Guided assessment dashboard
Plain-language impact summaries, ranked improvement actions, and an AI copilot designed for teams that do not live inside LCA software.
LCAgo
AI-assisted workspace for life cycle assessment workflows.
Open-source coreReproducible workflowsBuilt for experts
Overview
What it does
In developmentLCAgo helps researchers and sustainability teams build, assess, and interpret life cycle assessments with AI assistance and expert-guided workflows.
Life cycle assessment is slow not because the method is unclear, but because the work around it — assembling inventories, checking data quality, running scenarios, and writing up interpretation — is manual and hard to reproduce. LCAgo structures that work as a versioned, auditable workflow and applies AI assistance where it saves time without displacing expert judgment.
- Goal & scope structuring
- Inventory and data quality management
- Impact assessment across multiple methods
- Scenario comparison and sensitivity analysis
- Interpretation and reporting
Inside the workspace
See LCAgo in practice
From guided assessment to inventory modeling and scenario comparison, the workspace keeps evidence, assumptions, and next actions connected.
Inventory and data workspace
Connect sources, map inventory records, review data quality, and resolve missing factors across desktop and mobile workflows.
Scenario analysis
Compare design alternatives, inspect trade-offs, and keep assumptions visible while evaluating environmental performance.
Interface concepts shown for product direction. Product branding has been corrected using the official asset libraries; labels and details may evolve during development.
Features
Capabilities
What the workspace covers, from setup through to reporting.
Goal & scope workflow
Define functional units, system boundaries, and cut-off rules through a guided structure that stays attached to the study.
Inventory management
Import, map, and validate inventory data with built-in quality checks and full version history.
Impact assessment
Run assessments across multiple LCIA methods and review results through interactive visualisations.
Interpretation support
Surface hotspots, data gaps, and improvement opportunities — with every suggestion traceable to its inputs.
Scenario analysis
Compare alternatives and assumption sets side by side to evaluate design and sourcing decisions.
Reporting & collaboration
Generate reports that carry their assumptions with them, and share workspaces across a team.
Integrations
Seamless integrations
LCAgo sits on top of established open-source software rather than a proprietary engine, so models remain portable and results remain checkable.
Connects with
openLCA
Brightway2- Python
- MCP
How it works
How LCAgo works
A single workflow, with assumptions carried through every step rather than re-entered.
- 01
Data sources
Connect and import inventory data from databases, files, and APIs.
- 02
Model setup
Define goal, scope, functional unit, and system boundaries.
- 03
Impact assessment
Run assessments using multiple methods and analyse results.
- 04
Interpretation
Review hotspots, uncertainty, and improvement areas.
- 05
Reporting
Produce reports and visualisations for stakeholders.
Status
Development status
In developmentOnboarding early collaborators now.
LCAgo supports expert-reviewed LCA workflows. It does not replace professional judgment or methodological review.
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Interested in LCAgo?
Tell us about the systems you model and the decisions you need to support. We're onboarding early collaborators now.