Issue No.060
TL;DR // This edition is all about the Library of Life, an eco-friendly edge cloud, recommerce as a service, muscle-machine interfaces and logic-based AI models.
Hej, this is Sustainovation Tidbits.
As people remember from my previous newsletter Timo's Trend Thursday, this format is known for sharing bite-sized trend insights that pack a punch without going into epic detail. With over 950 trends and innovations featured across 190 episodes of Timo's Trend Thursday it’s time to kick off something new. But somehow similar.
For those who are passionate about the convergence of design, tech, innovation and sustainability, Sustainovation Tidbits is your go-to destination for a weekly dose of inspiration and insight.
01. Enveda
Enveda Biosciences leverages advanced AI and mass spectrometry to rapidly explore and decode 99.9% of natural small molecules that remain uncharacterized, creating a massive “Library of Life” to accelerate novel drug discoveries. Their platform identifies promising candidates from complex biological extracts in parallel, without traditional isolation steps, leading to medicines targeting previously “undruggable” pathways.
What’s differentiating?
The global challenge Enveda addresses lies at the intersection of public health, environmental sustainability, and equitable innovation. Non-communicable diseases like inflammatory disorders and emerging infectious threats still lack safe, effective, and accessible treatments, disproportionately impacting vulnerable populations - particularly in low-income countries. Enveda is making a difference by vastly expanding the chemical space available to drug developers. Around half of all oral small-molecule drugs derive from natural sources; yet, fewer than 0.1% of natural compounds are known to science and actively screened. Enveda reports expanding this catalog from ~300,000 to over 1.5 million compounds. Their AI-driven metabolomics platform allows them to evaluate thousands of compounds in parallel - uncovering candidates up to four times faster and at roughly one-tenth the typical cost, while benefiting from the evolutionary safety and biological compatibility that enhance clinical success rates.
Enveda
02. PoliCloud
PoliCloud provides decentralized, sovereign, and eco-friendly edge cloud infrastructure, delivered via containerized micro-data centers, to empower cities, enterprises, and public institutions with secure, localized computing and storage capabilities. Their platform combines proprietary hardware with Hivenet’s software to offer high-performance GPUs and confidential compute, reducing reliance on centralized hyperscalers while cutting costs and carbon emissions.
What’s differentiating?
PoliCloud is addressing a pressing global need: as AI and digital transformation grow, demand for compute power is expanding at ~20 % annually, but current centralized cloud models are increasingly costly, environmentally taxing, and dominated by U.S. providers -raising concerns about data sovereignty and sustainability. By deploying edge data centers that achieve zero water waste, reduce CO₂ emissions by approximately 75 %, and slash costs by up to 60 % within just 50 m² units, PoliCloud aligns with UN SDG 9 (Industry, Innovation, and Infrastructure) and SDG 13 (Climate Action), while strengthening data autonomy under GDPR and national regulations.
03. Renow
Renow uses AI-driven software and local warehouse networks to transform e-commerce returns into resalable, second-hand products by automating inspection, grading, relisting, and logistics all through its “recommerce as a service” platform.
What’s differentiating?
They tackle the massive inefficiency and waste in global e-commerce returns, a €70–80 billion annual market in Europe alongside a €94 billion second-hand sector, by reducing waste, extending product lifecycles, and helping retailers recover value while offering consumers access to nearly-new goods. Their solution aligns with UN SDG 12 (Responsible Consumption and Production), SDG 9 (Industry, Innovation & Infrastructure), and SDG 13 (Climate Action) by cutting manual processing by ~70%, accelerating resale timelines from months to days, and diverting large volumes from landfill. Renow’s platform blends two mobile apps - one for customers initiating returns and one for warehouse staff conducting inspections - that use AI to grade condition, automate relisting, create product details, and determine routing. This digital-first “virtual warehouse” approach enables decentralized processing via 3PL partners, eliminating the need for expensive infrastructure and slashing turnaround time, carbon emissions, and logistical costs
04. PhantomNeuro
Phantom Neuro develops a minimally invasive, implantable muscle-machine interface called Phantom X that decodes natural muscle signals to provide intuitive, real-time control of robotic prosthetics and exoskeletons, no brain surgery required.
What’s differentiating?
They address the global challenge of functional loss experienced by millions of amputees, individuals with nerve injuries, and those suffering age-related muscle weakness, conditions that current prosthetics and assistive devices struggle to manage effectively. According to a Wired report, 74.4% of upper-limb amputees use body-powered devices while only about 20.7% try myoelectric prosthetics, and many abandon them due to slow or imprecise control. Phantom’s implantable sensors, by contrast, have achieved gesture decoding accuracy between 84.8% and 98.4% and sub‑200 ms latency across 11 hand and wrist gestures, dramatically exceeding typical prosthetic performance
05. Literal Labs
Literal Labs develops a next-generation AI platform based on propositional logic and Tsetlin machines, delivering custom models that are dramatically faster, more energy-efficient, and inherently explainable compared to traditional neural networks, ideally suited for edge deployment. Their technology enables sub‑GPU performance, achieving 54× faster inference and using 52× less energy, at a cost of under $5 in hardware, with no need for high-power accelerators.
What’s differentiating?
They are addressing a critical sustainability and transparency gap in AI. The massive energy consumption of neural networks, particularly in edge devices, drives up costs and carbon emissions, while their "black box" nature poses serious risks in regulated sectors like healthcare, finance, and autonomous systems. Literal Labs’ logic-based models, built on research from Newcastle University and the University of Agder, offer a lean alternative: they reduce power draw and inference times by over fiftyfold, can run on minimal hardware, and produce outputs that are fully explainable. In summary, Literal Labs is turning rigorous academic advances in logic-based AI into a practical, scalable, and sustainable technology that tackles today's dual challenge of AI’s energy demands and opacity, making it an impactful innovation with immediate environmental and regulatory relevance.
Loved what you read in our 60th issue? If the first issue resonated with you I’d be more than happy if you could spread the word. In the meantime stay curious, and differentiating. See you next week.
cheers, Timo
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