Epsilla is an all-in-one platform that enables the rapid development and deployment of production-ready AI agents using private data and knowledge, leveraging vertical large language models (LLMs) and advanced retrieval-augmented generation (RAG) techniques. The platform addresses inefficiencies in data management and application development, allowing users to create AI solutions up to ten times faster while significantly reducing operational costs.
Funding
$500K raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Developing and deploying AI agents that leverage private data and knowledge is complex, often requiring significant engineering effort to manage large language models (LLMs), retrieval-augmented generation (RAG), and data integrations. Existing AI agent-building tools often lack customization, flexibility, or focus on only a small aspect of the problem, leaving developers to integrate disparate components.
Solution
Epsilla offers an all-in-one platform designed to streamline the creation, iteration, and operation of AI agents using private data, without requiring extensive coding. The platform enables users to build high-quality knowledge bases from diverse data sources, customize AI agents with modular RAG techniques, and evaluate agent performance. Epsilla integrates with various LLM providers, allowing users to select the optimal model based on quality, latency, and cost considerations.
Target Audience
Epsilla targets GenAI developers, small businesses, vertical industry startups, and enterprise teams seeking to build and deploy AI agents connected to private or public data.
Features
- No-code RAG platform for building production-ready AI applications
- Multi-source data integration, connecting to files, websites, cloud storage, and more
- High-performance vector database for efficient information retrieval
- Integration with LLMs from providers like OpenAI, Anthropic, MistralAI, Cohere, and Google
- Horizontally scalable data infrastructure to handle large datasets
- CI/CD-style evaluations for confident configuration changes and faster iteration
- Fine-grained, role-based access control and support for private cloud and on-premises deployment