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| Feature | ||
|---|---|---|
| Rating |
4.0
|
3.9
|
| Reviews | 9 | 11 |
| Category | Biotech | Biotech |
| Description |
We are building the next generation of deep-learning models for enzyme design to slash the cost of chemical manufacturing. The $6 trillion chemical industry is flawed: It produces 20% of industrial greenhouse gases, and is responsible for 15% of global energy usage. Enzymes offer a far more sustainable alternative to chemical synthesis and have already revolutionised how a select few chemicals are produced. The problem is each enzyme takes years of trial and error to develop. Our enzyme models learn the principles of catalysis, allowing us to design enzymes for each reaction, in days not years. We currently have $4.3M of LOIs and have completed our first $20k contract. |
Reticular helps pharma companies discover drugs with AI models like AlphaFold by making them steerable, just like you can prompt LLMs. Today, limited validation data means companies spend millions on failed experiments trying to steer these models through trial and error. We’re piloting our AI interpretability technology with early-stage biotechs and scaling rapidly. Just a week after our pivot, we identified the first interpretable features ever found in protein models, allowing precise control over biological functions. Nithin and John met competing in Biology Olympiads before spending 4 years as roommates at MIT publishing ML/bio research in NeurIPS and Nature. We believe biological models encode far more information than anyone is currently using - our goal is to unlock this potential. |
| Website | https://www.ligo.bio | https://reticular.ai |
| Positives |
"Fast, reliable, and constantly improving. Great product!"
Reba Mueller - 5/5
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"Saves us hours every week. Highly recommended!"
Mr. Chauncey Veum Jr. - 5/5
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| Negatives |
"Integration was difficult and documentation was unclear."
Newton Moore - 1/5
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"Had some issues with reliability and uptime."
Allan Adams - 2/5
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| Details | View Full Review → | View Full Review → |