ReguGraph | Intelligence Control Center

Forenly AI RaaS - Cloud Computing

Normalization

Vectorization

Reasoning

Observability

Regulatory Intelligence

Automated transformation of static PDFs into structured knowledge nodes
Multi-language support for global regulatory framework analysis
Context-aware metadata tagging for high-precision retrieval
Continuous monitoring of regulatory updates and delta detection

Agentic Orchestration

Proprietary Multi-Agent Swarm for deep reasoning and validation
Parallel inference threads using Gemini 2.0 and Claude 3.5 Sonnet
Automated obligation discovery with zero human intervention
Dynamic relationship mapping via Semantic Graph Engine

Enterprise Infrastructure

High-performance vector memory via Cloud SQL (pgvector)
Seamless integration with Google Cloud Vertex AI ecosystem
Sub-second retrieval accuracy for millions of compliance nodes
Hardened security with Google Cloud IAM and Audit Link

Audit & Transparency

Immutable audit logs for every AI decision and reasoning step
Visual traceability of obligation discovery logic chains
Verifiable consensus scores for high-stakes compliance voting
Explainable AI (XAI) for regulatory conflict resolution

Deployment Status

PROD_ACTIVE GCP_US_CENTRAL1 VERTEX_READY

1. Data Ingestion & Normalization

Heterogeneous artifacts are converted into knowledge nodes via Google Cloud Vertex AI OCR.

2. Agentic Reasoning Layer

Vertex AI Agent Builder handles multi-step reasoning and obligation discovery.

3. Semantic Mapping & Memory

RAG engine using Google Cloud SQL with pgvector indexing (Project: gen-lang-client-0132716388).

CURRENT FOCUS 🎯

4. Immutable Audit Finalization

AI decisions are hashed for full audit trails and explainable logic.

QUICK FAQ

Frequently Asked Questions

What exactly is ReguGraph?

ReguGraph is a next-generation compliance platform that transforms static regulatory documents (PDF, DOCX) into an intelligent Knowledge Graph via autonomous AI agents.

What does "2026" represent?

This denotes the platform's 2026 vision and Roadmap. The currently active V2.0 infrastructure is being developed towards the goal of fully autonomous regulatory tracking by 2026.

How is data security ensured?

All data is stored on Google Cloud Platform (GCP) with Enterprise-grade IAM and KMS encryption. Analyses are performed in a closed-circuit environment within Vertex AI.

Which document types can I analyze?

Currently, we offer high-precision OCR and semantic analysis support for complex PDFs, HTML pages, and DOCX documents.