Free
$0
- 1,000 pages
- 10,000 retrievals
- Community support
Overview
Agentset is an open-source infrastructure designed for developers to create production-ready Retrieval Augmented Generation (RAG) applications, specifically for powering search and Q&A functionalities within their products. Unlike many RAG systems that perform well in demos but struggle with real-world usage and large document sets, Agentset is built to deliver reliable answers at scale, even as data volume, user activity, and complexity increase. It aims to simplify the development process by providing a robust RAG pipeline without requiring developers to build or maintain it from scratch.
Key Capabilities
The platform offers several key features to ensure accuracy and reliability. It provides multimodal support, allowing it to process and answer questions from various data types including images, graphs, tables, and text, covering an entire knowledge base. Agentset automatically cites sources for its answers, enabling users to verify information. It also supports metadata filtering, which allows answers to be based on specific subsets of data.
Developer Experience
For developers, Agentset offers JavaScript and Python SDKs, supporting over 22 file formats for data upload. It is model-agnostic, giving developers the flexibility to choose their preferred vector database, embedding model, and Large Language Model (LLM). The platform also integrates with the AI SDK and provides an MCP server to extend knowledge bases to external applications, enhancing its utility for diverse development environments.
Key features
- Accurate Answers on custom data
- Multimodal Support for images, graphs, tables, and text
- Automatic Citations for answer sources
- Metadata Filtering for data subsets
- Preview Links for external feedback
- 22+ File Format Support for data upload
- Model Agnostic LLM, embedding, and vector database integration
- JavaScript and Python SDKs
Who uses it
Developers, particularly those building AI applications for search and Q&A, and large enterprises requiring reliable RAG solutions for extensive data corpuses.
Pros
- Delivers high accuracy on diverse data, including industry benchmarks.
- Supports multimodal content, processing images, graphs, and tables alongside text.
- Automatically cites sources for answers, enhancing verifiability.
- Offers flexibility with model-agnostic LLM, embedding, and vector database choices.
- Provides SDKs for JavaScript and Python with support for over 22 file formats.
Cons
- Requires scheduling a demo for access, without an immediate self-service trial option.
- Primarily focused on RAG, which may not cover all potential AI application development needs.
- While simplifying RAG, integrating and customizing for complex enterprise requirements may still demand significant developer effort.
Our take
Agentset offers a robust, open-source solution for developers to implement production-grade RAG systems, ensuring reliable AI-powered search and Q&A capabilities for complex data environments.
Pricing plans
Pro
$49/Month
- 10,000 pages
- Unlimited retrievals
- Email support
Enterprise
Custom Contact Sales
- Unlimited pages and retrievals
- On-premise or BYOC
- SOC 2, HIPAA, and GDPR reports
- Single-sign on
- Dedicated engineering support
Pricing details are provided for reference and may differ from the vendor's current plans.
Comments
Similar tools
62.6M/mo·+2.1M (+3.5%)·25.4%
Amazon Web Services provides reliable, scalable, and inexpensive cloud computing services, enabling organizations to innovate and scale efficiently.
203K/mo·+10.1K (+5.3%)·36.3%
Deepnote is a collaborative analytics and data science notebook that allows teams to explore data, automate insights, and make better decisions.
Rebellions provides AI accelerator hardware and full-stack software for data centers, optimized for efficient and scalable AI inference workloads.
Serpex offers a real-time search API that delivers clean, structured JSON results and comprehensive page content extraction for AI and data projects.
Orq.ai provides an AI control plane and sovereign AI gateway for enterprises to govern AI models, agents, and software development at scale.
Hugging Face is a collaborative platform for the machine learning community to share and build models, datasets, and applications.
Cohere provides an enterprise AI platform with powerful language models and agentic capabilities for automating processes and extracting insights from data.
Powabase is an AI-native backend-as-a-service providing per-project Postgres, authentication, storage, RAG, and agents for AI applications.
API · Agents · Open Source · On Premise · No Signup Required
50.7K/mo·-3.3K (-6.1%)·57.2%
Lambda provides cloud-based supercomputers and GPU instances for training and scaling advanced AI models and inference workloads.
Flexor transforms unstructured enterprise data into AI-ready context, enabling AI agents to reason freely and drive accurate, consistent decisions.
Versuno provides memory and context infrastructure for AI, featuring an open-source engine for agents and a forthcoming hosted cloud service.