Multi-LLM Orchestration: OpenAI & Anthropic

Multi-LLM Orchestration: Semawork Orchestrates OpenAI and Anthropic

As AI adoption grows, many organizations use multiple LLM providers—OpenAI GPT-4 for complex reasoning, Anthropic Claude for long context, and efficient models for simple tasks. But coordinating multiple models in a single workflow can be complex.

Semawork orchestrates OpenAI, Anthropic, and multiple models with intelligent routing, cost optimization, and unified observability.

The Challenge: Multi-Model Coordination

Using multiple LLM providers creates challenges:

• Routing decisions - Which model should handle which task?
• Cost optimization - How to balance quality and cost?
• Coordination - How to combine outputs from multiple models?
• Observability - How to track usage and performance across providers?

Without orchestration, you end up with ad-hoc model selection and no unified visibility.

Semawork's Multi-LLM Orchestration

Semawork provides intelligent coordination across multiple LLM providers:

Intelligent Routing

Route tasks to the best model for the job:

• GPT-4 for complex reasoning and code generation
• Claude for long context and document analysis
• Efficient models for simple tasks and cost optimization

Example: Document analysis workflow routes to Claude for long context, then uses GPT-4 for complex reasoning on extracted insights.

Cost Optimization

Optimize spend across providers:

• Premium models only when needed
• Efficient models for routine tasks
• Automatic routing based on task complexity
• Cost tracking across all providers

Result: 40% cost reduction while maintaining quality.

Multi-Model Coordination

Combine outputs from multiple models:

• Ensemble approaches - Use multiple models for critical decisions
• Output comparison - Compare results for consensus
• Fallback strategies - Route to alternative models if needed
• Unified responses - Combine model outputs intelligently

Example: Critical decision workflow uses both GPT-4 and Claude, compares outputs, and applies business logic for final determination.

Unified Observability

Single audit trail across all LLM operations:

• Usage tracking - Monitor usage across all providers
• Performance metrics - Compare model performance
• Cost analysis - Track spend by model and use case
• Audit trails - Complete records for compliance

Real-World Example

Use Case: Customer support ticket analysis

Orchestration flow:

1. Semawork receives ticket - Support ticket arrives
2. Intelligent routing - Routes to Claude for long context analysis (ticket history, customer data)
3. Multi-model coordination - Uses GPT-4 for complex reasoning (sentiment, urgency, routing decision)
4. Legacy integration - Fetches customer data from CRM APIs
5. Unified response - Combines model outputs, applies business rules, returns routing recommendation

Result: Intelligent ticket routing with multi-model coordination and cost optimization.

Benefits

• 40% cost reduction - Optimize spend by routing to appropriate models
• 2x quality improvement - Multi-model consensus for critical decisions
• 100% unified observability - Single audit trail across all LLM operations
• Intelligent coordination - Best model for each task automatically

Getting Started

Ready to orchestrate multiple LLMs?

See multi-LLM orchestration details or book a call to discuss your model coordination needs.