Search results for "zero"
⚡️ Open-source AI Gateway — Use any SDK to call 100+ LLMs. Built-in failover, load balancing, cost control & end-to-end tracing.
Framework for AI Backend. Build and run AI agents like microservices - scalable, observable, and identity-aware from day one.
LLM-powered framework for deep document understanding, semantic retrieval, and context-aware answers using RAG paradigm.
High-performance zero-dependency L4/L7 load balancer written in Go. Single binary with Web UI, clustering, MCP/AI integration. 8.5K RPS, 39 E2E tests.
Generate OpenAPI 3.1 specs from Go source code via static analysis — zero annotations, automatic framework detection
Design-first Go framework that generates API code, documentation, and clients. Define once in an elegant DSL, deploy as HTTP and gRPC services with zero drift between code and docs.
mkdir beats vector DB. B-tree NeuronFS: 0-byte folders govern AI — ₩0 infrastructure, ~200x token efficiency. OS-native constraint engine for LLM agents.
Milvus is a high-performance, cloud-native vector database built for scalable vector ANN search
Beads - A memory upgrade for your coding agent
Zero-dependency Web Application Firewall in Go. Single binary. Three deployment modes. Tokenizer-based detection.
A Go implementation of the Model Context Protocol (MCP), enabling seamless integration between LLM applications and external data sources and tools.
Open-source Agentic AI framework in Go for building, orchestrating, and deploying intelligent agents. LLM-agnostic, event-driven, with multi-agent workflows, MCP tool discovery, and production-grade o
Open-source, self-improving autonomous agent swarm🐇
One API for 25+ LLMs, OpenAI, Anthropic, Bedrock, Azure. Caching, guardrails & cost controls. Go-native LiteLLM & Kong AI Gateway alternative.
Artifical Ecology For Thought and Emergent Reasoning. The Colony That Builds With You.
The cognitive database. A new class of data storage. Not a vector store, not a graph DB, not a RAG wrapper. Ebbinghaus decay, Hebbian learning, and Bayesian confidence are engine-native primitives.
Model Context Protocol (MCP) server for Kubernetes and OpenShift
AI-native HTAP database with Git-for-Data and built-in vector search, serving as the data and memory backbone for intelligent agents and applications.
Automatically generate server and client framework code based on descriptive files (proto/api/sql), while using built-in jzero-skills to empower AI to generate production-ready business code adhering
A minimal, lightweight structured data store designed for small applications, scripts and automation workflows. Built for simplicity, portability and low overhead.
A selective learning and memory substrate for agentic systems — typed, revisable, decayable memory with competence learning and trust-aware retrieval.
Run AI coding agents in hardened container sandboxes.
Decentralized coordination protocol for autonomous agents
A Slack bot and MCP client acts as a bridge between Slack and Model Context Protocol (MCP) servers. Using Slack as the interface, it enables large language models (LLMs) to connect and interact with v