Sciloop

TL;DR: We’re making the AI that does your research for you. Book a call.

Hi.

We’re building Sciloop, a platform that automates the entire scientific research loop from hypothesis generation to experiment design, execution, analysis, iteration, and drafting real research papers.

https://youtu.be/GNM8iA6p9Ao

Our Story:

We’re Bilal and Osman, IPhO medalists and former MIT students with 4 years of experience applying ML in various research domains. While working at MIT CSAIL, we saw how large language models could help with literature review and even generate new hypotheses. Stanford’s recent study (Can LLMs Generate Novel Research Ideas?)  showed that LLM-generated hypotheses can be more novel than those from domain experts. We saw the same in our own work.

But after generating ideas, everything slowed down. We spent hours designing experiments, writing code, debugging compute setups, and rerunning failed jobs that could crash after 12 hours. Even with tools like Cursor that helped us code faster, the overall loop from idea to insight was still painfully manual. Researchers everywhere face this same bottleneck.

So we asked ourselves: what if the research loop itself could be automated?

So we built Sciloop. It takes a research intent — a question or hypothesis — and automatically designs, runs, and monitors experiments in parallel on our own managed cloud compute. It tracks metrics, analyzes results, recommends next steps, and finally drafts a paper summarizing methods and findings. Sciloop turns days of busywork into hours of progress.

Our goal is simple: to completely automate scientific discovery. The next decade will see a century of progress packed into a few years. As AI grows smarter and more accessible, its biggest impact will be speeding up science — finding new cures, discovering better materials, and driving breakthroughs in physics and math.

That’s our north star. But we’re not waiting for the future. We’re helping ML researchers move faster right now, automating the parts of their workflow that slow them down most. Sciloop is already being used in MIT research groups and by early partners working on real ML problems.

If you’re a company, research lab, or ML team struggling with model performance, experimentation speed, or scaling research, we’d love to work with you. Our goal is to deliver concrete improvements on your research challenges today.

🚀 The Ask - Let’s Make Research Self-Improving!

If you’re working on ML research that could move faster, book a quick chat at https://calendly.com/osman-sciloop/30min or email us at team@sciloop.dev.

We help brilliant research ideas stop gathering dust. This is for anyone who:

• Runs university or industry ML labs drowning in experiments.
• Is a research student buried under mountains of code and papers.
• Leads a company dreaming of R&D but lacking scientists or resources.
• Has a head full of creative ideas but no time to bring them to life.

Let’s collaborate and accelerate your research—together.

[1] Can LLMs Generate Novel Research Ideas? A Large-Scale Human Study with 100+ NLP Researchers