AISA-Kernel Level 90%+ GPU Cost Reducer for LLMs - Sell Project

Listed July 5, 2026

About AISA-Kernel Level 90%+ GPU Cost Reducer for LLMs

AISA: 90%+ LLM Cost Reducer with Kernel-Level Governance & IP Protection

AISA (Adaptive Inference Suppression Architecture) is a production-ready, system-level infrastructure layer built for enterprises running high-throughput LLM workloads. It acts directly at the kernel layer to optimize API and hardware efficiency while enforcing absolute data isolation. Key Metrics & Validation (TRL 6) 90%+ Cost Reduction: Proven to slash repetitive inference overhead from 97% down to 6% under real-world traffic. Production Verified: Fully tested and benchmarked on live, high-speed Groq API environments (not a simulation). Instant Portability: Runs seamlessly via a single black-box installation script on any standard Ubuntu machine. Security, Governance & IP Protection Kernel-Level Governance: Real-time data routing control, ensuring strict compliance and zero unauthorized data leakage. Hardware-Locked IP Protection: Advanced architectural design that locks and protects proprietary models/weights directly at the hardware layer. Zero-Trust Execution: Fully operational in disconnected/sandbox environments without external data exposure. Asset Sale Details This is a clean, comprehensive IP / Asset Sale (Pre-Revenue). Code Quality: Over 10,000 commits of granular development history. Architecture: Highly optimized, secure, low-level codebase built for rapid integration into existing AI platforms, routers, or corporate gateways.

Project details

Website: http://www.icomnewtechnologies.com

Video 1: https://www.icomnewtechnologies.com/prl3_demo.html

Next step: <h3>Growth & Commercialization Roadmap</h3><ol><li data-list="bullet">1. Package as an Enterprise AI Gateway / Router (SaaS or On-Prem): The most immediate commercial step is wrapping the proxy and mini LM kernel into a managed B2B gateway. You can sell this directly to mid-market and enterprise companies as a plug-and-play appliance that sits between their internal apps and OpenAI/Groq/Anthropic, instantly cutting their corporate AI bill.</li><li data-list="bullet">2. Target Regulated Industries (Finance, Healthcare, Legal): Leverage the kernel-level data governance and hardware-locked IP protection. Regulated enterprises cannot use standard cloud LLMs due to compliance risks. By branding this as a "Zero-Trust, Hardened AI Privacy Layer," you can secure high-ticket corporate contracts.</li><li data-list="bullet">3. Productize the Mini LM Kernel for Edge Devices (IoT / On-Prem Hardware): Take the local embedded server and mini LM kernel architecture and deploy it to edge hardware (e.g., NVIDIA Jetson, localized corporate servers). This opens up an entirely new market for offline, high-speed, localized AI processing where cloud connectivity is impossible or restricted.</li><li data-list="bullet">4. Introduce Smart Multi-Provider Load Balancing: Expand the proxy layer to not only suppress repetitive queries but also automatically route remaining traffic to the cheapest or fastest LLM API provider at any given microsecond based on real-time token pricing, creating an ultimate "FinOps AI Router."</li><li data-list="bullet">5. Create a "White-Label" Solution for AI Agencies: Many agencies build custom LLM apps for clients but struggle with maintaining profitability due to variable API costs. The buyer can white-label this architecture and license it to AI development agencies, allowing them to offer guaranteed cost-reduction to their own client base.</li></ol>

For sale

What's included

Domain name, Source code, All related design work, Email account

Full Git Development History: Complete repository access with over 10,000 commits of granular, step-by-step development history (proving IP authenticity and code lineage). Technical Architecture Documentation: Comprehensive system-level documentation covering the proxy layer, the embedded internal servers, and the mini LM kernel integration. Benchmark Scripts & Validation Logs: The exact performance testing suites and validation configurations used on the live Groq API environment.

Reason for selling

I am a core systems engineer and R&D developer, which means my passion and expertise lie entirely in solving complex architectural and low-level optimization challenges. I built AISA to prove that production-level LLM costs could be aggressively minimized at the kernel layer without sacrificing enterprise data governance. Now that the core technology is fully validated, benchmarked, and production-ready (TRL 6), it requires a dedicated B2B enterprise sales team, marketing infrastructure, and corporate scaling resources to fully commercialize it. I am selling the complete IP and development assets to a strategic buyer, corporate gateway provider, or AI router platform that can integrate this technology directly into their existing enterprise pipeline and scale it to its full market potential.

Project metrics

Average Monthly Revenue: Pre-revenue