AI × Sustainability · Custom Enterprise Systems
Custom AI Systems That Turn Sustainability Data Into Decisions
Net0 engineers bespoke sustainability platforms for global enterprises: automated data collection across every entity, audit-ready CSRD and ISSB reporting, and AI models that show exactly where emissions and cost come out together.
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Built for you
100%
Of your sustainability architecture designed around your own operating structure
10,000+
Integrations feeding emissions, energy, waste, and supply chain data in automatically
400+
Entities reporting through Net0 across enterprises and governments
What Changes for You
Sustainability Work That Finally Runs Itself
A custom Net0 system replaces manual collection, reconciliation, and reporting with one governed pipeline — so your team spends its time reducing emissions instead of chasing data.
70%
less manual effort
Data collection across entities, suppliers, and utilities runs automatically instead of through spreadsheets.
4×
faster reporting cycles
CSRD, ISSB, and internal disclosure packs assemble from one audited data layer.
100%
auditable data trail
Every figure traces back to its source system, method, and emission factor.
12–24wk
to production
From first workshop to a system running across business units and regions.
Decarbonisation you can act on
Scenario models show the cost, payback, and emissions impact of each abatement option before you commit capital.
Reporting that survives assurance
CSRD, ISSB, GHG Protocol, and local frameworks generated from one governed data layer, with full lineage for auditors.
Supply chain visibility
Supplier data, spend, and climate exposure combined into Scope 3 estimates that improve as real data arrives.
Energy, waste, and water in one place
Operational streams from meters, sensors, and facilities feed the same system that reports your targets.
Strategic Co-Design
What Is a Custom Sustainability AI System?
A custom enterprise AI solution is a purpose-built platform where data infrastructure, AI models, and application logic are engineered for one organization’s operating structure, not assembled from generic modules. Net0 begins every engagement with strategic co-design, mapping entities, compliance workflows, and sustainability priorities into a clear architecture before development starts.
Custom AI Models Built by Net0 Engineers
Net0’s in-house AI engineers and data architects develop custom ML models, analytics engines, and agentic workflows, integrated directly into existing ERP, SAP, and Oracle environments.
Linked to Financial and Operational KPIs
Environmental performance connects to capital allocation, risk registers, and CFO dashboards, with architectures that quantify ROI from decarbonization, supply chain, and compliance programmes.
Purpose-Built for Unmet Requirements
Climate-adjusted supply chain simulators, ESG risk engines, and operational digital twins: Net0 builds capabilities that standard sustainability software cannot configure.
Ground-Up Development
How Does Net0 Build Full-Stack AI Systems?
Net0 engineers the complete system stack (data lakes, model orchestration, API layers, security protocols, and interfaces) to enterprise specifications. Each component supports sustainability operations across Scope 1, 2, and 3 reporting, CSRD, CDP, GRI, and ISSB disclosure, with 10,000+ integrations connecting ERP, finance, and ESG platforms across global entities.
AI-Native by Design
Systems are architected around custom ML models, advanced analytics engines, and real-time data flows, enabling high-precision forecasting, optimization, and scenario planning.
Hybrid Data Infrastructure for ESG
Hybrid storage layers (time-series, document, and graph databases) designed for ESG data formats, CSRD and ISSB reporting requirements, and cross-system integration.
Enterprise-Ready Architecture
On-premise, multi-cloud, and federated deployment with ISO 27001 compliance, scalable APIs, and end-to-end observability, aligned to EU AI Act governance requirements.
Scope a sustainability system around your operating structure
Bring your entities, source systems, and disclosure obligations; we will map the architecture, integrations, and delivery sequence with you.
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Built to Evolve
How Do Custom Systems Keep Pace with Regulation?
Custom AI architectures must absorb new models, regulations, and business units without re-platforming. Net0 designs systems for multi-model orchestration, federated data governance, and sovereign or hybrid deployment, so large global enterprises (including Fortune 500 companies in the US and comparable organisations worldwide) and government entities maintain performance as AI capabilities and compliance requirements evolve.
Architectures Built for Continuous AI Evolution
Support new models, training cycles, and AI inference methods as requirements grow, without rebuilding core infrastructure or disrupting production workflows.
Enterprise Complexity, Engineered In
Multi-layer hierarchies, overlapping data ownership, and distributed teams: tailored architectures align with how large organizations actually operate across regions and entities.
Long-Term Maintainability at Scale
Designed for longevity: systems remain reliable, secure, and performant across years of AI upgrades, user growth, and operational change at institutional scale.
Choosing Your Path
Custom Build or Modular Platform?
Both paths lead to the same outcome: a system that fits how you actually operate. The modular platform gets you there fast, and custom engineering takes over where your requirements go beyond what any product covers.
Modular platform
Start here when the capability already exists
Carbon accounting, ESG reporting, air quality, waste, and energy are already covered
You need results in weeks, not a development cycle
Requirements map onto configuration, not new engineering
Budget favours predictable subscription over build investment
You can adopt module by module as strategy evolves
Typical time to first live module: 2–6 weeks
Custom engineering
Choose this when the system has to be built
The capability you need does not exist in any product yet
Data lives across systems no connector fully covers
Models must be trained on your own operational history
Deployment must run on-premise, sovereign, or federated
Sustainability logic has to sit inside financial decisioning
Typical time to production system: 12–24 weeks
How It Works
01
Map Objectives to System Requirements
Net0 begins with structured discovery alongside technical and sustainability teams, translating strategic goals into functional system requirements. Whether simulating decarbonization trade-offs, modelling distributed facility performance, or building a cross-border ESG command centre, ambition becomes architecture.
02
Co-Design the Full Technical Stack
Net0 engineers co-design the system architecture from the ground up: data lake structure, inference workflows, ML model types, orchestration layers, and enterprise integration logic. No templates — only what your sustainability and reporting use case actually demands.
03
Build and Deploy AI-Native Infrastructure
From probabilistic models and multi-modal analytics engines to federated data layers and user interfaces, Net0 builds and deploys every component to enterprise-grade standards. Emissions, energy, and supply chain pipelines, APIs, security protocols, and user roles are custom-developed for scale, compliance, and performance.
04
Test, Validate, and Operationalize
Every component is stress-tested and validated in the target environment against your audited baselines and real operational data. Rollout includes sandbox environments, UAT protocols, and production controls, ensuring figures hold up across business units and geographies.
05
Future-Ready by Design
Built to support multi-model AI architectures, distributed data systems, and cross-border operations, the custom solution evolves alongside the enterprise. Net0’s AI experts continuously update, adapt, and optimize the system as new capabilities emerge.
Delivery Timeline
From First Workshop to Production
A dedicated Net0 team works alongside yours throughout. Here is what the first six months typically look like.
Weeks 1–4
Discovery and architecture
Structured workshops with your technical, sustainability, and finance leads produce a signed-off architecture before any code is written.
Entity, data, and compliance mapping
Target architecture and model plan
Integration inventory and access review
Success metrics and acceptance criteria
Weeks 5–12
Build and integrate
Engineering runs in two-week increments against your environment, with working software reviewed at the end of every cycle.
Data layer and pipelines stood up
Models trained on your emissions and operations history
ERP, SAP, Oracle, and IoT integrations
Interfaces, roles, and access control
Week 13 onward
Validate, roll out, evolve
Validation moves into staged rollout by business unit and region, then into a long-term optimisation cadence.
Sandbox, UAT, and production controls
Region-by-region deployment
Model retraining as reporting rules change
Quarterly roadmap and capability reviews
System Architecture
One Stack, Engineered Layer by Layer
Every custom system Net0 builds shares the same five-layer shape. What changes is the engineering inside each layer: which sources are ingested, how data is modelled, which algorithms run, and where the system is deployed.
The Custom Stack
Interfaces
Role-based dashboards, approval flows, and APIs for finance, operations, and sustainability teams
Orchestration
Agentic workflows, scheduling, and human-in-the-loop review across entities and regions
Models
Custom ML, forecasting, and scenario engines trained on your emissions and operational history
Data layer
Time-series, document, and graph stores shaped for ESG, CSRD, and ISSB requirements
Data sources
ERP, SAP, Oracle, IoT sensors, invoices, utilities, and supplier submissions
Each layer is engineered independently, then aligned to the decisions the layer above it has to support.
Integrations
Connected to the Systems You Already Run
Over 10,000 integrations across ERP, finance, procurement, utilities, and IoT — with custom connectors engineered for anything that is not covered.
SAP
Workday
ServiceNow
Siemens
Schneider
IoT sensors
10,000+ integrations · 100,000+ emission factors · 120+ geographies · custom connectors built where none exist
Explore all integrations
Before You Ask
Frequently Asked Questions
Cost, ownership, maintenance, timelines, and how a custom build sits alongside the systems you already run.
How is a custom build priced?
Engagements are quoted as a fixed-scope build following the discovery phase, then an annual platform and support fee. Discovery is priced separately and produces a signed-off architecture you own, whether or not you continue into build.
Who owns the intellectual property?
You own your data, your models trained on that data, and the configuration and logic specific to your organisation. Net0 retains its underlying platform components and pre-existing frameworks, licensed to you for as long as the system is in service.
Who maintains the system after launch?
Net0 maintains it by default: monitoring, model retraining, connector updates, and security patching under an annual agreement. Where you prefer to run it in-house, we deliver documentation, training, and a handover period, or split responsibilities in a hybrid model.
How long does it take?
Discovery runs four weeks, build and integration typically twelve to twenty weeks depending on scope and the number of source systems, then staged rollout by business unit or region. First working software is reviewed within the first month of build.
What happens to our existing systems?
Nothing is ripped out. Your ERP, finance, and operational systems remain the source of truth; the custom platform integrates with them through secure APIs and data pipelines. Where you already run Net0 modules, those carry across into the custom architecture.
Can we start modular and move to custom later?
Yes, and most enterprises do. Modules deployed today become part of the custom architecture later, so early work is never wasted; the data model and integrations carry forward.
