Backmesh is a thoroughly tested Backend as a Service (BaaS) that offers an LLM API Gatekeeper, allowing your app to securely call LLM APIs. Using JWT authentication, configurable rate limits, and API resource access control, Backmesh ensures that only authorized users have access while preventing API abuse. Additionally, it provides LLM user analytics without extra packages, enabling identification of usage patterns, cost reduction, and improvements in user satisfaction.

At its core, Memary provides a modular memory management system tailored for large language model agents. By abstracting memory interactions through a common API, it supports multiple storage backends, including in-memory dictionaries, Redis for distributed caching, and vector stores like Pinecone or FAISS for semantic search. Users define schema-based memories (episodic, semantic, or long-term) and leverage embedding models to populate vector stores automatically. Retrieval functions allow contextually relevant memory recall during conversations, enhancing agent responses with past interactions or domain-specific data. Designed for extensibility, Memary can integrate custom memory backends and embedding functions, making it ideal for developing robust, stateful AI applications such as virtual assistants, customer service bots, and research tools requiring persistent knowledge over time.

Backender is a no-code solution designed to automate backend development. It streamlines processes such as server provisioning, database management, and integration with various services. Using Backender, developers and non-developers alike can build and manage backend systems without needing to write code. The platform provides a user-friendly interface to set up backend logic, handle file storage, and ensure system scalability, making it an essential tool for both small projects and enterprise-level applications.