Overview

Our Case Management platform provides a unified interface for managing investigations, risk reviews, and operational workflows across teams.
It enables customers to create, assign, and resolve cases efficiently — all while leveraging AI-driven insights and automation to significantly reduce resolution time and human error.

The product serves as a control center for analysts, compliance officers, and fraud teams to collaborate, triage, and act on complex events in real time.

Core Capabilities

1. Custom Workflows as Cases

• Users can define custom case types, workflows, and actions aligned with their internal Standard Operating Procedures (SOPs).

• Workflows can involve multiple data sources — such as identity verification results, document analysis, or graph-based entity linkages.

• Each case maintains a full audit trail of actions, comments, and data events.

Why it matters:
This modular design enables organizations to tailor case structures to their operational or regulatory context — whether AML review, fraud escalation, or KYC re-verification.

2. Analyst-Focused Interface

The Case Management interface is built for speed and clarity.

• Analysts can switch between cases instantly using a zero-latency dashboard that prioritizes active or high-risk items.

• The workspace includes real-time data context — pulling related user profiles, verification results, and graph connections directly into view.

• Cases can be grouped, filtered, and searched globally without page reloads.

Why it matters:
Analysts can process more cases per hour with less friction — reducing backlog, human fatigue, and context-switching overhead.

3. AI-Driven Automation

Beltic integrates AI agents throughout the case lifecycle to streamline manual decision-making.

• AI agents automatically analyze case data against customer SOPs, triggering recommendations or auto-resolutions when confidence thresholds are met.

• Rule engines can be combined with natural language processing (NLP) for unstructured input (e.g., analyst notes or uploaded documents).

Why it matters:
Repetitive, low-risk cases can be resolved automatically — freeing analysts to focus on exceptions and complex scenarios.

4. AI-Assisted Decision Support

Beyond automation, Beltic’s models help analysts summarize, interpret, and act faster.

• Summarization models condense large data sets, logs, and attachments into actionable overviews.

• Contextual embeddings allow the system to surface the most relevant entities, historical cases, or previous analyst comments.

• Decision suggestions are presented with confidence scores and traceable rationales for compliance and auditability.

Why it matters:
Analysts spend less time reading and more time deciding. The combination of automation and reasoning ensures high accuracy with full transparency.

Workflow Architecture

Beltic’s Case Management system is designed as a workflow engine that orchestrates:

1. Case Creation — initiated by API triggers, rule conditions, or manual input.

2. Assignment and Collaboration — role-based routing ensures each case reaches the right team.

3. AI Analysis — contextual understanding of documents, identities, and prior events.

4. Decision and Resolution — human review or automated closure based on SOP thresholds.

5. Post-Resolution Learning — feedback loops update AI models to continuously improve decision-making accuracy.

Integrations

• Graph Intelligence: Automatically links related entities and historical cases for pattern discovery.

• Identity & Document Systems: Pulls verification and document metadata into each case.

• Customer SOP Models: Trains AI agents on your specific decision logic, thresholds, and compliance rules.

• Notifications & Escalations: Integrates with alerting systems (e.g., Slack, email, or ticketing tools) for real-time case handoffs.

Example Use Cases

1. Fraud Escalation Workflow

A potential identity mismatch triggers a case automatically.
AI agents summarize the verification data, graph connections, and previous cases — presenting an immediate decision suggestion to the analyst.

2. AML Review Process

Suspicious activity alerts generate cases with linked entities and transaction data.
AI highlights previous watchlist hits, automatically drafts a SAR (Suspicious Activity Report) summary, and queues it for approval.

3. Document Validation Case

When a user uploads an inconsistent document, a case is opened with extracted metadata, forgery analysis, and OCR results preloaded.
Analysts can resolve the case within seconds using prefilled context.