with MongoDB’s team in a consulting phase. Everything gets mapped out, scope, expectations, pricing. What follows is AI-led testing on the existing application to take a snapshot, what Shilpa Kolhar refers to as a “baseline”,of how the legacy system behaves in production. This is critical. You can’t modernize a system you don’t fully understand.
Once you’ve got the baseline, the process moves through what Kolhar describes as a test-transform-trial-deploy loop. Think of it as continuous iteration with built-in guardrails. The AI doesn’t guess, it works based on known performance criteria. And the engineers aren’t watching from the sidelines, they’re deep in the code, overseeing changes and reducing the risk of critical failure. It’s what Devin Dickerson from Forrester calls “holistic,” and there’s no better word for it.
If you’re making enterprise-level bets on tech that needs to last and scale, this is the type of modernization cycle you want, fast, intelligent, and firmly under control.
AMP addresses gaps in current modernization solutions
Most current AI developer tools are built for starting from scratch. They’re optimized for greenfield projects, not for untangling years of legacy code and undocumented systems. That’s a limitation. MongoDB’s AMP takes a different route. It’s not trying to restart your business tech from zero. It’s built to upgrade what you already have, faster, with less disruption, and with more reliability.
Devin Dickerson, Principal Analyst at Forrester, points out that most tools on the market are best suited for new apps. That leaves a big gap when enterprises need to modernize what’s already in production. That’s where AMP fits. It effectively bridges the complexity of legacy systems with the speed and intelligence of AI-led transformation. This does more than automate, it systematizes results and reduces risk.
Rachel Stephens from RedMonk adds another key insight, it’s not just about tools. Traditional modernization depends heavily on system integrators or third-party consultants. These projects are slow, expensive, and often stall before generating any ROI. With AMP, MongoDB introduces a way to sidestep that inefficiency. You still get expert guidance, but the process isn’t trapped in endless cycles of manual labor and review.
For executives weighing digital transformation strategies, it’s important to realize that efficient modernization isn’t just a technical challenge, it’s an operational one. AMP helps solve both by reducing dependencies on manual input while preserving precision where it matters. It’s faster, more scalable, and has a structure that reduces the common failure points in legacy transformation.
MongoDB differentiates its modernization platform by emphasizing a data-layer-centric approach
A critical decision-point for any modernization project is data. If the data layer isn’t handled correctly, everything else collapses. MongoDB understands that and leads with it. AMP starts modernization from the data layer out, prioritizing how data works, moves, and scales before touching app logic or service layers.
That approach matters, because in most legacy systems, the data layer is the most rigid and least documented part, and often the biggest blocker to evolving an application. Devin Dickerson of Forrester notes that MongoDB’s strategy directly addresses this by putting the data layer at the core of the modernization process. It’s precise, foundational thinking.
Another key point for any enterprise executive: platform-agnostic design. A lot of vendors in this space sell tools that are deeply tied to specific cloud platforms. That creates lock-in. It restricts flexibility. AMP breaks from that model. By maintaining cloud neutrality, MongoDB gives organizations the ability to evolve their systems without becoming dependent on one provider’s infrastructure. That’s not just good engineering, it’s good business strategy.
For companies with multi-cloud strategies, AMP offers necessary control. The freedom to move components and data where it makes the most sense, without paying a penalty in compatibility or performance, is a significant differentiator. In a time when agility is everything, vendor lock-in is a risk few enterprises can afford. MongoDB sidesteps it by considering long-term scalability and adaptability from day one.
Early adopters of AMP report substantial improvements in code transformation efficiency
Enterprises using AMP aren’t just updating legacy systems, they’re seeing measurable, repeatable gains in performance. MongoDB reports that early adopters like Bendigo Bank and Lombard Odier have achieved up to 10x improvements in tasks related to code transformation. That’s not a general improvement claim, it’s a specific increase in operational throughput.
Those kinds of results matter when you’re allocating budget and resources to modernization. Executives need clarity on returns, and AMP is already producing them. The gains come from accelerating the most time-intensive parts of application redesign, refactoring code, testing changes, and deploying updated systems at scale. By doing this faster and more accurately, teams can shift their focus from fixing old problems to deploying new capabilities.
The list of supported legacy systems isn’t fully public yet, as MongoDB is rolling out coverage in staged development. But they’ve made it clear that support will expand incrementally, based on enterprise needs and technical feasibility. That signals long-term commitment, but also a focused execution strategy. They’re not promising everything up front. They’re delivering what works and growing from there.
For executives evaluating modernization platforms, the takeaway is straightforward. AMP doesn’t just promise acceleration. It’s hitting those targets in production environments. Those 10x results aren’t abstract, they’re happening now with high-trust institutions. That should carry weight when you’re deciding how to evolve your architecture and who you want to partner with to do it.
Key highlights
- AMP enables scalable AI integration: MongoDB’s AMP helps enterprises replace legacy systems with AI-ready architecture, addressing technical debt that slows digital transformation. Leaders should prioritize this shift to stay competitive in innovation-driven markets.
- Human-AI hybrid model reduces transformation risk: AMP combines AI automation with global engineering teams to streamline modernization while maintaining operational stability. Executives should leverage this model to accelerate delivery without compromising system integrity.
- Designed to overcome outdated modernization methods: AMP fills a major industry gap by targeting legacy updates, not just new development. Organizations relying on manual system integrator models can benefit from faster turnaround and lower risk through MongoDB’s structured process.
- Platform built to avoid vendor lock-in: By focusing on the data layer and maintaining cloud neutrality, AMP provides modernization flexibility while avoiding long-term platform dependencies. Leaders with multi-cloud strategies should consider AMP to retain infrastructure agility.
- Early results show real productivity gains: Customers like Bendigo Bank and Lombard Odier have reported up to 10x efficiency in code transformation tasks. Decision-makers should evaluate AMP’s early outcomes as strong indicators of ROI and modernization success.
