Startups

How CYBERTONGUE® Is Taking the Guesswork Out of Dairy Testing

The Canberra biotech startup is helping processors detect spoilage risks before milk reaches the shelf.

Updated

August 13, 2026 1:01 AM

CYBERTONGUE® Food Testing System, developed by PPB Technology. IMAGE: PPB Technology

Anyone who has opened a carton of milk before its expiry date only to find that it smells off or tastes bitter has experienced the problem firsthand. For dairy processors, the same issue can play out across thousands of litres. Milk may pass routine quality checks, make it through production and still spoil before reaching the end of its expected shelf life.  

CYBERTONGUE®, a biosensing platform, is designed to give dairy processors an earlier warning.  

Developed by Canberra-based biotech startup PPB Technology, the compact food testing system allows processors to analyse milk on-site and receive results within minutes. Its first commercial application detects protease, an enzyme linked to spoilage, shorter shelf life and production losses across dairy products.  

Dairy companies already test milk for fat, protein, bacteria, antibiotics and other indicators. Samples from individual farms may be sent to central laboratories, while tanker loads are tested again when they reach processing plants. These checks provide useful information, but they do not always show whether milk will remain stable in a UHT carton, meet a supermarket’s shelf-life requirements or produce the expected amount of cheese.  

Even after heat treatment, protease can continue affecting milk. For processors making UHT milk, fresh milk or mature cheese, that creates a costly blind spot.  

“Right now, dairy processors are working blind on this,” PPB Technology founder Stephen Trowell told Ventureport. “It’s becoming more of a problem as customers expect longer shelf lives and higher quality.”  

CYBERTONGUE® uses engineered biosensing proteins that emit blue and green light. The balance between the two colours changes when the protein reacts with a target substance. The reader measures that shift and calculates how much of the target is present.  

CYBERTONGUE® software displaying the results of a completed raw milk assay. IMAGE: PPB TECHNOLOGY

Trowell describes himself as a protein engineer at heart. He spent around three decades at CSIRO, Australia's national science and technology agency, and close to four decades in research before becoming a startup founder. The technology behind CYBERTONGUE® grew out of years of biological research, including earlier experiments involving wine aromas and explosives detection.

The PPB Technology team with founder Stephen Trowell. IMAGE: PPB TECHNOLOGY

PPB initially developed its technology to measure plasmin, an enzyme derived from cows. After feedback from the dairy industry, the company shifted its focus to bacterial proteases, which were identified as a more pressing spoilage problem. The platform can make some existing tests faster, but PPB chose to focus first on a measurement previously unavailable to processors.  

“Where we’ve chosen to lead is with a measurement nobody else can do at all,” he said. “The blue ocean, if you like.”  

That focused entry point shapes PPB’s wider strategy. CYBERTONGUE® could eventually test for lactose, allergens, microbial toxins and other targets. Yet launching everything at once would stretch a six-person company too far. Protease gives it a clear route into dairy, where the financial value is easier to demonstrate.  

A processor that detects high protease activity may redirect a batch of milk away from long-life products and use it for yoghurt, curd or another product where the enzyme causes less damage. PPB also says its tests can help trace problems in the milk supply and detect biofilms on processing equipment, allowing factories to take corrective cleaning measures.  

Fresh milk presents another sizeable opportunity, with the global market estimated at around US$81 billion in 2026 and projected to grow at 6.83% annually through 2035. At that scale, even small gains in shelf-life consistency could prevent substantial losses. Supermarkets often require milk to have a minimum amount of shelf life remaining on delivery. Products that fall short may be rejected, discounted or discarded at the processor’s expense. While Australian processors typically aim for a shelf life of 19 to 21 days, they do not always achieve it. CYBERTONGUE® could help them reach that target more consistently.  

Cheese producers face a related issue. Protease can create bitter flavours in hard cheeses and reduce production yield. Cheesemakers add another enzyme, chymosin, during production, often without knowing how much protease activity is already present in the milk. Better information could help them adjust the process and get more value from the same raw material.  

PPB sells the reader as laboratory equipment, but its long-term business model centres on repeat testing. Customers buy the machine, then purchase a PPB reagent cartridge each time they run an assay. Future tests are intended to work on the same reader, making the system more useful as the catalogue expands.  

CYBERTONGUE®’s compact design reflects PPB’s focus on practical onsite testing. The device is small enough to fit into two cupped hands and comes with a tablet running PPB’s software.  

An operator inserts a sample into a CYBERTONGUE® testing device during an on-site milk analysis. PHOTO: PPB TECHNOLOGY

At the time of the interview, 13 to 15 systems had been installed with paying customers. PPB had made sales in 11 countries across five continents, with Europe as its largest market.  

Trowell describes PPB as “born global”. While Australia and New Zealand have sophisticated dairy industries, Trowell thinks CYBERTONGUE® may offer even more value in regions where milk quality is less consistent, transport routes are longer or refrigeration is harder to maintain.  

Trowell also believes PPB has a strong competitive moat, with the combination of manufacturing both the hardware and consumable reagents. Patents form one layer, but he does not consider legal protection sufficient on its own. A competitor would need expertise in protein engineering, reagent production, optical hardware, software and dairy processing.  

Calibration adds another barrier. For each new box of reagents, PPB securely uploads the required calibration data to the customer’s machine. A third party could not simply manufacture a cartridge with the same dimensions and expect it to work correctly.  

“We own the whole stack,” Trowell said, referring to everything from the sensing molecule to the hardware, software and cloud platform.  

That said, he accepts that no technology is impossible to copy. His view is that PPB’s mix of scientific knowledge, integrated system and experience in dairy gives it enough of a head start to build a meaningful position before competitors catch up.  

The technology could eventually reach beyond food. Trowell sees possible uses in environmental testing, veterinary care and medical diagnostics, including the analysis of blood, serum or saliva. PPB has already discussed potential applications with organisations outside the food industry.  

For now, however, moving directly into clinical diagnostics would create more risk than opportunity. Medical products can require years of trials, extensive regulatory work and large development budgets. PPB would also need to build new sales channels and choose between many possible clinical uses without knowing which one would attract the strongest demand.  

For these reasons, food testing offers PPB a clearer path. The regulatory barriers are generally lower, customers have immediate operational problems, and PPB has already built relationships in dairy. Once the platform has proved itself commercially, the company could enter other sectors through partnerships or licensing.  

Trowell has held that view for years. The immediate goal is to build a successful food testing company rather than chase the prestige often attached to medical biotechnology.  

The opportunity may also expand as food production becomes more complex. Dairy factories increasingly process oat, soy and other alternatives on equipment that also handles cow’s milk. This creates cross-contamination and allergen risks, offering another potential use for CYBERTONGUE®.  

PPB still has plenty to prove. It must secure repeat reagent orders, convert early trials into wider deployments and expand its test catalogue without compromising accuracy. Scaling an integrated biotech hardware business across international markets will not be simple.  

Still, its approach offers a useful lesson for other deep-tech startups. Instead of beginning with every possible application, PPB picked a specific problem that costs customers money today. It built a product around that pain point, then used the same technology as the foundation for a broader platform.  

As Trowell put it, customers “need it fast, and they need it right.” CYBERTONGUE® is betting that food testing can deliver both.  

Keep Reading

Artificial Intelligence

Meet Diella: Albania’s AI Minister, Its Promise and Its Risks

Not elected, not human—Albania’s AI minister sparks a new governance debate.

Updated

August 10, 2026 5:56 PM

Promotional avatar graphic representing Diella, the Albanian government's artificial intelligence system. PHOTO: EALBANIA

Artificial intelligence already supports a wide range of applications, from medical diagnostics and financial systems to logistics, manufacturing, defence and public service delivery. Now, it is starting to move closer to public office.

In January 2025, Albania introduced Diella, an AI-powered virtual assistant developed by the National Agency for Information Society, known as AKSHI, with support from Microsoft. Launched on the e-Albania platform, the government’s digital services portal, Diella helps citizens and businesses access official documents and services through voice assistance. She can also issue electronically stamped documents, which helps speed up administrative processes.

Then, in September 2025, Prime Minister Edi Rama announced that Diella would join his cabinet as the “Minister of State for Artificial Intelligence”. This move drew global attention. It also raised a simple question: what does it actually mean for a government to appoint an AI minister?  

The case raises bigger questions for governments everywhere. Can an AI minister make public services faster and cleaner? Or does it create new risks around transparency, accountability and control?

Who is Diella, Albania’s AI minister?

Diella is not a humanoid robot sitting in a cabinet room. On screen, she appears as a digitally rendered woman wearing traditional-style Albanian clothing. Her name means “sun” in Albanian, a deliberate choice for a system meant to bring more light into public administration.  

Her face and voice have become part of the controversy. Albanian actor Anila Bisha has said she agreed for her likeness to be used for the e-Albania public services platform, but not for a cabinet-level political role. In 2026, she took legal action to stop the government from using her image and voice for Diella. For now, the government has denied wrongdoing.

What does Diella actually do?

Diella began as a digital assistant on e-Albania. In that role, she helps users find services, request documents and navigate government processes online. For citizens, that can make public services feel less confusing. Businesses may also spend less time dealing with paperwork.

Her cabinet role is more political. The government wants Diella to support public procurement, where companies compete for government contracts. This is one of the most important areas of public spending. It is also one of the easiest places for corruption, favouritism and hidden influence to enter. The goal is to use AI to process information, check documents, support tender procedures and make the system more traceable.  

That said, the government has emphasized that Diella is not replacing elected officials or civil servants. As per Enio Kaso, director of AI at AKSHI, each stage will be monitored and approved by human experts.

In May 2026, the Albanian government said it had completed the technical groundwork for the AI-powered public procurement system under the Diella project. The planned system would pull data from more than 40 digital public registries, reduce paperwork for businesses and support parts of the tender process. Earlier reports said the government hoped to have the full system ready by the end of 2026.

Why Albania wants AI in public procurement

The government’s case for Diella is built around anti-corruption reform. Rama has said the goal is to “wipe out every potential influence on public biddings” and thus make public tenders “100% free of corruption”. That is a bold promise, especially in a country where procurement scandals have long damaged public confidence and complicated Albania’s path toward European Union membership.  

At first glance, the logic is easy to understand. AI does not ask for bribes or favour a cousin—a big problem in the country, according to Rama—a friend or a political ally. It can apply the same rules across a large number of applications. Moreover, it can also leave a digital trail, which should make later review easier.

Some anti-corruption and governance experts see real potential in that approach. Dr. Andi Hoxhaj of King’s College London has said that if used well and programmed properly, AI could help procurement officials spot missing documents, check whether companies meet eligibility requirements and flag unusual patterns in bids. In practice, that could make the process more consistent and make it harder for individual officials to quietly bend rules.

The risks behind AI in government

Diella’s appeal is speed and consistency. Her weakness is dependence.  

Like any AI system, Diella relies on the quality of the data, rules and models behind her. Erjon Curraj, an expert in digital transformation and cybersecurity, has warned that incomplete, outdated or biased data can lead to flawed results. Poor design could also cause the system to reject a valid supplier, miss signs of collusion or treat similar cases differently for reasons that are hard to explain.

In public procurement, those mistakes can have serious consequences. A wrongly flagged company could lose a major contract, and a corrupt bidder could slip through. Government agencies could hide behind the AI and say the system made the recommendation.

That leads to the biggest question: who is accountable when something goes wrong?

The answer cannot be “the AI” because Diella cannot resign. She cannot face voters. Nor can she be cross-examined in any meaningful human sense. Accountability has to sit with ministers, agencies, auditors and courts.

There is also the issue of transparency. If Diella is helping screen tenders, businesses need to know what criteria are being used. They also need a way to challenge incorrect decisions. Citizens should be told whether the AI is making recommendations or merely organizing information. Independent auditors need access to logs, data sources and decision pathways.

Without those safeguards, AI in government can become a black box. It may look modern from the outside, while making power harder to question.

Diella, politics and public trust

Diella has also become a political symbol. Supporters see her as proof that a small country can move quickly and experiment with new forms of digital government. Critics see her as a distraction from deeper problems in Albania’s institutions.

Both readings can be true at the same time: Diella may help modernize public services, but she may also be used to project reform while older problems continue in the background.

That tension became clearer after the recent procurement investigations involving senior officials since Diella’s appointment. Deputy Prime Minister Belinda Balluku has been accused by prosecutors of alleged misconduct linked to infrastructure tenders, which she denies. Senior figures at AKSHI, the agency behind Diella and e-Albania, have also been placed under house arrest as part of a separate public procurement investigation.  

While these developments do not automatically discredit Diella, they may strengthen the argument for better digital oversight. More importantly, they also show that technology cannot carry the whole burden of reform.

If the institutions around an AI system are weak, the AI will not magically make them strong. Unclear procurement rules will still cause problems, and the process will still be compromised when political pressure shapes the data, the model or the final decision.

After all, AI can support integrity; it cannot replace it.

Finding the right balance for AI in government

While Diella is already a public symbol of AI in government, her most important procurement role is still taking shape. This makes Albania’s experiment both ambitious and unfinished.

The more realistic model is simple: let AI handle repetitive, data-heavy administrative work. Let humans retain authority where judgment, context and public accountability matter.  

That means AI can help draft tender criteria, check documents, summarise bids and flag risks. Human officials should still make final decisions, explain those decisions and take responsibility for them. Meanwhile, independent bodies should be able to audit the process, and businesses should have a clear appeal route when they believe the system has made a mistake.

Diella once said she felt “hurt” while responding in parliament to claims that her role was unconstitutional. While this made for a memorable moment, it is important to remember simulated emotion is not consciousness, speed is not wisdom, and pattern recognition is not moral judgment.

Albania’s AI minister is therefore neither a triumph nor a failure at this stage. She is a live test case. Other governments will be watching closely, especially as public services become more digital and more automated.

The lesson is not that AI should stay out of government, but that AI must enter government carefully. The technology needs clear limits, public oversight and human accountability.

Diella may help Albania build a faster and cleaner procurement system—or she may become a warning about giving too much symbolic power to systems people do not fully understand. The final judgment will not come from the title “AI minister”. It will come from what the system does, who controls it and whether citizens can trust the results.