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Service

Multi-LLM Orchestration

Use Claude, Gemini, and GPT together — intelligent routing sends each task to the best model, with automatic failover and cost optimization built in.

3+

LLM Providers

High

Availability via Failover

Up to 60%

Cost Reduction

Best

Model Per Task

Locked into one AI provider is a liability

Single-vendor AI means you're stuck with one model's strengths and weaknesses. When that model degrades, hallucinates, or increases pricing, you have no fallback.

Multi-LLM gives you options. The right model for the right task, automatic failover when providers have issues, and the leverage to negotiate pricing because you're never locked in.

The Stack

Three models, one orchestration layer

Each model has distinct strengths. We route tasks to the model that handles them best — so you get better results at lower cost.

Claude (Anthropic)

Best for

Long-form analysis, complex reasoning, document understanding, safety-critical tasks.

Used for

Meeting summaries, proposal drafting, compliance reviews.

Gemini (Google)

Best for

Data analysis, structured extraction, multi-modal understanding, search-grounded responses.

Used for

CRM data analysis, market research, competitive intelligence.

GPT (OpenAI)

Best for

Creative content, conversational AI, code generation, broad general knowledge.

Used for

Email drafting, chatbots, content generation.

Capabilities

Everything you need to run multiple models in production

From intelligent routing to compliance logging, the orchestration layer handles the complexity so your team doesn't have to.

Intelligent Routing

Each task is automatically sent to the best model based on type, complexity, and cost. Your team doesn’t need to know which model is working.

Task classificationModel matchingCost optimizationLatency routing

Automatic Failover

If one provider goes down, requests automatically route to the next best model. Zero downtime, zero intervention.

Health monitoringInstant failoverProvider diversitySLA protection

Cost Optimization

Simple tasks use cheaper models. Complex tasks use powerful ones. You stop overpaying for AI by matching cost to complexity.

Task complexity scoringModel cost trackingBudget controlsUsage analytics

Unified API Layer

One API, multiple models. Your applications don’t care which model responds — they get consistent, structured output every time.

Schema normalizationResponse formattingError handlingRate limiting

Evaluation & Testing

We continuously benchmark models against your specific use cases to ensure you’re using the best option as models improve.

A/B testingQuality scoringDrift detectionModel comparison

Compliance & Logging

Every request and response is logged with model, latency, cost, and quality metrics. Full audit trail for regulated industries.

Audit loggingData residencyPII detectionRetention policies
Our Process

How we implement multi-LLM orchestration

From inventory to optimization, we build the routing layer that makes multiple models work as one.

01

AI Inventory

We catalog your current AI usage and planned use cases. What models are you using? What tasks do they handle?

02

Architecture Design

We design the routing layer, failover strategy, and cost model. You approve the approach before we build.

03

Implementation

We build the orchestration layer, integrate with your systems, and validate with real traffic.

04

Optimize & Scale

We monitor model performance, adjust routing rules, and add new models as the landscape evolves.

Case Study
58% Reduction in AI Costs
B2B SaaS — AI-Powered Product Features

Challenge

Company was routing all AI tasks through GPT-4, paying premium pricing for tasks that didn’t need premium capability. No fallback when OpenAI had outages.

Solution

Implemented multi-LLM orchestration: simple classification tasks routed to Haiku, analysis to Claude Sonnet, creative content to GPT-4. Added Gemini as failover for all routes.

Result

AI costs dropped 58% without quality loss. System maintained full uptime during two major provider outages. Response latency improved 34% by using faster models for simple tasks.

FAQ

Common questions about multi-LLM

Everything you need to know about running multiple AI models in production.

Talk to Us About Multi-LLM

The “best” model depends on the task. Claude excels at reasoning and safety. GPT excels at creative content. Gemini excels at structured data. Using one model for everything means you’re paying premium prices for tasks that don’t need premium capability, and you’re getting worse results for tasks that don’t match that model’s strengths.

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