In a market where almost every technology vendor is racing to slap the letters “AI” on a product sheet, one health software company is trying to stand out by promising the exact opposite. Simplifi is courting Australian healthcare providers with a deliberately contrarian pitch: it will not use artificial intelligence in its products, and it wants buyers to see that as a feature rather than a limitation.
The positioning, reported this week by Pulse+IT News, cuts sharply against the grain of a health sector that has spent the past two years chasing generative AI for everything from clinical note-taking to triage and administrative workloads. Simplifi’s bet is that a meaningful slice of the market is quietly uneasy about all of it, and would rather buy software that behaves the same way every single time.
The news
Simplifi’s argument, as put to Australian providers, is built around a single word: deterministic. Traditional software follows fixed rules. Feed it the same inputs and it returns the same outputs, every time, and a human can in principle trace exactly why. Generative AI models do not work that way. They are probabilistic, which means the same prompt can produce different answers, and the reasoning behind any given output is difficult to fully audit.
For a clinic manager or a health service weighing up a purchase, Simplifi’s message is that predictability is worth paying for, particularly when the stakes involve patient records, medication data or clinical decision support. The company is framing its refusal to embed AI not as a technology gap it has failed to close, but as a trust proposition it has chosen on purpose. In effect, it is asking buyers a pointed question: do you actually want a system that might behave differently tomorrow than it did today?
It is a striking piece of counter-programming. Where rivals lead with demos of chatbots summarising patient histories or drafting referral letters, Simplifi is leading with the promise that nothing in its software will hallucinate, drift or surprise you.
Why it might land in health
Healthcare is arguably the sector where this pitch has the best chance of resonating. Clinicians and administrators operate under heavy medico-legal and privacy obligations, and the tolerance for unexplained error is close to zero. The now well-documented tendency of large language models to “hallucinate”, to generate confident but false information, is a genuine liability when the output touches a patient.
There is also a growing body of caution from within the profession. Concerns about AI-generated clinical documentation, the difficulty of validating models against real-world safety standards, and the question of who is liable when an algorithm gets it wrong have all made health a harder sell for AI-first vendors than, say, marketing or logistics. A product that promises “no AI, no surprises” speaks directly to that anxiety.
Simplifi is essentially wagering that some buyers have quietly reached AI fatigue: tired of being told every tool now needs a copilot, and wary of features they cannot fully control or explain to a regulator. For risk-averse decision-makers, “boring and predictable” can be a powerful sales line.
The counterargument
AI-first vendors would say Simplifi is fighting the last war. Their case is that AI in health is not a gimmick but a response to a real crisis: overworked clinicians, ballooning administrative burden and workforce shortages that show no sign of easing. Ambient scribing tools that draft notes from a consultation, systems that flag drug interactions or triage inbound messages, and models that surface patterns in large datasets are already saving time and, proponents argue, catching things humans miss.
From that camp, a blanket refusal to use AI looks less like principled caution and more like a vendor locking its customers out of the biggest productivity shift in a generation. The better answer, they contend, is not to shun the technology but to deploy it responsibly: keep a human in the loop, constrain the model to narrow tasks, log every output and build in guardrails. Determinism, they would add, is not the same as safety. Plenty of rules-based software has shipped dangerous bugs, and plenty of AI systems are carefully bounded.
The honest middle ground is that both sides are describing real risks. AI can hallucinate; legacy software can fail silently. The question for buyers is which failure mode they are better equipped to detect and manage.
What it means for Australia
For Australian health providers, this debate is landing at a pointed moment. The sector is midway through a long digitisation push, from My Health Record reforms to electronic medical records rollouts across state hospital systems, and privacy remains a raw nerve after a run of high-profile data breaches in recent years. The Therapeutic Goods Administration has been sharpening its thinking on how AI-enabled medical software is regulated, and clinical bodies have urged caution on tools that touch patient care without clear evidence and accountability.
In that environment, Simplifi’s pitch could find willing ears among smaller clinics, allied health practices and conservative health services that lack the in-house expertise to vet and govern AI systems and would rather not carry the risk. For a practice manager who cannot afford a data science team, “we simply do not use AI” is an easy story to tell a board or a privacy officer.
The flip side is that Australia’s health system is under acute workforce and cost pressure, and governments at every level are actively encouraging productivity gains from digital tools. A vendor that rules out AI entirely may struggle to compete on efficiency as rivals automate more of the administrative grind. The likely outcome is segmentation: some buyers will pay a premium for predictability, while others chase the time savings, and both markets will coexist.
What’s next
The real test is whether “shun AI” is a durable strategy or a marketing window that closes as the technology matures and regulation catches up. If AI health tools accumulate a track record of safe, auditable use, the deterministic pitch may narrow to a niche. If the sector instead sees a run of AI-related failures, privacy incidents or regulatory crackdowns, Simplifi could look prescient.
Either way, the company has done something useful for the broader conversation. By making refusal an explicit product decision rather than a quiet default, it has forced a question the rest of the industry tends to skate past: not whether you can add AI to health software, but whether, in a given use case, you should. Australian buyers now get to answer it for themselves.
Sources: Pulse+IT News.
