What If You Could Ask Every AI Model at Once?
Atlas AI Synthesis
Different AI models excel at different tasks. We built a platform that routes questions to the best model, or combines answers from multiple models into one synthesized response. Users get the best of OpenAI GPT, Anthropic Claude, Google Gemini, and more in a single interface.
At a Glance
Key results and metrics from this project.
The Challenge
Users were switching between ChatGPT, Claude, and Gemini to get the best answers. Each model has strengths and weaknesses. GPT models excel at coding, Claude at nuanced reasoning, Gemini at research. But combining them manually was tedious and time-consuming. There was no unified interface to leverage the best of each.
The Solution
What we built to solve the challenge.
- Clean chat interface with model selection
- Side-by-side response comparison view
- Synthesized answer display with sources
- Conversation history and favorites
- Multi-model API orchestration
- Response caching for cost optimization
- Usage tracking and billing
- Custom prompt templates
- Query classification for optimal routing
- Multi-model response synthesis
- Confidence scoring and source attribution
- Continuous model performance benchmarking
Key Capabilities
Technology Stack
The Business Impact
Measurable results and transformation.
The platform delivers 40% better response quality by intelligently routing queries to the optimal model or synthesizing answers from multiple models. API costs dropped 30% through smart caching and routing, while user productivity doubled.
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