AI Impact Summit

Global AI Impact Commons

Barb

Australia flag

Australia

Public Sector

Implementing Organisation

Kindship

Australia, Australia

Civil Society

Implementing Point of Contact

Unknown

Contributor of the Impact Story

Australia

Year of implementation

2026

Problem statement

Barb is trying to solve for fast and accessible disability support planning for families across Australia.

Impact story details

Kindship has developed an AI-powered National Disability Insurance Scheme (NDIS) navigator that acts as a virtual assistant named Barb, using machine learning and natural language processing to provide personalised support including budget optimisation, plan interpretation, provider recommendations, and 24/7 assistance. For privacy and compliance, all data is stored locally on the user’s device.

AI Technology Used

Machine Learning
Natural Language Processing

Key Outcomes

Narrative Outcome

Barb simplifies disability support planning for Australian families navigating the National Disability Insurance Scheme (NDIS). The platform generates complex career impact statements in 30 seconds, a process that typically takes weeks manually. Barb is claimable under the NDIS and supports hundreds of families, reducing administrative burden.

Impact Metrics

Number of Families being supported by Barb

Baseline Value

0

Post-Implementation

Barb is claimable under the National Disability Insurance Scheme (NDIS) and is supporting hundreds of families across Australia, illustrating the role of AI in simplifying and improving disability support planning.

Speed at which Barb Generates Carer Impact Statements, which are letters written by those who care for disabled persons as part of NDIS applications

Baseline Value

This process typically takes weeks when done manually

Post-Implementation

Barb can generate complex carer impact statements in 30 seconds

Implementation Context

Deployed

Australia

Key Partnerships

Replicability & Adaptation

Not specified

* The data presented is self-reported by the respective organisations. Readers should consult the original sources for further details.