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Myrtle Software Limited

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Our expertise in compressing recurrent neural networks allows us to do more at the edge today. Re-configurable to future-proof your designs for whatever AI may come tomorrow.

CRN
04978210
Founded
2003
Age
22

Overview

Legal name
MYRTLE SOFTWARE LIMITED
Region
East of England
Registered address
THIRD FLOOR ST. ANDREWS HOUSE
59 ST. ANDREWS STREET
CAMBRIDGE
ENGLAND
CB2 3BZ
Insolvency history
No

Company events

Reference milestones and recent Companies House filing stream events.

11 events
11 Dec
2026

Confirmation statement due

Confirmation Due

Next confirmation statement due date

30 Sep
2026

Accounts due

Accounts Due

Next accounts due date

27 Nov
2025

Confirmation statement filed

Confirmation

Last confirmation statement made up date

31 Dec
2024

Accounts filed

Accounts

Last accounts made up date

22 Nov
2024

Appoint Person Secretary Company With Name Date

Officers

AP03 | Transaction MzQ0NDU3NjU4OGFkaXF6a2N4

Published 22 Nov 2024 10:48

22 Nov
2024

Termination Secretary Company With Name Termination Date

Officers

TM02 | Transaction MzQ0NDU3NjIwM2FkaXF6a2N4

Published 22 Nov 2024 10:45

01 Nov
2024

Capital Allotment Shares

Capital

SH01 | Transaction MzQ0MTc0Nzk3MmFkaXF6a2N4

Published 01 Nov 2024 12:09

01 Nov
2024

Capital Allotment Shares

Capital

SH01 | Transaction MzQ0MTc0NjM5N2FkaXF6a2N4

Published 01 Nov 2024 12:00

01 Nov
2024

Capital Allotment Shares

Capital

SH01 | Transaction MzQ0MTc1NjA0OGFkaXF6a2N4

Published 01 Nov 2024 02:21

17 Sep
2024

Accounts With Accounts Type Total Exemption Full

Accounts Analysed

AA | Transaction MzQzNjE5MTUwM2FkaXF6a2N4

Published 17 Sep 2024 10:47

27 Nov
2003

Incorporated

Inception

Company registered at Companies House

Public funding

10 awards
First funded
2013
Funded years
2013, 2016, 2017, 2018, 2019, 2020, 2025
Age at first award
9 years

Projects

2025 Innovation Loans Lead participant

Efficient Secure LLMs

16 Jul 2025 to 16 Jan 2027

Awarded
£1,333,896
Total cost £1,333,896

This project seeks a loan to assist the applicant in commercializing a low latency AI inference accelerator for devices that are present in many edge devices and pieces of critical infrastructure e.g. telecoms base stations

2020 Feasibility Studies Lead participant

CORTEX - Continuity Grant

1 Jun 2020 to 30 Nov 2020

Awarded
£65,295
Total cost £106,500

no public description

2019 Collaborative R&D Lead participant

LEO Satellite Based AI Demonstrator

1 Apr 2019 to 30 Sep 2021

Awarded
£561,558
Total cost £802,225

Satellites typically have limited computing power, in part because they are solar powered and because their rigorous testing schedules and inaccessible operating location demands reliable, time proven technology, often several generations behind current state of the art devices we are familiar with. Our project aims to automatically produce a deep learnin...

2019 Collaborative R&D

COgnitive REal time SENsing SystEm for autonomous vehicles- Cognitive real time sensing system for autonomous vehicles - CORTEX

1 Mar 2019 to 31 Mar 2022

Awarded
£636,810
Total cost £909,728

In 2016 many people were predicting fully autonomous cars within 5 years. After initial quick progress, their recent development has slowed significantly. The market is now adjusting to the new, slower rate of development. This has been seen in more measured predictions from manufacturers and experts, with some companies rolling back on autonomy plans and...

2018 Collaborative R&D Lead participant

Silicon Designs for Core Autonomy Algorithms (SiDeCAA)

1 Apr 2018 to 30 Sep 2019

Awarded
£258,166
Total cost £368,809

"Affordable, vehicle-mounted cameras are an effective way to access high quality image data from a vehicle's surroundings. However, this data contains no information about vehicles, cyclists, pedestrians, traffic signs or road markings. We have to deduce this higher level information from the images using software, which must run in real time to keep up w...

2017 Feasibility Studies Lead participant

AI Object Detection Hardware for Space and Polar Region Exploration

1 Dec 2017 to 31 May 2018

Awarded
£69,159
Total cost £98,799

Artificial Intelligence, or AI, algorithms are becoming ever more powerful - improving speech recognition, providing driving assistance and even recommending movies and music. To take these algorithms into environments where conditions are extreme, and both power and human intervention are limited, requires that they run as power efficient robust hardware...

2017 Collaborative R&D

Smart ADAS Verification and Validation Methodology (SAVVY)

1 Jul 2017 to 31 Dec 2019

Awarded
£108,936
Total cost £155,623

There is an emerging and strong demand for new techniques to enable the robust design and verification & validation (V&V) of ADAS features in a safe, repeatable, controlled and scientifically rigorous environment. This is driven by a number of challenges: reduced engagement of, and reliance on, the driver in the driving task; the very high number and comp...

2017 Collaborative R&D Lead participant

Efficient Deep Learning Hardware for Robotics and Autonomous Systems

1 Mar 2017 to 30 Nov 2017

Awarded
£69,159
Total cost £98,799

There is a wide consensus that deep learning algorithms are key to the future of smart autonomous machines and robots. This project aims to automate the production of low power, lightweight hardware implementing these algorithms so that RAS applications become a reality.

2016 Feasibility Studies Lead participant

Efficient Computer Vision ADAS Hardware for Connected and Autonomous Vechicles

1 Feb 2016 to 31 Jan 2017

Awarded
£147,147
Total cost £210,211

Bringing the next generation of Advanced Driver Assistance Systems (ADAS) hardware to automobiles is complex, expensive, iterative and slow. Development and rollout in the marketplace is further slowed by the high standards naturally required by the car industry. A major consequence of this situation is that advanced computer vision algorithms, which are ...

2013 GRD Development of Prototype Lead participant

Myrtle Software: Project Aurora

1 Jul 2013 to 30 Jun 2015

Awarded
£151,199
Total cost £336,821

The worst insult for effects in movies is that they 'look like a computer game'. But why do games look like games and most movies don't? The use of real-time computer generated images is spread widely across many industries from medical imaging to internet games. All these industries lag behind Hollywood in the authenticity and quality of their images. On...

Product types

Collaborative R&D Feasibility Studies GRD Development of Prototype Innovation Loans