Automating CEQA Reviews
Learn how to set up AI-powered workflows to streamline CEQA document reviews and compliance checks.
Read guide →Guide archive
Practical playbooks, workflows, and best practices for leveraging AI in environmental planning and regulatory compliance.
Each guide documents a repeatable pattern pulled from live CEQA and NEPA delivery work. They package prompt libraries, data models, and QA routines so your team can move from pilots to production without re-learning the same lessons.
Use them to standardize how you scope AI efforts, align consultants and agency staff, and maintain auditable records that satisfy both CEQA Guidelines and CEQ regulations.
Learn how to set up AI-powered workflows to streamline CEQA document reviews and compliance checks.
Read guide →Implement natural language processing to analyze environmental impact statements efficiently.
Read guide →Best practices for integrating diverse environmental datasets with AI models.
Read guide →Step-by-step guide to implementing environmental data APIs in your workflow.
Read guide →How to train custom ML models for environmental prediction and classification tasks.
Read guide →Automate regulatory compliance checks using AI-powered validation tools.
Read guide →Deploy language models to draft scoping narratives, validate baseline data, and rank likely impact topics early.
Read guide →Blend automation with expert oversight using structured queues, staffing pods, and QA instrumentation.
Read guide →Build data pipelines and dashboards that track mitigation measures, deadlines, and field verification status.
Read guide →Download our comprehensive guide covering everything from basic concepts to advanced implementation strategies for AI in environmental planning workflows.