Decision-Making AI For The Enterprise

InstaDeep delivers AI-powered decision-making systems for the Enterprise. With expertise in both machine intelligence research and concrete business deployments, we provide a competitive advantage to our customers in an AI-first world.

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Building AI systems for the industry

Leveraging its expertise in GPU-accelerated computing, deep learning and reinforcement learning, InstaDeep has built AI systems to tackle the most complex challenges across a range of industries and sectors.

Biology Biology


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Logistics Logistics


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Electronic Design Electronic Design

Electronic Design

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Energy Energy


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Our latest updates from across our channels

InstaDeep Raises $100M to Scale Decision-Making AI Products that Solve Real-World Problems

InstaDeep Raises $100M to Scale Decision-Making AI Products that ...

on Jan 25, 2022 | 12:05pm

Series B led by Alpha Intelligence Capital; BioNTech and Deutsche Bahn among Investors  LONDON (JAN 25, 2022) – InstaDeep, a leader in advanced AI decision-making sy...

InstaDeep and Oxford University Research Collaboration Accepted t...

on Jan 24, 2022 | 07:31pm

This research was authored by Scott Cameron at the University of Oxford and InstaDeep, in collaboration with Prof Stephen Roberts, Dr Arnu Pretorius of InstaDeep and Tyron Cameron...

BioNTech and InstaDeep Developed and Successfully Tested Early Wa...

on Jan 11, 2022 | 12:43pm

Early Warning System combines Spike protein structural modeling with artificial intelligence (AI) to detect and monitor high-risk SARS-CoV-2 variants, identifying >90% of WHO-d...

An early detection system for desert locust outbreaks in Africa, ...

on Dec 13, 2021 | 09:15am

Our collaboration with Google AI, “On pseudo-absence generation and machine learning for locust breeding ground prediction in Africa”, describes an early detection system for...

InstaDeep announces three workshop papers accepted at NeurIPS2021...

on Dec 07, 2021 | 07:43am

InstaDeep today announces that it has had three papers accepted for presentation at the 2021 Annual Conference on Neural Information Processing Systems (NeurIPS 2021), including o...

InstaDeep attending GDG Sousse and GDG Beja DevFests...

on Dec 03, 2021 | 08:00am

InstaDeep is pleased to continue its partnership with the Google Developers Group (GDG) and their popular programme of Developers Festivals (DevFests).  This December, the co...

InstaDeep co-founder speaks on “Promoting Female Talent” pane...

on Nov 26, 2021 | 11:45am

InstaDeep’s co-founder and CWO, Zohra Slim, attended the closing ceremony of the 3rd edition of the “Promoting Female Talent” career development program that took place at t...

InstaDeep supports GDG Algiers DevFest...

on Nov 17, 2021 | 01:26pm

InstaDeep is pleased to announce its involvement in the GDG Algiers DevFest, happening simultaneously online and at the offices of another locally-based sponsor, Altius Services,...

InstaDeep’s DeepChain platform showcased at 2021 Festival o...

on Nov 12, 2021 | 02:12pm

InstaDeep was a proud Platinum Sponsor of the recent Festival of Biologics, held from the 9th to the 11th November 2021 in Basel, Switzerland, where it exhibited the company’s A...

InstaDeep presents our DeepPack product for complex load optimisa...

on Nov 08, 2021 | 09:30am

Following on from the company’s record four contributions to NVIDIA’s Spring GTC, InstaDeep is delighted to be participating in the global Autumn event with a presentation on...


Causal Multi-Agent Reinforcement Learning: Review and Open Problems

S.J. Grimbly | J. Shock | A. Pretorius

NeurIPS Nov 2021

On pseudo-absence generation and machine learning for locust breeding ground prediction in Africa

I.S. Yusuf | K. Tessera | T. Tumiel | S. Nevo | A. Pretorius

NeurIPS Nov 2021

One Step at a Time: Pros and Cons of Multi-Step Meta-Gradient Reinforcement Learning

C. Bonnet | P. Caron | T. Barrett | I. Davies | A. Laterre

NeurIPS Oct 2021

Mava: A new Framework for Distributed Multi-Agent Reinforcement Learning

A. Pretorius | K. Tessera | A.P. Smit | C. Formanek | S.J. Grimbly | K. Eloff | S. Danisa | L. Francis | J. Shock | H. Kamper | W. Brink | H. Engelbrecht | A. Laterre | K. Beguir

Jul 2021

Scaling Properties of Deep Residual Networks

A-S. Cohen | R. Cont | A. Rossier | R. Xu

ICML May 2021

Designing a Prospective COVID-19 Therapeutic with Reinforcement Learning

M. J. Skwark | N. L. Carranza | T. Pierrot | J. Phillips | S. Said | A. Laterre | A. Kerkeni | U. Sahin | K. Beguir

NeurIPS Dec 2020

In the Press