The Enjins Manifest: AI Engineering For Net Zero

To the Founders, CTOs, and Visionaries of the Climate Transition, read our manifest to understand the what, why, how, and our bold ambition.

Nick Jetten

February 24, 2026

We are living at a defining moment in the race to Net Zero.

The global push to decarbonize has reached a point where ambition alone is not enough. The complexity, speed, and scale required demand a new type of intelligence, one capable of optimizing entire systems, not just components.

At the same time, artificial intelligence has matured from a research novelty into an industrial engine. Generative AI and autonomous agents are reshaping how we design, deploy, and manage technology.

At Enjins, we believe AI is the most powerful tool of our era — and the climate transition is the most urgent challenge of our time.

Our mission is to connect the two through AI engineering: building production-grade systems that turn climate data into operational impact.

In this manifest, we share WHERE we see the biggest opportunities for AI within climate, WHY Climate × AI makes sense technically, HOW to engineer it effectively, and WHEN to act.

WHERE AI Can Move the Climate Needle

ClimateTech is not a single market, it’s a network of complex and different data-heavy ecosystems with their own dynamics. Where data intensity meets hardware integration and high emissions, AI has the greatest leverage.

1. The Energy Transition

Our most urgent and mature domain. With renewables now covering nearly half of EU electricity, we face a €584 billion grid modernization challenge. AI is the only scalable tool that can coordinate decentralized assets through real-time forecasting, optimization, and control.

2. Mobility & Transport

Electrification is accelerating, but infrastructure lags behind.
From optimizing charging networks and fleet operations to monitoring battery life cycles, AI can transform logistics efficiency and make low-emission mobility truly scalable.

3. Decarbonizing Industry & the Built Environment

These “software-wrapped hardware” systems — from industrial control to smart HVAC — are ripe for AI-driven prediction, anomaly detection, and adaptive control, reducing emissions while improving uptime.

4. Climate Intelligence

Not a subsector of heavy emissions, but an enablement layer.
AI models powering real-time climate risk analysis, environmental simulations, and early warning systems strengthen every other subsector. Intelligence isn’t just insight — it’s resilience.

WHY Climate × AI Works

The technical landscape of climate solutions is both chaotic and data-rich. Sensors, IoT devices, satellites, drones, and digital twins generate torrents of data. The challenge is no longer data scarcity, but rather engineering intelligence at scale.

Four system truths make AI indispensable:

Abundant Data Sources – From solar panels to satellites, every climate venture sits atop vast, underutilized datasets that can feed meaningful AI models.
Hardware–Software Convergence – Most climate systems are “cyber-physical.” Once the software layer is working, AI becomes the next logic step to make it adaptive and autonomous.
Expert Knowledge Bottlenecks – Industrial and energy experts can make better, faster decisions when agentic AI systems learn from their domain insights within safe, structured knowledge bases.
Decision-Making under Uncertainty – Machine Learning based Predictive models remain key for everything from balancing renewables to managing volatility. The better we predict tomorrow, the smarter we steer today.

HOW to Invest and Build: The Engineering Mindset

Most AI efforts fail not in vision, but in execution.

Bridging the gap from idea to deployed system requires an engineering-first mindset.

Stop the FOMO, Get Real

AI isn’t a magic fix — but ignoring it is an existential risk. Each use case has its own “AI DNA.” A machine learning project for grid control has a different architecture and dynamic than an agentic AI system for workflow automation. We help companies to make the right choices here, and balance between pragmatism and scalability.

Shift from Consulting to Engineering

You don’t need only advice; you need working systems.

We design, build, and deliver end-to-end, production-grade AI systems, compliant with the EU AI Act and ready to scale. If we deem infrastructural components relevant from previous projects, we bring them along to avoid reinventing the wheel.

Build and Plan in Parallel

Balance between over-strategizing and building blindly. We condense what used to take months into rapid validation cycles through high-speed AI Design Sprints and ensure to prototype as early as possible.

Data as a Moat

As AI models commoditize, proprietary data, especially from hardware assets, becomes an important moat in climate & energy. We help to create data infrastructures that allow you to start leveraging this moat.

AI Engineering as crucial skillset for production-grade Agentic AI

We are now entering a world where especially generative AI systems act with intent, orchestrating workflows, not just answering prompts. Reliable agentic systems require robust orchestration, safety layers, and engineering discipline. Similar to the past challenge of bringing ML models beyond proof of concept, production-grade Agentic AI demands decent AI engineering skills and LLMOps.

Well designed green AI

If we use AI to drive climate impact, it must also be engineered responsibly, systems that help reduce emissions should not silently add to the problem. At Enjins, we approach this as a design dimension, not an afterthought. Through careful system design, lightweight model choices, optimized compute, intelligent caching, and continuous monitoring of carbon cost, we’ve learned that you can build production-grade AI systems whose positive climate impact far outweighs their footprint.

WHEN: The Moment Is Now

The era of experimentation is over.
The AI adoption curve has bent — and climate solutions can’t afford to wait.

Why this moment matters:

Climate Market Pressure – Investors no longer fund “green at any cost.” The next generation of climate ventures must scale profitably — and AI is the scaling mechanism.
Technological Maturity – LLMs, edge inference, and MLOps toolchains have reached industrial-grade reliability. What once was R&D is now ready for deployment.
Automation as a Standard – We use AI to automate the repetitive layers of engineering itself, delivering higher quality systems faster and more economically.
Climate Volatility – Every hour of energy imbalance, every degree of deviation, compounds into cost and carbon. Acting now isn’t optional — it’s intelligent.

OUR AMBITION: AI as an Engine for Climate Impact

We are building Enjins to be the AI engineering partner for ClimateTech in Northwest Europe. We help to make the right decisions early on, combined with outstanding AI engineering expertise and reusable technical assets like streaming, MLOps and multi-agent frameworks. All contribute to shorten the road from data to deployment, and to get it right the first time. We embed with your teams, work on your stack, and transfer both knowledge and capability. Together, we build AI for climate impact, done right the first time.

"Let’s reach Net Zero faster, by engineering intelligence where it counts."