Find the most suitable architecture for AI-Native functionality.
Find the most suitable architecture for AI-Native functionality.
Don’t vibe-check your AI agents. Design variations, benchmark them, and see how your agent actually behaves
Not for no-code AI, but for the right AI
Design the AI before writing the code. Measure it in terms of cost, throughput, and latency, and compare different designs.
Not for no-code AI, but for the right AI.
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Core features
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Core features
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Core features
Stop Guessing AI Infra. Design it, bench it.
Stop Guessing AI Infra. Design it, bench it.
Eliminate the guesswork from your AI stack.
Platform lock-in is a trap. Q-Bench lets you benchmark the entire industry objectively. Whether it's latency, cost, or accuracy you need, get mathematical proof that you’ve chosen the absolute best architecture for your users.
Eliminate the guesswork from your AI stack.
Platform lock-in is a trap. Q-Bench lets you benchmark the entire industry objectively. Whether it's latency, cost, or accuracy you need, get mathematical proof that you’ve chosen the absolute best architecture for your users.
Ditch the Spreadsheets. Visualize Trade-offs in One Click.
Stop wasting hours maintaining manual scripts and complex Excel sheets. Get a unified dashboard that instantly reveals Cost, Latency, and Quality metrics (RAGAs, DeepEval). Spot the winning configuration in seconds and get back to building.
Ditch the Spreadsheets. Visualize Trade-offs in One Click.
Stop wasting hours maintaining manual scripts and complex Excel sheets. Get a unified dashboard that instantly reveals Cost, Latency, and Quality metrics (RAGAs, DeepEval). Spot the winning configuration in seconds and get back to building.
Tame the Stochastic Nature of LLMs
Avoid the 'lucky run' trap. Q-Bench clusters across your agent architectures and lets you see the overall behavior. By clustering runs based on Token, Output, or Reasoning values, we reveal different sets of behaviors your agents exhibit in production.
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Use cases
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Use cases
How it works?
Workspace
Organize your workspace with the folder structure you're used to. Create your designs in .design pages, perform your benchmarks in .bench files, and customize your workspace exactly how you want it.
Design
Design and orchestrate your AI agents visually. Connect LangChain, LlamaIndex, or any custom platform to build complex RAG flows. See real-time cost estimates and execution results as you build.
Bench
On the Bench page, select your design via the Bench Node, then enter the execution mode and count. Your design will run as many times as specified, with results clustered by token usage. This allows you to group outputs based on similar token-cost data and inspect all variations within each cluster.
Workspace
Organize your workspace with the folder structure you're used to. Create your designs in .design pages, perform your benchmarks in .bench files, and customize your workspace exactly how you want it.
Design
Design and orchestrate your AI agents visually. Connect LangChain, LlamaIndex, or any custom platform to build complex RAG flows. See real-time cost estimates and execution results as you build.
Bench
On the Bench page, select your design via the Bench Node, then enter the execution mode and count. Your design will run as many times as specified, with results clustered by token usage. This allows you to group outputs based on similar token-cost data and inspect all variations within each cluster.
Workspace
Organize your workspace with the folder structure you're used to. Create your designs in .design pages, perform your benchmarks in .bench files, and customize your workspace exactly how you want it.
Design
Design and orchestrate your AI agents visually. Connect LangChain, LlamaIndex, or any custom platform to build complex RAG flows. See real-time cost estimates and execution results as you build.
Bench
On the Bench page, select your design via the Bench Node, then enter the execution mode and count. Your design will run as many times as specified, with results clustered by token usage. This allows you to group outputs based on similar token-cost data and inspect all variations within each cluster.
Workspace
Organize your workspace with the folder structure you're used to. Create your designs in .design pages, perform your benchmarks in .bench files, and customize your workspace exactly how you want it.
Design
Design and orchestrate your AI agents visually. Connect LangChain, LlamaIndex, or any custom platform to build complex RAG flows. See real-time cost estimates and execution results as you build.
Bench
On the Bench page, select your design via the Bench Node, then enter the execution mode and count. Your design will run as many times as specified, with results clustered by token usage. This allows you to group outputs based on similar token-cost data and inspect all variations within each cluster.
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Use cases
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Use cases
How it works?
1- Create Your Workspace
2- Create your Design
3- Benchmark to the Design
First, I'm setting up my workspace. I'll start by building a core LLamaIndex Agent, and then I might create a LangChain Agent that performs the same function for comparison. I created basic_langchain.design and i'll create basic_llamaindex.design
Organize your workspace with the folder structure you're used to. Create your designs in .design pages, perform your benchmarks in .bench files, and customize your workspace exactly how you want it.
1- Create Your Workspace
2- Create your Design
3- Benchmark to the Design
First, I'm setting up my workspace. I'll start by building a core LLamaIndex Agent, and then I might create a LangChain Agent that performs the same function for comparison. I created basic_langchain.design and i'll create basic_llamaindex.design
Organize your workspace with the folder structure you're used to. Create your designs in .design pages, perform your benchmarks in .bench files, and customize your workspace exactly how you want it.
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Benefits
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Benefits
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Benefits
To focus on the right architecture
To focus on the right architecture
Platform Integrations
LangChain, LlamaIndex and other Agent-AI development frameworks integrations
Platform Integrations
LangChain, LlamaIndex and other Agent-AI development frameworks integrations
Platform Integrations
LangChain, LlamaIndex and other Agent-AI development frameworks integrations
Evaluation Integrations
Integrations with indrustrial evaluation framework like RAGA's, DeepEval and etc
Evaluation Integrations
Integrations with indrustrial evaluation framework like RAGA's, DeepEval and etc
Evaluation Integrations
Integrations with indrustrial evaluation framework like RAGA's, DeepEval and etc
Emails
Get price alerts for your stack and auto-rebenchmark on every change.
Emails
Get price alerts for your stack and auto-rebenchmark on every change.
Emails
Get price alerts for your stack and auto-rebenchmark on every change.
API and MCP
Connect to your own applications with abstract APIs and MCP tools. Connect your servers in your designs
API and MCP
Connect to your own applications with abstract APIs and MCP tools. Connect your servers in your designs
API and MCP
Connect to your own applications with abstract APIs and MCP tools. Connect your servers in your designs
Effortless Architecture
Build, modify, and iterate on every possible architectural variation in minutes.
Effortless Architecture
Build, modify, and iterate on every possible architectural variation in minutes.
Effortless Architecture
Build, modify, and iterate on every possible architectural variation in minutes.
Behavioral Insights
Benchmark architectures to see production behavior. Forecast costs, outputs, and performance
Behavioral Insights
Benchmark architectures to see production behavior. Forecast costs, outputs, and performance
Behavioral Insights
Benchmark architectures to see production behavior. Forecast costs, outputs, and performance
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FAQ
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FAQ
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FAQ
Questions? We've got answers.
Questions? We've got answers.
Why create a Design for the AI function?
Why should I run benchmarks before writing code?
Which platforms can I use to improve what?
Can I integrate my own custom API or local model?
When will the full version be released?
Which data sources are supported for RAG benchmarking
Why create a Design for the AI function?
Why should I run benchmarks before writing code?
Which platforms can I use to improve what?
Can I integrate my own custom API or local model?
When will the full version be released?
Which data sources are supported for RAG benchmarking
Why create a Design for the AI function?
Why should I run benchmarks before writing code?
Which platforms can I use to improve what?
Can I integrate my own custom API or local model?
When will the full version be released?
Which data sources are supported for RAG benchmarking
Start AI Design with Q-Bench
Stop guessing, start benchmarking. Sign up to get early access and stabilize your AI Agent performance before you scale.
Start AI Design with Q-Bench
Stop guessing, start benchmarking. Sign up to get early access and stabilize your AI Agent performance before you scale.