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Average Ratings 0 Ratings

Total
ease
features
design
support

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Write a Review

Description

Agenta provides a complete open-source LLMOps solution that brings prompt engineering, evaluation, and observability together in one platform. Instead of storing prompts across scattered documents and communication channels, teams get a single source of truth for managing and versioning all prompt iterations. The platform includes a unified playground where users can compare prompts, models, and parameters side-by-side, making experimentation faster and more organized. Agenta supports automated evaluation pipelines that leverage LLM-as-a-judge, human reviewers, and custom evaluators to ensure changes actually improve performance. Its observability stack traces every request and highlights failure points, helping teams debug issues and convert problematic interactions into reusable test cases. Product managers, developers, and domain experts can collaborate through shared test sets, annotations, and interactive evaluations directly from the UI. Agenta integrates seamlessly with LangChain, LlamaIndex, OpenAI APIs, and any model provider, avoiding vendor lock-in. By consolidating collaboration, experimentation, testing, and monitoring, Agenta enables AI teams to move from chaotic workflows to streamlined, reliable LLM development.

Description

Vivgrid serves as a comprehensive development platform tailored for AI agents, focusing on critical aspects such as observability, debugging, safety, and a robust global deployment framework. It provides complete transparency into agent activities by logging prompts, memory retrievals, tool interactions, and reasoning processes, allowing developers to identify and address any points of failure or unexpected behavior. Furthermore, it enables the testing and enforcement of safety protocols, including refusal rules and filters, while facilitating human-in-the-loop oversight prior to deployment. Vivgrid also manages the orchestration of multi-agent systems equipped with stateful memory, dynamically assigning tasks across various agent workflows. On the deployment front, it utilizes a globally distributed inference network to guarantee low-latency execution, achieving response times under 50 milliseconds, and offers real-time metrics on latency, costs, and usage. By integrating debugging, evaluation, safety, and deployment into a single coherent framework, Vivgrid aims to streamline the process of delivering resilient AI systems without the need for disparate components in observability, infrastructure, and orchestration, ultimately enhancing efficiency for developers. This holistic approach empowers teams to focus on innovation rather than the complexities of system integration.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Cerebras
ChatGPT
Claude
DeepSeek R1
DeepSeek-V3
GPT-4.1
Gemini 2.5 Flash
Gemini 2.5 Pro
Gemini 3 Deep Think
Gemini 3 Pro
Gemini 3.1 Flash-Lite
Hugging Face
LangChain
Llama
Llama 2
Llama 3.1
Llama 3.2
Llama 3.3
OpenAI
Python

Integrations

Cerebras
ChatGPT
Claude
DeepSeek R1
DeepSeek-V3
GPT-4.1
Gemini 2.5 Flash
Gemini 2.5 Pro
Gemini 3 Deep Think
Gemini 3 Pro
Gemini 3.1 Flash-Lite
Hugging Face
LangChain
Llama
Llama 2
Llama 3.1
Llama 3.2
Llama 3.3
OpenAI
Python

Pricing Details

Free
Free Trial
Free Version

Pricing Details

$25 per month
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

Agenta

Founded

2023

Country

Germany

Website

agenta.ai/

Vendor Details

Company Name

Vivgrid

Country

United States

Website

www.vivgrid.com

Alternatives

Alternatives