ESG data sitting in spreadsheets across business units, with no way to consolidate it for a board report without a weeks-long manual exercise?
Supplier sustainability data arriving in inconsistent formats -- some via PDF, some via email, some via forms -- with no automated ingestion or validation?
ESG Data Management Platform
Custom ESG data management software that collects, validates, and consolidates sustainability data across facilities, suppliers, and business units -- giving sustainability teams and CFOs a single verified data store instead of a spreadsheet-per-site exercise before every board report.
Generic data tools handle ESG data poorly. The collection is multi-channel, the formats are inconsistent, the validation rules are domain-specific, and the audit trail requirements are stricter than most operational reporting. A purpose-built platform handles all of that without forcing your team to work around it.
Centralised ESG data collection across facilities, suppliers, and business units
Automated data validation and anomaly detection before reporting
Audit trail for every data point -- source, date collected, who approved
Integration with ERP, energy management systems, and supplier portals
RaftLabs builds custom ESG data management platforms for sustainability teams and CFOs -- centralised data collection from facilities and suppliers, automated validation, and audit-ready reporting. Most projects deliver in 10 to 16 weeks at a fixed cost.
100+Software products shipped
·FixedCost delivery
·10-14Week delivery cycles
·24+Industries served
ESG data management is a data engineering problem first
Sustainability reporting looks like a compliance problem from the outside. From the inside, it is a data engineering problem -- inconsistent sources, variable formats, manual collection, no validation layer, and no audit trail. The compliance requirement is simply what makes the data engineering problem impossible to ignore any longer.
Most organisations reach a point where spreadsheet-based ESG data collection stops working. The dataset gets too large, the number of facilities or suppliers too high, or the disclosure frameworks too demanding for a manual process to satisfy. A purpose-built ESG data management platform handles collection, validation, centralisation, and audit trail in a way that scales with the reporting obligation -- and gives the data quality that external assurance providers require.
What we build
Data collection and ingestion
Multi-channel data collection covering web forms for supplier and facility submissions, API connections to energy management systems and utility providers, flat file upload and parsing for Excel and CSV submissions, and email parsing for suppliers who send data by attachment. Structured supplier portals with guided input and field-level validation reduce the volume of unusable submissions that arrive in open-ended formats. Collection schedules configurable by data type, reporting period, and organisational unit. Every submission timestamped and source-attributed at the point of ingestion before any processing occurs.
Data validation and quality
Rule-based validation applied to incoming data before it enters the reporting store. Range checks flag values outside the physically plausible range for the metric, facility type, and prior-year comparison. Cross-metric consistency checks identify internally contradictory submissions -- for example, energy consumption per square metre increasing while reported floor area decreased. Year-on-year variance alerts flag significant changes without a corresponding operational explanation. Validation failures returned to the submitter with specific error descriptions so the problem is corrected at source rather than discovered at reporting time.
Centralised data repository
A single authoritative data store for all ESG metrics across Scope 1, 2, and 3 emissions, energy, water, waste, social metrics, and governance indicators -- organised by facility, business unit, and reporting period. Organisational hierarchy configuration allows data submitted at entity level to be consolidated to group level with clearly defined consolidation rules. Multiple time series maintained for the same metric so restated prior-period figures are tracked alongside the original submission. The single source of truth that gives a consistent answer to "what were our total emissions last year?" regardless of who asks.
Audit trail and data lineage
Every data point stored with its full provenance record -- source system or submission channel, collection date and time, submitting entity, transformation applied, validation outcome, reviewer, and approval status. An immutable log of every data modification, version change, and approval action. Prior-period restatements tracked with the reason for revision and the recalculated figures. The data lineage that allows any figure in a published ESG report to be traced directly to its source record -- which is what external assurance providers require before they will sign off on sustainability disclosures.
Reporting and disclosure output
Structured data output aligned to GRI, SASB, TCFD, and CDP reporting frameworks. Export formats matched to what each framework and disclosure platform accepts. Calculated metrics -- emissions factors applied, intensity ratios computed, boundary adjustments documented -- included in the output alongside raw figures. Third-party verification access: assurance providers receive a read-only view of source data, transformations, and approval records for the metrics in scope without requiring access to commercial or operational data outside the assurance engagement.
Integration with existing systems
Bidirectional integration with ERP systems (SAP, Oracle, Microsoft Dynamics) for financial and operational data that feeds emissions and social metrics calculations. Energy management system integration (Schneider Electric EcoStruxure, Siemens, Johnson Controls) for facility-level energy consumption data. Supplier portal integration where supplier sustainability data flows directly into the collection layer rather than arriving by email. Finance system integration for revenue and production volume denominators used in intensity calculations. Integration scope assessed during discovery based on what systems you have and what data they hold.
Frequently asked questions
Commercial ESG platforms handle standard reporting frameworks well. The case for custom software is when your data sources are non-standard, your organisational structure doesn't match platform assumptions, or your reporting requirements span frameworks in ways that commercial tools handle expensively. Platforms designed for common configurations work well for organisations that fit those configurations. When the configuration work exceeds what the platform supports, or when the cost of platform licences is disproportionate to the reporting obligation, a custom build is the more practical option. We give you an honest assessment of whether a commercial platform fits before scoping a build.
Supplier data ingestion typically involves a combination of structured supplier portals (web forms with field-level validation), file upload with parsing logic for Excel and CSV, and email-based submission with extraction logic for structured attachments. The ingestion layer normalises incoming data to a standard schema before validation rules run. Suppliers receive specific feedback when their submission fails validation -- which field failed, what the expected range is, what they should resubmit -- rather than having the problem surface at reporting time when the submission cannot be corrected.
A platform covering data collection, validation, and reporting output for a single reporting scope typically takes 10 to 14 weeks. A more complete system with supplier portals, multi-scope coverage, ERP integration, and audit trail for external assurance typically takes 14 to 22 weeks. The timeline depends on the number of source system integrations, the complexity of the organisational hierarchy, and the assurance access requirements. Fixed cost agreed before development starts -- scoped after an assessment of your data sources, reporting frameworks, and organisational structure.
Yes. ERP integration (SAP, Oracle, Microsoft Dynamics) is a standard part of ESG data management builds where financial and operational data feeds into emissions calculations -- production volumes for intensity metrics, headcount for social metrics, and financial turnover for normalisation denominators. Energy management system integration (Schneider Electric EcoStruxure, Siemens, Johnson Controls) handles facility-level energy consumption data. The integration scope depends on what systems you have, what data they hold, and whether that data is currently accessible via API or requires a data export approach. Both are assessed during discovery before scoping.