Parea Description
The prompt engineering platform allows you to experiment with different prompt versions. You can also evaluate and compare prompts in a series of tests, optimize prompts by one click, share and more. Optimize your AI development workflow. Key features that help you identify and get the best prompts for production use cases. Evaluation allows for a side-by-side comparison between prompts in test cases. Import test cases from CSV and define custom metrics for evaluation. Automatic template and prompt optimization can improve LLM results. View and manage all versions of the prompt and create OpenAI Functions. You can access all your prompts programmatically. This includes observability and analytics. Calculate the cost, latency and effectiveness of each prompt. Parea can help you improve your prompt engineering workflow. Parea helps developers improve the performance of LLM apps by implementing rigorous testing and versioning.
Parea Alternatives
Narrow AI
Narrow AI: Remove the Engineer from Prompt Engineering
Narrow AI automatically writes, monitors and optimizes prompts on any model. This allows you to ship AI features at a fractional cost.
Maximize quality and minimize costs
Reduce AI costs by 95% using cheaper models
Automated Prompt Optimizer: Improve accuracy
- Achieve faster response times with lower latency models
Test new models within minutes, not weeks
- Compare the performance of LLMs quickly
- Benchmarks on cost and latency for each model
- Deploy the optimal model for your usage case
Ship LLM features up to 10x faster
- Automatically generate expert level prompts
- Adapt prompts as new models are released
- Optimize prompts in terms of quality, cost and time
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Entry Point AI
Entry Point AI is a modern AI optimization platform that optimizes proprietary and open-source language models. Manage prompts and fine-tunes in one place. We make it easy to fine-tune models when you reach the limits. Fine-tuning involves showing a model what to do, not telling it. It works in conjunction with prompt engineering and retrieval augmented generation (RAG) in order to maximize the potential of AI models. Fine-tuning your prompts can help you improve their quality. Imagine it as an upgrade to a few-shot model that incorporates the examples. You can train a model to perform at the same level as a high-quality model for simpler tasks. This will reduce latency and costs. For safety, to protect the brand, or to get the formatting correct, train your model to not respond in a certain way to users. Add examples to your dataset to cover edge cases and guide model behavior.
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Literal AI
Literal AI is an open-source platform that helps engineering and product teams develop production-grade Large Language Model applications. It provides a suite for observability and evaluation, as well as analytics. This allows for efficient tracking, optimization and integration of prompt version. The key features are multimodal logging encompassing audio, video, and vision, prompt management, with versioning and testing capabilities, as well as a prompt playground to test multiple LLM providers. Literal AI integrates seamlessly into various LLM frameworks and AI providers, including OpenAI, LangChain and LlamaIndex. It also provides SDKs for Python and TypeScript to instrument code. The platform supports the creation and execution of experiments against datasets to facilitate continuous improvement in LLM applications.
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Langfuse
Langfuse is a free and open-source LLM engineering platform that helps teams to debug, analyze, and iterate their LLM Applications.
Observability: Incorporate Langfuse into your app to start ingesting traces.
Langfuse UI : inspect and debug complex logs, user sessions and user sessions
Langfuse Prompts: Manage versions, deploy prompts and manage prompts within Langfuse
Analytics: Track metrics such as cost, latency and quality (LLM) to gain insights through dashboards & data exports
Evals: Calculate and collect scores for your LLM completions
Experiments: Track app behavior and test it before deploying new versions
Why Langfuse?
- Open source
- Models and frameworks are agnostic
- Built for production
- Incrementally adaptable - Start with a single LLM or integration call, then expand to the full tracing for complex chains/agents
- Use GET to create downstream use cases and export the data
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Pricing
Free Trial:
Yes
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Company Details
Company:
Parea
Website:
www.parea.ai/
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