🚀 Next Generation Multi-tenant AI One-Stop Solution. Builtin Admin & Billing System. Enterprise-Grade Unified LLM Gateway Support for 200+ Models And 35+ Providers, Load Balacing w/ Priority-base Routing, Cost Management, Chat Share, Cloud Sync, Credit/Subscription Billing, All File Parsing, Web Search, Built-in Model Cache.

Koog is a JVM (Java and Kotlin) framework for building predictable, fault-tolerant and enterprise-ready AI agents across all platforms – from backend services to Android and iOS, JVM, and even in-browser environments. Koog is based on our AI products expertise and provides proven solutions for complex LLM and AI problems

LLM Development, Design Patterns and Best Practices, First Edition - Published by Packt

LangChain-lite for ABAP: Enterprise LLM orchestration framework with lazy execution, powerful templating, caching, and token prediction. Build complex AI workflows in SAP ERP, SAP S/4.

A Java 8+ LangChain implementation. Build powerful LLM based applications in an (enterprise) Java context.

Lightweight BApp that seamlessly integrates powerful LLM-scanning capabilities into Burp's built-in Scanner with improved accuracy. Supports the latest LLMs from OpenAI (gpt-4o, o1), Anthropic (Claude 3.5, Claude 3), and Google (Gemini 1.5). Requires valid API key(s) and an active Burp Suite Pro or Enterprise license.

Redefine agentic evaluation in enterprise AI. By simulating realistic scenarios, these evals enables rigorous, multi-dimensional assessment of LLM-powered productivity agents.

Corporate Trainer and Consultant with 19+ years of experience specializing in Generative AI, LLMs, MLOps, LangChain, and enterprise AI enablement.

Production-grade multi-agent orchestration engine. Compose agentic workflows from a pluggable catalog of Agents, LLMs, tools, and retrievers. Execute locally with LangGraph or distributed with Temporal. Built-in RAG pipeline for enterprise knowledge retrieval. A2A and MCP protocol support. Visual drag-and-drop blueprint builder.

High-performance LLM Gateway built in Go - OpenAI compatible proxy with multi-provider support, adaptive routing, and enterprise features

This Guidance demonstrates how to build an application for search based on the information in an enterprise knowledge base through the deployment of interface nodes, including large language models (LLMs).

MedGuard is a robust, production-grade Python library that ensures HIPAA compliance for large language model (LLM) agents. Designed for enterprise applications in healthcare, MedGuard provides comprehensive security, privacy, and compliance frameworks that integrate seamlessly into your AI-driven workflows.

An orchestration platform for AI agents in the enterprise. Slack bot that integrates with GitHub Models API. Analyses channel messages, modifies files via PRs, and answers general questions using an LLM agent with tool calling.

Unveiling Challenges for LLMs in Enterprise Data Engineering

🤖 Enterprise-grade AI Agent Service based on FastMCP framework. Features 25+ MCP tools, 10 professional agents, dual LLM modes (Cursor built-in + DeepSeek API), and seamless Cursor IDE integration. 企业级智能体调用服务，支持双LLM模式，提供25+专业MCP工具和10个专业智能体。

FireBench: Evaluating Instruction Following in Enterprise and API-Driven LLM Applications

Enterprise-grade FastAPI backend with Zero Trust security, multi-LLM provider support (OpenAI/Ollama/Local), and built-in threat protection. Features GPU-resistant Argon2 auth, scoped tokens, LLM firewall, rate limiting.

REST API tailored for enterprise professionals in managerial roles. Uses LLMs to convert Gmail emails into Jira tickets for you and your team.

**Description:** A Neuro-Symbolic framework that uses High-Dimensional Geometry and Statistical Physics to ground LLMs, preventing hallucinations and sycophancy in enterprise agents. **Topics:** `llm`, `neuro-symbolic`, `ai-safety`, `azure-openai`, `hallucination-mitigation`

🚀 Integration of Odoo, Power BI, and LLM for enterprise data management. Visualize Odoo data in Power BI, query it intuitively via LLM, and analyze it with Machine Learning in Python. Enhancing decision-making and predictive analytics! 📊🤖

production-ready Retrieval-Augmented Generation (RAG) chatbot microservice built with FastAPI, designed for enterprise workloads requiring high performance, scalability, and reliability. The service delivers real-time streaming responses, robust LLM caching, advanced vector search, and a seamless knowledge ingestion pipeline, all wrapped in a clean

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AI Agent In Action: LLM-based Application Guide for Enterprise Development

Define enterprise-level multi-agent orchestration architecture for managing and governing LLM networks with human-in-the-loop control.

In this project, we develop an enterprise benchmark framework for large language model (LLM) evaluation. We extend HELM, an open-source benchmark framework developed by Stanford CRFM, to enable users evaluate LLMs with domain-specific datasets such as finance, legal, climate, and cybersecurity.

GoRAG is a production-ready, high-performance RAG (Retrieval-Augmented Generation) framework built entirely in Go. Designed for enterprise scalability, it seamlessly connects your internal data to the most powerful LLMs with zero Python dependencies.

Advanced four-layer AI-powered guardrails for multi-agent systems designed to prevent destructive behaviors in large language models (LLMs). The framework includes prompt validation, backdoor attack detection, hallucination prevention, and multi-agent context validation within agentic workflows on enterprise software.

A lightweight RAG for enterprise executives and employees who require powerful AI in productivity tasks. uses TinyLlama:1.1b as it's LLM. Uses Gemma Embedding 300m. Lightweight models ensure fast inference on mobile CPU's

Achieving Operational Maturity in ML + LLM Platforms: A Deep Dive into Enterprise-Grade Components

Splunk Technology Add-on for monitoring Ollama LLM deployments. Features file monitoring of server logs, HEC integration for custom telemetry, and CIM compliance for enterprise security. Provides HTTP access log parsing, prompt analytics, and built-in data redaction. Compatible with Splunk Cloud Platform