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atexa
For Technical Teams

Seamless Integration with Existing Systems & Workflows

Built for developers, by developers. Vatexa's AI solutions integrate seamlessly with your existing tech stack, providing powerful APIs, comprehensive documentation, and enterprise-grade security.

99.9%

Uptime with enterprise-grade infrastructure

< 24h

Average integration time with existing systems

SOC 2

Type II compliant with enterprise security

Artemis for Technical Integration

Developer-First AI Analytics Platform

Artemis provides robust APIs, SDKs, and comprehensive documentation for seamless integration. Built with modern architecture and enterprise-grade security for mission-critical applications.

RESTful APIs & GraphQL

Comprehensive APIs with real-time data access and flexible query capabilities

Multi-Platform SDKs

Native SDKs for Python, JavaScript, Java, .NET, and more

Enterprise Security

SOC 2 Type II, GDPR compliant with end-to-end encryption

API Integration Dashboard
Voice AI Technical Integration
Swara for Technical Implementation

Voice AI with Enterprise-Grade Architecture

Swara's voice AI platform is built for scale and reliability. Integrate voice capabilities into your applications with minimal code and maximum flexibility.

WebRTC & SIP Integration

Native support for modern communication protocols and legacy systems

Webhook & Event Streaming

Real-time event notifications and data streaming for seamless integration

Custom Voice Models

Train and deploy custom voice models for your specific use cases

Get Started in Minutes

Simple, powerful APIs that integrate with your existing infrastructure

Python SDK Example
import vatexa

# Initialize Artemis client
artemis = vatexa.Artemis(api_key="your_api_key")

# Get real-time analytics
analytics = artemis.get_analytics(
    metrics=["revenue", "conversion_rate"],
    timeframe="last_30_days"
)

# Initialize Swara voice agent
swara = vatexa.Swara(api_key="your_api_key")

# Create voice agent
agent = swara.create_agent(
    name="Customer Support",
    voice_model="professional",
    language="en-US"
)

print(f"Analytics: {analytics}")
print(f"Agent created: {agent.id}")

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