About my Start-up
We are an industrial biotech software company. Combining our chemical engineering and biotechnology background with an innovative artificial intelligence and software specialization, we offer the next generation software platforms, for designing new processes on industrial scale estimating the detailed TEA and LCA from initial TRLs, and for optimizing existing processes by creating digital twins of them.
Connected to our process simulation tool, the platform integrates a marketplace of (bio)waste providers, which allows companies to find potential partners to use their waste as a raw material, estimating its techno-economic viability through our easy-to-use platform. Our mission is to encourage companies to become circular, by giving a digital tool that estimates its economic and environmental impact.
Why your idea is a “winner"?:
Unlike conventional process simulators like Aspen Plus, in which the user has to introduce a lot of configurations and process parameters to obtain results, we integrated reinforcement learning in our platform, which means a self-thinking support system that provides data-driven recommendations to the user, making it very user-friendly and affordable for everyone who has a basic understanding of (bio)chemistry.
What is your current or intended business/revenue model?:
Our business model is B2B, we sell to companies, and our product is a SaaS (Software as a Service). We offer flexible monthly licenses for using our platform, which may be canceled at any time.
Do you have any Patent or IP registered (related to the solution that you are looking for an investment)?:
We are IP pending.
Has your technology already been implemented in any field/sector?:
Not really. Our key enabling technology is called "reinforcement learning" which is a recent type of artificial intelligence that learns from simulations, to solve complex problems. This has been implemented in fields like video-games or new drug design, where lots of data can be obtained through simulations. But has not been yet implemented to new process design, due to the complexity of coupling both worlds.
Which market and customer need(s)/problem(s) is (are) your products(s)/service(s) going to solve?:
Biotech companies have lots of uncertainity when scaling up. While they are very focused on enzyme optimization and their process in the lab, they sometimes loose the long term objective: Producing their products on a commercial scale, and they don't have any digital tool to estimate detailed investment and operational costs from initial stages. These companies spend months or years deciding which technologies they should use, which raw material providers choose, which will be their by-products or waste, and which will be the minimum selling price of their product, to see if they can compete with petrochemistry.
Currently, the only solution they have is to contract an engineering company, where a whole group of chemical engineers spend months performing the study, design, optimization and analysis of their process. Not only is it an expensive and lenghty process, but they have no flexibility to evaluate different options, technologies or raw materials providers, and most times results are sub-optimal.
We help companies reduce that lenghty process by offering a digital platform that automates that design, optimization and study, giving them a detailed estimated CAPEX, OPEX and LCA from initial stages.
Team members
Chemical engineer, with experience managing teams for data science projects. She has participated in projects related to water quality, data science, machine learning, etc…
Emanuel is a software engineer with deep experience in software development. He has worked in different companies as a full stack developer, and he is also passionated about technology and AI.
Sergi is a web developer, with a Master’s and experience in HH.RR which makes him a very interesting profile for not only developing the product, but to hire new talent.
Chemical engineer with a posgraduate in artificial intelligence with deep learning. Albert has experience in the chemical industry working mainly in pharmaceutical companies. His research is focused in applying reinforcement learning in new chemical process design. He founded Intemic to democratize this technology, offering it to companies as a Saas.
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