Key Highlights

• 14-year-old Arjun Shah has developed Supercompress, an AI tool designed to reduce token usage for AI applications.
• The startup claims the technology cuts context by an average of 65% while preserving over 98% of critical information.
• Shah says Supercompress currently has around 150 users and is available as a plugin for coding agents.
• The California-based Indian-origin entrepreneur has applied to Y Combinator for startup funding.
• If selected, the startup would receive an initial investment of $500,000 through Y Combinator's standard funding model.

Teen Entrepreneur Targets Rising AI Costs

Arjun Shah, a 14-year-old Indian-origin entrepreneur based in San Jose, California, says he has developed an AI tool aimed at addressing one of the industry's growing challenges—high AI token costs.

His startup, Supercompress, is designed to reduce the amount of text sent to large language models by removing redundant information before processing, potentially lowering computing costs for businesses using AI applications.

The claims about the tool's performance are based on statements made by Shah and have not been independently verified.

How Supercompress Works

According to Shah, AI applications often send large amounts of contextual information to language models, even when much of it is unnecessary for generating an accurate response.

Supercompress is designed to:

• Analyse a user's query.
• Identify the most relevant portions of the available context.
• Remove redundant information.
• Send a shorter prompt to the AI model.

Shah says the system reduces context by an average of 65% while retaining more than 98% of critical information.

In one demonstration shared by the startup, the tool reportedly compressed context by 97.5% while producing a response similar to the original prompt.

Current Users and Product Availability

According to Shah, Supercompress currently serves around 150 users.

The product is also available as a plugin for AI coding agents, allowing developers to integrate context compression into AI-assisted programming workflows.

The company says reducing token usage could help organisations lower operating costs associated with large language model APIs.

From Coding at Seven to Building AI

Shah says he began experimenting with Python programming at the age of seven before moving away from traditional coding because he disliked memorising syntax.

Instead, he focused on understanding the mathematical and conceptual foundations of artificial intelligence.

He credits AI development tools such as Claude Code and Cursor with enabling him to build software more efficiently.

According to Shah, he later spent months studying neural networks before developing his own AI framework.

Startup Seeks Y Combinator Backing

Shah has now applied to Y Combinator, one of Silicon Valley's best-known startup accelerators.

If selected, Supercompress would receive $500,000 in funding under Y Combinator's current investment structure, along with mentorship and access to the accelerator's founder network.

Y Combinator has previously backed companies including Airbnb and Reddit.

Selection into the programme is highly competitive, and Shah's application is currently under review.

Earlier AI Project

Before Supercompress, Shah worked on therooted.ai, an AI-powered retrieval system that referenced classical Ayurvedic texts, including the Charaka Samhita, to suggest remedies for common ailments.

According to Shah, his mother supported him throughout his entrepreneurial journey and co-founded that earlier project.

Why This Matters

As businesses increasingly adopt generative AI, managing token usage has become a significant cost consideration, particularly for applications processing large volumes of text. Tools that can reduce unnecessary context while maintaining response quality could improve efficiency and lower operational expenses. However, the effectiveness of such solutions ultimately depends on independent validation and real-world performance across diverse AI workloads.

Frequently Asked Questions (FAQs)

Who is Arjun Shah?

Arjun Shah is a 14-year-old Indian-origin entrepreneur based in San Jose, California, and the founder of the AI startup Supercompress.

What is Supercompress?

Supercompress is an AI context-compression tool that aims to reduce token usage by removing unnecessary information before sending prompts to language models.

How much token reduction does the startup claim?

According to the company, Supercompress reduces context by an average of 65% while preserving more than 98% of important information.

Has Supercompress received Y Combinator funding?

No. Shah has applied to Y Combinator, but the application is still under review.

Why are AI tokens important?

AI providers typically charge based on the number of tokens processed. Reducing token usage can help businesses lower the cost of using large language models.