ReguShield AI
ReguShield AI
Compliance Intelligence Infrastructure
Investor DemoBeta Dashboard
Building the compliance layer of Europe

Turn regulation into real-time decisions.

ReguShield AI helps regulated digital businesses detect compliance risk earlier, understand operational impact, and move faster with clear recommended actions.

Not a static dashboard. A live compliance decision layer.

Open Investor DemoOpen Beta Dashboard
AMLEU AI ActMiCAWorkflow Mapping
Live Decision Engine
Risk Overview
High Risk
ReguShield AI Shield
From regulation to decision.
AI Risk Score
82
Active Alert
AML Monitoring Trigger
Pricing

Choose the operating layer that fits your stage.

ReguShield AI is designed for different levels of compliance maturity — from visibility and monitoring to a full decision engine with audit-ready outputs.

Starter
Visibility
299 € / mo
Weekly risk summary
Core risk scoring
Email reporting
View Product Demo
Growth
Action Engine
Core Product
999 € / mo
Real-time alerts
AI recommendations
Team / impact analysis
Open Investor DemoOpen Beta Dashboard
Enterprise
Infrastructure
3000 €+
Custom workflows
Full API integration
Audit-ready reporting
Book Enterprise Demo

How It Works

From operational data to regulator-ready decisions.

ReguShield AI turns fragmented operational signals into structured, prioritized, and regulator-ready compliance decisions.

01

Ingest

Connects operational data, workflow events, internal controls, and regulatory signals through light setup or API-ready integrations.

02

Detect

Identifies risk-relevant patterns across AML, MiCA, EU AI Act, and market-entry readiness scenarios.

03

Score

Calculates a live exposure score using urgency, business impact, control gaps, and scenario severity.

04

Map

Connects each signal to affected workflows, teams, control points, and reporting responsibilities.

05

Act

Generates recommended actions, evidence-backed outputs, and submission-ready compliance reporting packages.

Software Proof

Built as software, not as a consulting layer.

ReguShield AI is designed as a live compliance operating layer with sector-specific logic, decision workflows, evidence tracking, and regulator-ready outputs.

API-ready architecture
Live risk scoring engine
Workflow mapping layer
Action recommendation engine
Evidence and audit trail layer
Regulator-ready reporting output
Web-based operational interface
Multi-sector scenario system

Technical Proof

Built as a compliance intelligence system, not a static dashboard.

ReguShield AI is designed to ingest operational signals, normalize risk inputs, map regulatory logic to workflows, calculate exposure, generate actions, and assemble regulator-ready outputs.

Data Inputs

  • Transaction data
  • KYC / customer records
  • Workflow events
  • Policy and document inputs
  • Regulatory signals
  • Internal compliance triggers
  • Model outputs / governance signals

Core Engine

  • Ingestion layer
  • Signal normalization logic
  • Risk scoring engine
  • Workflow mapping engine
  • AI-assisted recommendation engine
  • Priority and team assignment logic
  • Evidence and audit logging
  • Report assembly layer

Outputs

  • Risk score
  • Scenario-based alerts
  • Recommended action
  • Team assignment
  • Priority level
  • Evidence trail
  • Decision summary
  • Regulator-ready reporting pack

Architecture Flow

Ingest

Operational data, regulatory signals, and internal control inputs enter the system.

Detect

Risk-relevant patterns, control failures, and scenario triggers are identified.

Score

Exposure is prioritized through a live scoring model based on impact, urgency, and severity.

Map

Signals are tied to workflows, teams, control points, and reporting obligations.

Act

Recommended actions, evidence layers, and regulator-ready outputs are generated.

AI-assisted scoring and recommendations

ReguShield AI uses structured scoring logic and AI-assisted recommendation generation to translate compliance complexity into operational next steps.

API-ready integration model

Designed to integrate with transaction systems, KYC tools, internal workflows, policy inputs, and compliance-related data sources through API-based or connected data pipelines.

Infrastructure direction

The long-term goal is not only reporting, but building a live compliance decision layer that can operate as infrastructure across regulated digital businesses.

In short: ReguShield AI is built to convert data → risk → decision → report, with a system architecture designed for integration, explainability, and operational action.

System Architecture

Operational data meets regulatory logic

ReguShield AI combines operational data, regulatory logic, workflow-level mapping, and reporting assembly to generate live risk scores, recommended actions, and regulator-ready outputs.

Inputs

  • Transactions
  • KYC / User Data
  • Workflow Events
  • Policy / Document Inputs
  • Regulatory Signals
  • Model / Governance Signals

Core Engine

  • Ingestion Layer
  • Signal Normalization Layer
  • Risk Scoring Engine
  • Workflow Mapping Engine
  • Action Recommendation Engine
  • Evidence & Audit Layer
  • Report Assembly Layer

Outputs

  • Alerts
  • Team Assignment
  • Priority
  • Recommended Action
  • Evidence Trail
  • Decision Summary
  • Report Pack
  • Submission Readiness

Architecture Flow

Data Sources → Signal Detection → Risk Scoring → Workflow Mapping → Action Engine → Evidence Layer → Report Output

Team

Founder-led. Compliance-focused. Product-driven.

ReguShield AI is being built with a strong execution focus around finance, compliance, and operational product thinking.

SI

Sedat İşkara

Founder

Finance, compliance, and product strategy background. Building ReguShield AI as an operational compliance intelligence layer for regulated digital businesses.

Focus areas: product vision, compliance positioning, go-to-market structure, and investor narrative.

SÖ

Serdar Öncü

Business Development & Strategic Partnerships

Supporting ReguShield AI on partnership development, strategic communication, market-facing collaboration, and growth-oriented business execution.

Focus areas: partner outreach, growth conversations, external relationships, and strategic expansion support.