Sovereign STEM Intelligence.
Open Science & Enterprise AI.
ExperimentLab pioneers sovereign small language models, sparse MoE architectures, and neuro-symbolic reasoning engines for mathematics, semiconductor hardware, and computational physics. Open for peer collaboration with global researchers and on-premise deployment for institutions.
Open Science & Private Enterprise
ExperimentLab operates at the intersection of open academic research and mission-critical sovereign deployment. Select your track below to explore collaboration pathways.
Pioneering Sovereign STEM Intelligence
We invite researchers, universities, PhD scholars, and labs worldwide to collaborate on our open sovereign models, peer-reviewed whitepapers, and verifiable evaluation engines.
Tensor mechanics, orbital kinematics, relativistic calculations, and differential physics simulations fine-tuned on verified academic corpora.
Hardware description language synthesis (Verilog HDL), timing closure validation, CMOS cell layout automation, and digital logic verification.
Coupling neural policies with SymPy computer algebra systems for verifiable step-by-step higher calculus, number theory, and Olympiad problem solving.
Biochemical reaction pathways, molecular graph embeddings, pharmacokinetic properties, and biomedical literature synthesis.
High-entropy statutory legal reasoning taxonomy across Bharatiya Nyaya Sanhita (BNS 2023), BNSS 2023, SARFAESI, and constitutional property law.
We offer academic researchers direct access to pre-training checkpoints, dual-GPU training scripts, and co-authorship on the Vigyan research series.
Private Intelligence On Your Hardware
Full on-premise installation for EdTech platforms, engineering software, and regulated defense institutions. Pull the network cable — it keeps answering.
Installed directly onto servers inside your building or air-gapped private clusters. Zero third-party telemetry, zero cloud calls, zero data leaks.
You own the fine-tuned model weights forever. No monthly user seat license, no per-token billing, and no remote switch we hold.
High-throughput local C++ inference engines designed to embed directly into learning management systems, test-prep suites, or engineering CAD software.
Why Platform Builders Choose Vigyan
Put mathematical and scientific intelligence inside your own product, on your own machines, without shipping your users' questions to a third party.
Answers With Their Working Attached
Every response and its reasoning steps stay in logs on your own machine. When a partner, an auditor, or an examiner asks how an answer was produced, you can show them.
Built To Embed
Step-by-step math and science problem solving inside learning apps, test-prep platforms, or engineering software — fine-tuned on your own syllabus.
Small Enough To Own
High parameter efficiency fits on everyday office servers and laptops you can actually buy. No per-token billing, and no remote key we can switch off.
Open Research & Training Corpora
Published whitepapers, LaTeX sources, and datasets are openly accessible. Download the weights, check the math, and inspect the code.
Vigyan AI Research Papers Series
5 formal peer-reviewed whitepapers covering Sparse MoE upcycling, DUS seam healing, Tool-DPO symbolic grounding, GRPO test-time compute, and Neuro-Symbolic GraphRAG.
shreyansh-1B-SLM-pretrain-stem-english
22.7 million rows of textbooks, open papers, and technical corpora across physics, chemistry, mathematics, and engineering.
shreyansh-hinglish-english-stem-500k
500,000 bilingual STEM problem-solving pairs, formal English working alongside natural Hinglish explanations for learners who think in one and take exams in the other.
The Questions We Would Ask Us
Including the one most vendor pages leave out.
What is Vigyan AI?
A sparse mixture-of-experts math and science model, roughly 1 billion parameters active per token out of 7 billion total, trained on open STEM corpora and installed on hardware you already own. Built for platforms that cannot send their questions to someone else's cloud.
Is Vigyan as good as a frontier cloud model at raw reasoning?
No. It is better at answering inside your building without your data leaving it. A frontier model has more raw reasoning going for it, and every question you type is sent to a company you do not control. We do not publish accuracy figures for Vigyan. We would rather you judge the output on your own material in a test install.
Does it keep working without internet?
Yes. Once installed, the model, its weights and its logs all live on your hardware. Pull the network cable and it still answers. That is the one claim on this page you can check in the room without taking our word for it.
How is Vigyan-7B licensed and deployed?
A fixed-scope license starting from ₹10 Lakh, with 100% perpetual ownership of the fine-tuned weights handed over to you, installed privately on your own servers, and no recurring per-token fees.
What data was Vigyan trained on?
shreyansh-1B-SLM-pretrain-stem-english, a 13.1 GB corpus of 22.7 million rows of physics, chemistry, mathematics and computer science, plus shreyansh-hinglish-english-stem-500k, 500,000 bilingual problem-solving pairs. Both are published and openly inspectable.
How can software platforms embed Vigyan AI?
As an install on your own servers with the full weights handed over, so the system keeps running even if we stop existing. Licensing, custom fine-tuning on your own syllabus, and dedicated private machines are all in scope.
Partner With ExperimentLab
Connect directly with our research engineers in Varanasi — for peer-reviewed academic research collaboration, open dataset access, or sovereign on-premise enterprise deployment.
• 100% on-premise enterprise installation with weights handed over
• Test install on your own material before any commitment