Companies

Bloomsbury AI automates customer care and advice. Our AI reads background documents and any additional information, and then automates answers (with explanations) to customer questions. Questions that the AI can’t answer are passed on to a Human.

The founding team are world experts in Machine Learning and  have over 60 patents and 200 peer reviewed publications.

Guillaume Bouchard completed his PhD in statistics from INRIA. He has 15 years experience at Xerox Research and UCL in machine learning and NLP.

Luis Ulloa is a prize winning research engineer. He created the optimisation and machine learning algorithms and IP behind two of the most profitable projects at Xerox Research.

Calipsa is building a Deep Learning based cloud platform to automate traffic surveillance, monitoring and data collection. Our technology transforms existing IP cameras into smart cameras allowing them to classify what is on the road. Currently, these tasks rely entirely on human operators which is both inefficient and expensive.

Rashid Khan has a Master’s in Machine Learning from the University of Cambridge. Rashid has extensive industrial experience ranging from consulting to tech startups. He has worked at Symantec, Accenture and Wonga over the past five years.

Boris Ploix has a degree in Applied Mathematics from Imperial College. He spent the last 3 years working in the transport industry at the French Ministry of Transport and Transport for London. He worked on several data analytics projects during his time there.

Businesses leak close to 10% in top-line value every year due to poor visibility over internal data, particularly in finance and operations.

inPact processes contracts, invoices and other unstructured documents, using AI to extract and analyze complex commercial terms and provide companies the missing insights needed to plug the value leak.

In a few months, inPact has built a growing clause database and trained NLP models that beat leading contract management software on contract term detection, launched an Alpha version with early adopters, and signed two pilots for working capital optimisation and vendor management.

After graduating from Columbia Law at 21, Jose Sampedro Mazon became a corporate lawyer at global law firm Linklaters in London. Following an MBA at INSEAD, he joined the Boston Consulting Group leading Strategy & Ops transformations at Asian banks as a project leader. He then worked as a business development director at Oracle Cloud.

Dr Siddhartha has a PhD in Computer Science with 10 years of experience working in multiple R&D teams for institutions such as Imperial College London, NTU Singapore, and the University of Sydney. He has extensive experience in various machine learning domains, and in particular, Natural Language Processing (NLP).

LEORIX manages infrastructure for high-frequency data pipelines.

Instead of paying for hundreds of developer hours to build complex custom solutions, companies can be up and running in days. Currently, the back-end stacks of data streaming applications require multiple platforms and a different set
of experts. Businesses today spend $72B per year to build efficient systems.

We designed LEORIX to solve this problem. Now, companies can save time and money because they don’t need to pay specialised developers to build the pipelines from scratch. So far, we have partnered with several leading cloud providers in Southeast Asia.

Thana Kuganesan built and exited his tech startup SparkGrid in Sri Lanka and scaled it from 2 to 15 employees in 2.5 years by bootstrapping as CEO. He is a computer science engineer from the University of Moratuwa and was a back-end engineer for robotics and multiplayer game applications for 7 years.

Sri Kuganesan has a Master’s in distributed systems at KTH-Sweden. He has 12 years of industrial experience and is a core member of Hadoop Distributed Platform. He specialises in data streaming and has worked at Spotify and Ericsson for 4 years. He owns 2 provisional patents for data distribution and compression techniques.

MechaniX unlocks the true potential of A.I. with synthetic data generation.

In the world of AI, data is fuel. Lack of datasets is the major development obstacle for deep learning systems due to the extremely high cost involved for the collection and annotation of real-life data.

MechaniX specializes in the generation of synthetic training data. We provide data that’s hard to collect, expensive to label or sometimes even impossible to replicate in real-life. This enables companies to train mission critical AI systems with 20% better sample performance at a lower cost.

By now, we have secured two paid pilots, with a hedge fund and a proprietary trading firm. We are also in early talks with a CTA fund, one of the world’s largest hedge funds and have 4 more LOIs in the pipeline.

Thomas Yue completed his PhD in Computational Physics at University of Nottingham, where he specialised in meshfree numerical simulations. Using simulation skills, he has developed a career in algorithmic trading as a strategist and was the CIO of a Fintech robo-advisor while lecturing at Hong Kong Open University.

Au Chi Chiu (David) has an MSc in Financial Mathematics and Statistics and a BEng in Computer Science both from HKUST. He began his career in Deutsche
bank and worked as a strategist at high frequency trading firm. He has more than a decade of in depth experience in applying machine learning for trading strategies development.

Waste collection is a critical service that every city needs to run daily. But its planning is often done manually, and consequently, collectors may choose inappropriate technologies, longer routes, or simply leave waste uncollected.

Waste Labs runs a proprietary AI platform that enables waste collectors and cities to analyse and improve their collection system. By creating a digital twin of the system, the platform highlights inefficiencies, and suggests improvements, helping to reduce collection costs by 10% – 40%.

The company already counts a global waste collector among their clients.

Vladimir Chuchkin spent 12 years in Business Development across large international Tech and Energy companies. He has worked closely with governments in Asia, Middle East and Africa. He originated and structured Energy and Power Generation projects that are worth over US$10 billion, including those in the waste-to-energy sector.

Dr Elias Willemse is an expert in optimisation modelling and spent 12 years developing AI to optimise waste collection. He holds a PhD in Industrial Engineering, initiated and led funded projects in waste management, and worked with large institutions such as WorleyParsons, OXFAM and the Housing Development Board in Singapore.