Streamline SB-253 Climate Disclosure Compliance with AI- Powered XBRL Tagging
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Regulatory Mandate
What You Need to Know
What is SB-253?
California’s SB-253 requires companies with over $1 billion in annual revenue doing business in California to publicly disclose their greenhouse gas emissions. Reports must cover Scope 1 and 2 emissions starting in 2026, with Scope 3 reporting beginning in 2027.
XBRL Infrastructure
XBRL US developed the State GHG Emissions (SGHG) Taxonomy as a California-specific entry point to the ISSB Taxonomy for SB-253 reporting. While not yet mandatory, XBRL format is strongly recommended and expected to become standard as the regulation matures. Early adopters will gain a significant advantage as digital, machine-readable reporting becomes the norm.
Who is Affected?
Thousands of U.S.-based companies doing business in California with revenue exceeding $1 billion will need to report. The first submissions for Scope 1 and 2 emissions are due in 2026, based on prior fiscal year data.
Powerful Features
Smart · AI-Powered Automated GHG Data Processing
AI-powered extraction & normalization of Scope 1, 2 & 3 emissions.
- AI detects emissions values, targets, methodologies
- Auto-suggests correct SGHG taxonomy tags
- Fully aligned with CARB reporting expectations
Automated SGHG Taxonomy Mapping
Instant mapping of extracted data to California's State GHG (SGHG) Taxonomy.
- Converts unstructured data into valid XBRL.
- Ensures error-proof taxonomy assignments.
- Includes AI chatbot assistance for support
SB-253 XBRL Viewer
Explore, compare, and validate California climate disclosure XBRL files.
- Parse & view complete emission disclosures
- Supports SGHG + ISSB tags
- Viewable with AI-generated insights
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Compliance Hub
Our SB-253 Solution
SGHG Taxonomy Compliant
Automated tagging aligned with XBRL US State GHG Emissions Taxonomy specifications, ensuring regulatory compliance from day one.
ISSB Alignment
Built on the ISSB Taxonomy foundation, reducing reporting burden for companies subject to multiple regulatory requirements globally.
Automated Data Structuring
Transform unstructured emissions data into machine-readable XBRL format, eliminating manual tagging work that takes days.
Quality Assurance Layer
Human-in-the-loop review ensures business context and accuracy while maintaining the efficiency gains from automation.
Platform Integration
White-label deployment that extends your platform's capabilities without requiring you to build XBRL infrastructure in-house.
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Implementation
SB-253 Implementation Timeline
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Platform Benefits
Why Choose BriskFlow AI for SB-253?
Regulatory Expertise
Our platform is built by experts who deeply understand California’s SB-253 requirements. We automatically align your data with the exact XBRL US State GHG Emissions Taxonomy specifications, ensuring your submissions are completely compliant from day one without the guesswork.
Time Saving
Eliminate manual data entry and tagging. Our two-layer AI system extracts, structures, and validates emissions data in seconds—transforming unstructured PDFs into machine-readable formats. What used to take your team weeks can now be completed in a fraction of the time.
Multi-Framework Support
SB-253 is just the beginning. Our architecture is built on the ISSB foundation, meaning the data you map today can be seamlessly utilized for EU CSRD, SEC rules, and global mandates, drastically reducing the reporting burden for companies operating internationally.
Revenue Partnership Model
We don't just sell software; we build partnerships. Our white-label deployment allows you to seamlessly integrate our powerful XBRL engine directly into your own SaaS product, opening up new revenue streams and adding immediate value to your existing clients.
Proven Track Record
Trusted by enterprise platforms and leading ESG service providers. We process thousands of complex sustainability reports with industry-leading accuracy. Our human-in-the-loop review ensures that every tag carries the exact business context required by auditors.
Future-Proof Technology
As the CARB regulations evolve and reporting templates update in late 2025 and beyond, our AI engine updates instantly. You will never have to worry about rebuilding infrastructure or falling behind on the latest technical XBRL specifications.
Process Flow
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XBRL Mapping
Technical Approach
Automated Extraction
Our AI identifies and extracts GHG emissions data from sustainability reports, including Scope 1, 2, and 3 emissions, baseline years, targets, and methodologies (market-based vs. location-based).
XBRL Structuring
Extracted data is automatically mapped to the appropriate SGHG Taxonomy concepts, creating properly structured, machine- readable XBRL documents that meet CARB specifications.
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Expert Review
Human Review
Expert review ensures business context is preserved and taxonomy application is appropriate, maintaining quality while achieving dramatic time savings.