From manual sampling to real-time insight: how Greentech Baltic increased PET recovery revenue by 10%

Before, we could only look at the final results to figure out yield. Everything in between was guesswork. We had no data.”

Tadas Lenkutis, PhD

Technologist/Production Manager

Relying on manual checks also limited confidence in product blending. To meet customer requirements, the team had to estimate the proportions of clear and light blue PET, often relying on intuition instead of accurate composition data.

The solution: Continuous analysis, powered by AI 

The Analyzer system offered a more scalable alternative, and the data that Greentech Baltic (a Greengroup company) had been missing. After a quick calibration process, Tadas was confident enough to replace one-off sampling with AI:

I compared Analyzer data to manual analysis, and the results matched. I know I can trust the system, which means we don’t need to conduct manual inspections anymore. I get reliable data for the entire day instead.”

Tadas Lenkutis, PhD

Technologist/Production Manager

Instead of spending dozens of hours to sample 300 kilograms of material per month,  Greentech Baltic, now spend a fraction of that to analyse several tonnes each day.

With minute-to-minute composition data, the team can now spot problems as soon as they arise — instead of hours, days or weeks later. If contaminated bales arrive, for example, they can reject them without wasting time on processing:

Our entire sampling process has changed. We collect data every day now. Measuring more material means we can trust our analysis more, because we’re accounting for differences across a full day, not just a single batch or bale.”

Tadas Lenkutis, PhD

Technologist/Production Manager

Greentech Baltic receives PET bales from both deposit return schemes (DRS) and pre-sorted waste, which can vary in purity. Infeed data helps Tadas and his team adjust operations to material streams from different sources, and identify trends in quality. That insight is shared across the group’s multinational network, aligning sites on quality with the same consistent, data-driven reporting.

For Tadas, one of the biggest operational improvements has been moving from intuition to data-driven decisions on final product blends. Now, instead of estimating, his team uses Analyzer composition data to meet customer specifications in granular detail:

Instead of guessing, we know the exact percentage of contamination. That means we can decide faster, adjust the blend, and increase profitability.”

Tadas Lenkutis, PhD

Technologist/Production Manager

The outcome: A revenue boost, and a pathway to automated operations

Data-driven blending has a measurable impact on revenue. Greentech Baltic can charge a premium for clear PET flakes, or maximise profits when customer requirements allow for a small proportion of light blue flakes. That precision is worth an estimated 10% increase in revenue for Greentech Baltic's PET recovery facility.

As part of the company’s wider waste intelligence strategy, Tadas sees an opportunity to embed Analyzer data in existing machinery, using live data to automatically adjust parameters:

I think the next phase of AI deployment will see integrations with equipment, where we can adjust things like line speed to keep things efficient. In the future, I think that data-driven automation will be very important.”

Tadas Lenkutis, PhD

Technologist/Production Manager

Tadas told us that he values our technology, but also the long-term vision that our team’s expertise and enthusiasm supports:

The Greyparrot team understands what the main struggles for recyclers are. I have a lot of ideas about new features that could help us, and you’re always eager to incorporate them into product development plans.

Normally companies are more conservative, but Greyparrot is clearly eager to develop the technology as much as possible. It feels like a collaboration.”

Tadas Lenkutis, PhD

Technologist/Production Manager

Waste intelligence has already replaced manual checks at  Greentech Baltic's PET processing facility. The next step is already taking shape: automation, optimisation, and the consistent profitability that comes from turning every tonne of waste into a precisely managed resource.

Learn how more waste management leaders are using AI to boost efficiency (and profits) here.