Engineering High-Performance AI & Software Systems.
Introlic is an independent technology lab focused on next-generation model architectures, high-speed generative systems, and modern digital platforms. We build fast, efficient, and unconstrained technology from first principles.
Founded in India • Building for the World
Born in India.
Engineered for the World.
Introlic was founded on March 26, 2026 by mr.Faiz — at the age of 17. It was born from a question that first surfaced in 2019: "Why is there no Indian company among the ranks of Google, Microsoft, or Tesla?"
That question became an obsession. Starting with just a computer and an internet connection, mr.Faiz taught himself programming through YouTube and ChatGPT, built and shipped live platforms, scaled to 13,000 monthly users, learned exactly why most Indian tech companies hit a ceiling, and decided to attack the root cause instead of the surface.
The ceiling for Indian tech isn't talent. It is architecture dependency. Most companies here build services and products on top of foreign AI infrastructure they do not control. Introlic was founded to close that gap — not by copying what already exists, but by engineering a better substrate from the mathematical ground up.
Parallel Generative Paradigms
We are exploring model architectures based on discrete diffusion and parallel denoising. Our research focuses on shifting away from standard sequential token generation to build highly efficient, scalable language engines that run with minimal computational footprint.
"We don't build for one country. We build for the entire human horizon. If you want to scale, you must never limit your ambition with a geography."
— mr.Faiz, Founder
Sovereign Intelligence
SOVEREIGNTYBuilding AI infrastructure India owns end-to-end — from the mathematical core to the inference router — with zero dependency on foreign closed-source APIs.
Global Deployment Radius
EXPANSIONIndia is our origin, not our ceiling. Introlic is engineered for enterprise deployment from Tokyo to San Francisco.
Native System Philosophy
ENGINEERINGWe prioritize custom kernel-level optimization over framework abstraction, ensuring our compute cycles are spent on logic, not overhead.
Efficiency Over Capital
EFFICIENCYInspired by the $6.3M DeepSeek paradigm — extreme mathematical optimization outperforms runaway compute spend.
Outlier DNA
EXECUTIONFounded by a self-taught engineer who built and scaled a 13,000-user platform before the age of 16.
Our Vision
What Introlic
is here to achieve.
We are not building another model. We are engineering the infrastructure layer that brings Parallel Intelligence into production — with the precision of native systems and the ambition of a generation that refuses the ceiling.
The first foundational LLM designed and built in India, for the world.
Breaking the absolute dependency on foreign model providers. We are engineering a math-native, parallel diffusion substrate from the ground up — tailored to run efficiently on domestic infrastructure, proving that global AI architecture can be pioneered from India.
A search engine built on mathematical retrieval, free of trackers.
Modern search has become an ad-driven surveillance monopoly. We are building a native, privacy-first search index powered by our parallel token reasoning engine — returning objective truth without foreign censorship or profiling.
Reclaiming the public square with an independent social platform.
Social networks should be critical national infrastructure, not channels for foreign narrative control. We are engineering a decentralized, high-throughput social engine that operates under mathematical sovereignty — giving users control over their data.
Reducing foreign dependency across our entire stack.
From Triton/CUDA kernels to C++ runtime layers and edge deployment protocols, we are eliminating dependency on the legacy Western stack. True sovereignty means running on bare metal we control, not renting APIs from monopolies.
Efficiency-driven growth scaling to the flagship ARC One model.
We currently run on MR.FAIZ's personal funds while looking for the right long-term funding partners. This ensures absolute independence in our early stages as we scale to the flagship ARC One model.
The Architecture of
Scaling & Progression.
The Honest Strategy
Why not build the 390B flagship directly?
Building Anyway.
mr.Faiz is 17 years old. There is no institutional backing, no family capital, no VC safety net. The resources available right now are limited — and that is a fact, not an excuse.Waiting until conditions are perfect is not a strategy. It is surrender.
01 // No Money? Start Smaller.
If the 390B flagship is beyond current reach, the logical move is not to stop — it is to build what you can afford now. A 220M model is a real model with real output. That is where we begin.
02 // Prove, Then Scale.
Every XT-Class milestone is evidence. Compounding evidence attracts the right funding partners. Currently running completely on MR.FAIZ's funds, the path to the flagship is built milestone by milestone.
Efficiency Over Capital.
DeepSeek demonstrated that $6.3M and extreme mathematical discipline can outpace billion-dollar labs. The constraint is not the bottleneck — it is the competitive advantage. The flagship is the destination. The XT-Class models are the engine that pays for the journey.
Execution
Log.
Verifiable phases of the Introlic architecture. Real-world runtime records mapping our transition from small proofs to high-density models.
Our first real experiment with the Introlic stack. Proof that the protocol compiles, runs, and generates coherent output. The foundation proof that the architecture is viable.
Why 220M, not 100M–150M?
Below 150M, a model is too small to surface meaningful emergent behaviors. At 220M, we learn denoising stability, memory pressure under load, and true inference dynamics — the highest-knowledge threshold we can reach within current resource constraints.
Model Taxonomy
XT-Class
220M — 7B Parameters
The Inference Pioneers. While we seek matching long-term funding, we build with what we have. Currently funded completely by MR.FAIZ, revenue and validation data from XT models directly fuel the path to the ARC One flagship.
ARC One-Class
390B Parameters — Flagship
The Cognitive Peak. ARC One is the destination that every XT-Class milestone builds toward. A 390B parameter sovereign Diffusion LLM. When we arrive, it will not just be large. It will be the most efficient large model built from a native engineering foundation.
The Route to 390B.
Each component in the XT-Class unlocks capital, computing resources, and vital infrastructure telemetry. This is not a random sequence of models. This is a deliberate, force-multiplying path to the ARC One-Class flagship.
Common
Queries.
Architecture questions, strategic clarifications, and technical briefings. Answered without hedging.
Have a question not answered here? Contact the command directly.
THE PATH TO
390B STARTS HERE.
Join the internal tier of producers. Early access to the XT-Class backbone starts soon. Secure your authentication vector today.