Improve smart-building outcomes with human-response intelligence

Smart-building systems can optimise technical performance, but realised outcomes also depend on how occupants respond to interventions.

EluxEvo is a UK deep-tech SME developing Human Acceptance Intelligence (HAI). Our AI/ML approach combines connected-device and environmental data with human interaction and behavioural signals, learning patterns of comfort, participation and response. HAI is being developed to make these human factors measurable alongside conventional technical and energy data.

We are seeking collaboration with HEMS and BMS providers, building controls and energy-management platforms, smart-device and low-carbon technology providers, and operators of occupied building portfolios where technical optimisation interacts materially with occupant comfort, acceptance or sustained response.

A potential collaboration could explore whether HAI can provide a complementary human-response intelligence layer alongside existing sensing, control and optimisation, helping partners better understand the relationship between technical interventions and their realised outcomes in occupied environments.

What EluxEvo brings

EluxEvo has secured and led Innovate UK grant-funded R&D and participates in Digital Catapult’s Applied AI Growth Programme. Our HAI capability is at TRL 5, progressing towards TRL 6, with development and testing through smart-home environments and pilots.

We bring:

• AI/ML combining connected-device, environmental and human-response data.

• Experience developing and testing technology at the interface between occupants, connected devices and building conditions.

• A developing human-response intelligence layer intended to complement rather than replace HEMS, BMS, controls and existing building optimisation.

• Experience of collaborative, grant-funded innovation.

What we are looking for

We are particularly interested in partners with existing HEMS, BMS, controls, low-carbon technology or building-optimisation capabilities and a defined deployment challenge. Relevant environments could include residential portfolios, smart and commercial buildings and public estates where there is access to relevant building systems, data and users.

Complementary consortium expertise

We also welcome conversations with specialist technology and research partners where complementary AI/ML, probabilistic modelling, optimisation, human-AI interaction or validation expertise can materially strengthen the deployment and evidence pathway.

Potential BridgeAI pathway

We are seeking partners for the current BridgeAI Deployment Catalyst opportunity, with the appropriate strand determined by the real-world challenge:

• AI for Operational Systems: where HAI could inform or enhance optimisation or operation of energy, comfort or building interventions.

• AI for Decision Critical Systems: where human-response intelligence could provide additional evidence for consequential decisions about whether, when or how an intervention should be deployed or adapted.

• AI for Assurance and Compliance: potentially relevant where a partner has a defined requirement against which building, intervention or human-response outcomes need to be monitored, validated or evidenced.

The project is at design stage:

We have defined the HAI capability and deployment hypothesis and are seeking partners to co-design the specific use case, integration and validation approach around a genuine operational challenge. The resulting challenge would determine the most appropriate BridgeAI Deployment Catalyst strand.