Advanced AI Configuration

Model Communication Protocol
Model Communication Protocol

MCP Configuration

Standardized Communication with Third-Party Systems

MCP (Model Communication Protocol) provides a standardized and scalable way for AI Agents to communicate with third-party services without being affected by API changes.

Instead of constantly updating configurations whenever a third-party API changes, MCP acts as a stable communication layer between your system and external platforms such as Google, Azure, Salesforce, or other enterprise systems.

With MCP, enterprises can build internal tools and APIs once and use them consistently across agents—ensuring reliability, scalability, and seamless integration.

Key Benefits

  • Check
    Future-proof integrations — Stay ahead of API changes with easy integrations
  • Check
    Standardized communication layer — Communicate seamlessly between internal systems and external APIs
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    Custom MCP server support — Adapt MCP to your unique business needs
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    Tool creation within MCP — Build reusable tools for consistent workflows
Your System
enterprise client · agents
→
std call
MCP Protocol Layer
Stable Standardized Scalable
API changes never affect agent configuration
→
adapted
Google
Azure
Salesforce
Custom API
Model Communication Protocol
Model Section

Configurable AI Models Tailored to Your Industry

Customize AI models for your business by selecting the right industry domain, adjusting settings, and activating features based on your unique requirements. Empower your team to make AI work for your specific industry needs.

From here, you can

  • Check Select the industry domain (e.g., Airlines, Banking, Loyalty, Retail)
  • Check Configure the model payload settings
  • Check Choose which features and parameters the model should analyse
  • Check Add or remove features based on customer requirements
model.config.json ⬤ Configuration
domain "banking"
payload { maxTokens: 4096, temp: 0.3 }
features {
→ sentimentAnalysis: true
→ intentClassification: true
→ entityExtraction: true
→ anomalyDetection: false
} // 3 of 5 features active

Third-Party Data Configuration Settings

Live Data Integration from External Platforms

This module allows AI Agents to fetch and respond using live data from third-party systems such as:

SIEBEL platforms
Salesforce
Loyalty systems
Any external data provider
CRM systems
SIEBEL
Salesforce
CRM
Loyalty
→
OpenSearch
Indexed
→
AI Agent
Live

When enabled

  • Third-party data is ingested into OpenSearch
  • Agents can access live updates in real time
  • Users receive responses based on the most recent data

Data Encryption

Enterprise-Grade Security for Sensitive Information 

Data Encryption ensures that sensitive information-such as financial data, credit card details, and personal identifiers-is never exposed to the LLM (Large Language Model).

This guarantees

User privacy protection
Regulatory compliance
Secure AI communication
Safe handling of financial and personal data

How It Works

  • Sensitive data is encrypted before processing
  • Only non-sensitive, privacy-safe data is sent to the AI model
  • Financial and confidential information remains protected
  • Multiple backend encryption methods ensure compliance

Guardrails Configuration

Intelligent AI Behaviour Control & Security Protection

Guardrails define how the AI Agent behaves—ensuring safe, secure, and policy-compliant interactions.

There are two types of guardrails:

Input Guardrails
Output Guardrails
Input
Prevents malicious or manipulative user prompts such as:
  • Prompt injection attacks
  • Jailbreaking attempts
  • Instruction overrides
  • Unauthorized data deletion requests
Output
Prevents the AI from generating:
  • Harmful or inappropriate content
  • Privacy-violating responses
  • Privacy-violating responses Privacy-violating responses
  • Cybersecurity-sensitive outputs

AI Agents – Agent Flow (Generate Agent Flow)

Design Structured Workflows for Intelligent Automation

Agent Flow allows administrators to visually configure how an AI Agent processes requests. It transforms AI Agents from simple chat responders into intelligent, task-executing digital assistants.

This Enables

Multi-step reasoning
Automated action execution
Context-aware responses
End-to-end workflow automation

Using Agent Flow, you can

  • Define topics and actions
  • Add anomaly detection logic
  • Integrate MCP tools
  • Connect third-party APIs
  • Configure response paths
  • Control decision logic
Guardrails Pipeline
User
Input Guardrail
AI Model
Output Guardrail
Safer Response

Build Smarter, Safer & More
Intelligent AI Agents

From anomaly detection and voice verification to MCP-powered integrations and configurable agent workflows—these modules give enterprises complete control over how their AI Agents operate.

Configure Secure Automate Scale
See the AI Platform in Action