Forget Copilots: This Startup Claims It Can Slash Coding Costs by 80%

Bringing “agentic AI” to the legacy code crisis

When Aravind Jayendran looks at legacy software, he doesn’t see lines of code. He sees drag.

The Bengaluru-based founder and CEO of LatentForce has just secured a $1.7 million seed round to cut that weight loose. Using what the company calls “agentic AI,” LatentForce aims to transmute brittle, aging systems into modern enterprise software. The round was co-led by Ideaspring Capital and Yali Capital, funding that will push the startup’s R&D beyond its Indian roots and into global markets.

“Most enterprises today are constrained by decades of accumulated technical debt,” says Jayendran. “Code migration is not just a coding problem; it is fundamentally a system transformation challenge.”

From the lab to the enterprise

Founded in 2024, LatentForce isn’t a typical garage startup. It spun out of the Foundation for Science and Innovation Development at IISc Bangalore. The founding trio—Jayendran, CTO Vinay Kyatham, and research lead Dr. Prathosh A P—bring a heavy mix of deep generative models and academic rigor to a messy problem.

While a thousand AI coding tools are currently pitching themselves as “copilots” for individual developers, LatentForce is hunting bigger game. They are targeting the sprawling, undocumented monolithic systems that run global banks, insurers, and telecom giants. These are migration projects that usually span years, touch millions of lines of code, and burn through fortunes in consulting fees.

LatentForce’s bet is that modernizing these beasts isn’t a chatbot problem; it’s an orchestration problem.

The startup is building deterministic migration pipelines using task-specific Small Language Models (SLMs). Instead of just generating new syntax, the platform refactors and validates code to match modern governance standards. The company claims this approach can slash the cost and time of major migrations by up to 80%.

The philosophy: Continuity of intent

Internally, the team frames modernization as translation without loss. Co-founder Prathosh argues that the real asset in legacy software isn’t the syntax, but the business logic trapped inside it.

“For us, modernisation is not just rewriting code; it is continuity of intent, carrying forward the wisdom of the past into the architecture of the future without distortion,” Prathosh explains.

The system uses AI agents to map that logic and dependency graphs, proposing changes that upgrade the infrastructure while guaranteeing the software still behaves the way the business needs it to. Instead of armies of consultants combing through COBOL or Java line by line, LatentForce wants enterprises to treat modernization as a controlled pipeline designed to:

Ingest and analyze complex dependency graphs.
Transform code using specialized Small Language Models.
Verify and deploy with strict governance controls.

Engineering control at scale

CTO Vinay Kyatham is blunt about why previous attempts at automated migration have failed.

“Enterprise migration projects fail not because of lack of intent, but because of loss of engineering control at scale,” Kyatham says. “We built LatentForce to give teams deterministic pipelines, security by design, and the ability to modernise mission-critical systems with confidence rather than guesswork.”

That emphasis on control—rather than just speed—is the core pitch to CIOs who have been burned by multi-year transformation efforts that inevitably slip or balloon in budget.

The $5 trillion problem

The target market is massive, but crowded. LatentForce estimates the modernization sector at $22.7 billion today, while its investors cite a “$5 trillion legacy code market”—a figure representing the economic value currently stuck in outdated mainframes and servers.

Enterprises currently pour money into global systems integrators like Accenture and TCS to manage these transitions manually. Meanwhile, AWS, Microsoft, and GitHub are racing to deploy AI in the same space. LatentForce isn’t trying to kill the consultants; it wants to be the tool they use. Ideally, it positions itself as the infrastructure layer for migration that SIs and internal teams plug into.

Why the investors wrote the check

For the backers, this is an infrastructure play. Naganand Doraswamy, managing partner at Ideaspring Capital, sees the combination of custom LLMs and graph engines as a potential shift for the sector, noting the platform’s vertical integration.

Yali Capital is banking on the team’s technical depth. Ganapathy Subramaniam of Yali notes that “AI-first deep-tech” is central to their thesis, pointing to the founders’ background in applied research as a key differentiator.

LatentForce is already running pilots with developers in the BFSI and SaaS sectors across India and the US. However, like many seed-stage infrastructure plays, hard metrics—customer names, pricing models, and volume of code migrated—remain under wraps.

The challenge now is proving repeatability. LatentForce has a focused thesis on one of tech’s least glamorous problems. If they can turn the “brownfield mess” of legacy debt into a clean, automated engineering process, they won’t just be another AI tool; they will be the solution to every CIO’s oldest headache.