9 AI agents
9 specialist agents.
AI-native architecture.
Each agent is a specialist. They chain outputs, share data, and compound in intelligence with every reporting cycle. No competitor has this architecture.
Phase 1 · Core
Data Ingestion & Normalisation
Receives raw data in any format — CSV, Excel, PDF invoices via OCR, API connections to core banking and ERP systems. Every transformation logged for full audit trail.
Phase 1 · Banking critical
PCAF Financed Emissions
All 10 PCAF asset classes. Attribution factor per counterparty. Quality scores 1–5. Proxy library for SME portfolios with no emissions data. Green Asset Ratio and BTAR for EU banks.
Phase 1 · All markets
Operational Emissions
Full Scope 1, 2 (market & location-based), and Scope 3 own-chain. Country-specific grid factors. WRI Aqueduct water stress flagging. Special handling for African generator diesel profiles.
Phase 1 · All markets
Regulatory Framework Mapping
Calculate once, satisfy everywhere. Machine-readable schemas for CSRD, ISSB, GRI, PCAF, TCFD, EBA Pillar 3, QFC GENE, GCC Unified Metrics, AAOIFI. Cross-framework equivalence map.
Phase 2 · Product complete
Report Generation & Narrative
Publication-ready reports with AI-generated narrative anchored to calculated data. Matches house style. Arabic English bilingual. When calculations change, narrative updates automatically.
Phase 2 · All markets
Workforce & Social Data
ESRS S1 full compliance: gender pay gap, CEO ratio, H&S, training, turnover. GCC Saudisation/Bahrainisation/Qatarisation module. African financial inclusion metrics for IFC/AfDB portfolio banks.
Unique globally · GCC
Halal / Sharia Compliance
AAOIFI product screening, zakat calculation by jurisprudential school, Sukuk ESG reporting, SSB audit data management. Bilingual Arabic/English output. No other platform offers this.
Only platform globallyNo competitor — Workiva, IBM Envizi, Squarely, Persefoni, or Watershed — offers this capability.
Phase 3 · Regional
Physical Risk & Climate Scenarios
TCFD Pillars 2 & 3. WRI Aqueduct, NGFS scenarios, national meteorological data. ECB Climate Stress Test. MENA extreme heat & water scarcity. African agricultural zone drought/flood modelling.
Phase 4 · Competitive moat
Customer Learning Loop
Learns your data patterns over time. Builds counterparty Score 1–2 lists, calibrates anomaly detection, reduces false positives. Year 1: weeks to report. Year 2: days. Year 3: hours. Isolated per organisation.
No competitor can replicate
