Lotus Assist is a Gold Coast and Brisbane-based NDIS provider founded by Helen and Nicole Marquez. Like most providers in the space, Lotus Assist was built around a simple mission: delivering high-quality, person-centred support to NDIS participants.
Anthony Marquez managed the technology behind the organisation — setting up systems, building automations, and trying to make the tools actually work for the practitioners who depended on them. What he saw from that seat was how much of the team's time was being consumed by paperwork.
The Challenge
By 2024, Lotus Assist had a growing team of support coordinators and practitioners — and a documentation burden that scaled with every new participant. Progress notes, service agreements, support plans, incident reports: the volume was relentless.
The team started experimenting with AI tools to see if they could reduce the time spent writing. The results were promising — until they looked more carefully at what was actually happening with the data.
"We were pasting participant information into these tools without really thinking about where it was going," Anthony recalls. "When we actually looked into it, we realised we were sending sensitive participant data to servers overseas. That's not something we could continue doing."
The compliance concern was real. NDIS participants had shared deeply personal information — diagnoses, behaviours, family circumstances — with Lotus Assist in a context of trust. Sending that information to a US-based AI platform, with no guarantees about how it was stored or used, wasn't acceptable.
But going back to manual documentation wasn't acceptable either. The efficiency gap was too significant.
The Solution
LAIT AI was developed out of this exact problem — initially to solve it for Lotus Assist, and then built into a platform that other NDIS providers could use.
The core requirements were non-negotiable from the start:
Australian data hosting. All data stays in Australia, on AWS infrastructure in the Sydney region. Participant information never crosses international borders.
Private, isolated instances. Each organisation runs on its own environment. Lotus Assist's data is completely separate from any other LAIT customer's data — there's no shared pool, no co-mingling.
No training on customer data. The AI model is never trained on participant information. Notes stay notes; they don't become training examples.
NDIS-specific workflows. General-purpose AI tools require significant prompting to produce documentation that matches NDIS conventions. LAIT was built with NDIS documentation patterns in mind from day one.
The compliance team at Lotus Assist reviewed the infrastructure and data handling approach before the organisation committed to using it. That review was what made adoption possible — the team needed to be confident, not just comfortable.
The Results
Since adopting LAIT AI, Lotus Assist has seen meaningful improvements in documentation efficiency across the team.
Practitioners are spending less time on writing and more time on direct support work. The documentation that does get produced is more consistent — AI-assisted drafts follow a structure that's easier to review and finalise than documents built from scratch.
The team reports that tasks which previously required extended writing sessions — progress notes, incident reports, plan review summaries — now take a fraction of the time. The AI drafts provide a strong starting point that practitioners refine rather than build from scratch.
What Made the Difference
Three things stand out when Anthony reflects on why LAIT AI worked where other tools hadn't.
The compliance team was comfortable. This might sound like a low bar, but it's not. Most AI tools fail at this step for NDIS providers. The ability to point to Australian hosting, per-org isolation, and no training on customer data was what got the green light internally.
Data sovereignty was guaranteed, not promised. There's a difference between a platform that says "we care about privacy" and one that can show you where your data lives and how it's isolated. LAIT could show the infrastructure. That matters.
It was built for NDIS workflows. A general AI tool can produce NDIS documentation if you prompt it carefully. But "prompt it carefully" means training staff, writing guides, and managing inconsistency. A tool that understands NDIS documentation patterns out of the box reduces that overhead significantly.
See LAIT AI in action
Book a personalised demo and discover how LAIT AI keeps your organisation's data private.
For NDIS providers looking to adopt AI responsibly, the Lotus Assist experience points to a clear path: the privacy and compliance requirements aren't obstacles to work around — they're the starting point for evaluating any AI tool.
Learn more about LAIT AI and how we built the platform, or book a demo to see it working with NDIS documentation workflows.
NDIS AI Privacy Guide
Download our guide on using AI safely in NDIS environments — covering data privacy, compliance, and best practices.