Artificial Intelligence and data

We turn data into analytical capacity, so teams can focus on understanding, deciding and acting.

If a conventional calculation rule solves the problem better, we don’t use AI. The calculation has to stay traceable and defensible; artificial intelligence is applied only where it reduces effort or improves a decision.

We design data and artificial intelligence solutions for specific sustainability needs: automating data collection, connecting sources, calculating indicators, detecting issues, comparing scenarios or anticipating risks.

We can start from scattered documents and spreadsheets, or from a technology infrastructure that already generates data but doesn’t yet make it easy to interpret. We begin by defining what question the system needs to answer, and what decision the organisation needs to make.

We organise the sources, set up indicators, and build a traceable calculation base. On top of that, we apply AI only where it adds value: for example, to extract information from invoices, technical data sheets and PDFs, classify documents, detect anomalies, or generate alerts and predictions..

The result can be an automated data-collection system, an operational dashboard, an impact-and-cost simulator, or a tool integrated with your existing systems. The goal is to cut repetitive tasks and give the team more capacity to measure, understand and manage sustainability with autonomy.

Servicios

Identificamos qué decisiones debe facilitar el sistema, qué información necesitan los usuarios y qué procesos ofrecen una oportunidad real de automatización o mejora.

Mapeamos fuentes, herramientas y responsables y definimos modelos de datos, criterios de calidad, reglas de cálculo y mecanismos de trazabilidad.

Aplicamos inteligencia artificial para extraer y clasificar información procedente de facturas, PDF, fichas técnicas y otros documentos no estructurados, reduciendo la introducción manual de datos.

Diseñamos cuadros de mando, indicadores operativos, simuladores y sistemas de alertas que permiten entender los resultados, comparar alternativas y detectar situaciones que requieren actuación.

Pilotamos las soluciones con datos y usuarios reales, acompañamos su integración con las herramientas existentes y capacitamos al equipo para mantener y evolucionar el sistema.

Identificamos qué decisiones debe facilitar el sistema, qué información necesitan los usuarios y qué procesos ofrecen una oportunidad real de automatización o mejora.

Aplicamos inteligencia artificial para extraer y clasificar información procedente de facturas, PDF, fichas técnicas y otros documentos no estructurados, reduciendo la introducción manual de datos.

Pilotamos las soluciones con datos y usuarios reales, acompañamos su integración con las herramientas existentes y capacitamos al equipo para mantener y evolucionar el sistema.

Mapeamos fuentes, herramientas y responsables y definimos modelos de datos, criterios de calidad, reglas de cálculo y mecanismos de trazabilidad.

Diseñamos cuadros de mando, indicadores operativos, simuladores y sistemas de alertas que permiten entender los resultados, comparar alternativas y detectar situaciones que requieren actuación.

Measuring the impact of an iconic piece to make better decisions on materials, finishes and logistics
Joidart

Measuring the impact of an iconic piece to make better decisions on materials, finishes and logistics

LCA of JOIDART’s Embòlic earrings
Bringing traceability, environmental impact and end-of-life together in a single management tool
Benlligat

Bringing traceability, environmental impact and end-of-life together in a single management tool

Pasaporte digital y ACV del mobiliario hotelero
Assessing an alternative to anthracite before scaling it up industrially
Celsa

Assessing an alternative to anthracite before scaling it up industrially

ACV comparativo del biochar en la industria siderúrgica
Environmental data for choosing lower-impact materials, processes and finishes
Mr Karton

Environmental data for choosing lower-impact materials, processes and finishes

ACV comparativo de paneles acústicos de cartón reciclado

The architecture for building the system’s intelligence

A digital solution adds value when it improves a real decision within the organisation. At Spora we don’t start with the technology — we start by understanding what the company needs to know, which processes it wants to improve, and what information it needs to act with better judgement: we organise and improve data quality before automating, apply AI only where it reduces effort or expands analytical capacity, and build information systems your team can use and grow.

  1. Define questions and use cases

    Which decisions we want to improve, what information is needed, and which tasks are worth automating.

  2. Organise sources and structure the data

    Systems, indicators, owners, formats, frequencies and consolidation rules.

  3. Ensure quality, traceability and governance

    Validation, primary data, evidence, permissions, versions and methodological control.

  4. Build the information system

    Data models, dashboards, automations, integrations and our own digital architecture.

  5. Apply analytics and AI with judgement

    Classification, pattern reading, alerts, reporting and decision-oriented analysis.

  6. Visualitzar i pilotar

    Dashboards, prototypes and pilot cases to validate value, usability and impact.

  7. Activate autonomy and continuous improvement

    Team training, operational use, indicator review and system evolution.

  8. Scale

    Extend to more areas, processes and decisions; standardise, industrialise and maximise impact.

More team autonomy.
Better information for decisions.
Less operational friction.
More anticipation capacity.

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