Generative AI chat

Trusted AI and robotics for high-compliance space deployments

Multi-year deployment with the Australian Space Agency

aKin's intelligent assistants combine a deeper level of understanding with reasoning capabilities to support complex tasks, and to help people make more objective, informed, and responsible decisions.


Inspector understands what is happening in the environment, identifies anomalies, creates alerts, and performs AI Analytics. Inspector’s embodiment is a swarm of smaller robots with sensors.


Manager is an ambient AI brain, with an overarching view of the whole environment. It understands people, processes, events and the habitat as a whole system. Manager is embodied in a ‘brain’ represented by an abstract avatar.

An AI assistant that’s able to intuit human emotion and respond with empathy could be exactly what’s needed, particularly on future missions to Mars and beyond. The idea is that it could anticipate the needs of the crew and intervene if their mental health seems at risk.”
MIT Technology Review (2020)

Collaboration with Australian Space Agency, using proprietary aKin AI

Manage Habitat and Environment as a Complex System

Managing Space Habitats

Current AIs are unable to manage complex systems, let alone those with high risk factors - space habitats.

Today, they only perform linear tasks like scheduling and resource optimization. 

Habitats are complex systems. They have dynamic feedback loops, shifting variables, and nebulous goals. They have multiple humans in varying states of emotional and functional capacity,  each with tasks to do, and resources to manage. 

aKin's wave 3 AI has been embodied in PAL (Like Kubrik’s HAL 9000, except trustworthy), a habitat and environmental manager for NASA’s JPL, with dual-use as aKin Pixi, a household manager which is in scale-up with the Australian Federal Government funding support for disability, aged care and primary caregiver applications.

Australian Space Agency

Crew wellbeing & social support

aKin wave 3 AI  stack has enabled generative chat AI to truly empathize with humans and crew members.

Chat-bots today have either a social function (entertainment, Q&A or search bots) or task performance function (“turn on the lights”). In both cases these are single-turn, and human-driven with prompt-driven output, rather than a true reciprocal relationship. Using breakthrough AI theory, aKin has successfully modelled human life as a deep river of state, with the human persona (emotional state, values, drivers) as the underlying current, and a ‘mental model’ or event trajectory as the undercurrent driving decision making. Inputs and output are not the ‘problem to be solved,” they are mere clues to this state river. This means aKin can function in a low-prompt environment with improved compute and data efficiency.

Generative AI chat

Personal AI for complex tasks

For the first time, our Personal AI allows complex task support for human-robot collaboration. In a world-first project, we developed both AI software and hardware for TRL8 task support in space environments. Our in-house capabilities span state of the art computer-vision, generative natural language processing, sensor fusion, embedded systems, human (fatigue, sentiment, pose) analysis and human-machine interaction into one truly vertical platform - all from codebase zero.

Previously robots were constrained to industrial environments, or simple social robots in human domestic environments. Our robots today are aware of the human state, and are able to manage complex iterative tasks.


aKin wins significant space agency grant for ‘AI crew for Space

The Australian Space Agency has awarded a•kin a grant to build helper and inspector robots, and an AI habitat manager.

An emotionally intelligent AI could support astronauts on a trip to Mars

With thanks to the Advanced Manufacturing Growth Centre, aKin will develop a platform to combine robot brain, sensors and hardware.

Robotics adoption matters: combining artificial and natural intelligence

In the last day of the Robotics adoption matters series, Alexander Hadjiivanov discusses the case for AI in human-robot collaboration.