Best AI tools for< Monitoring Engineer >

Portkey is a monitoring and improvement tool for Gen AI apps, helping teams enhance cost, performance, and accuracy. It integrates quickly, monitors LLM requests, and boosts app resilience, security, performance, and accuracy. The tool offers a product walkthrough and easy integration with OpenAI Python and Node libraries.

Bugpilot is an error monitoring tool specifically designed for React applications. It offers a comprehensive platform for error tracking, debugging, and user communication. With Bugpilot, developers can easily integrate error tracking into their React applications without any code changes or dependencies. The tool provides a user-friendly dashboard that helps developers quickly identify and prioritize errors, understand their root causes, and plan fixes. Bugpilot also includes features such as AI-assisted debugging, session recordings, and customizable error pages to enhance the user experience and reduce support requests.

Frigate is an open source NVR application that focuses on locally processed AI object detection for security camera monitoring. It allows users to run advanced analysis on their camera feeds without sending data to the cloud, reducing false positives and providing precise notifications. Frigate offers custom models with Frigate+ and integrates with popular home automation platforms for enhanced functionality.

Langtrace AI is an open-source observability tool powered by Scale3 Labs that helps monitor, evaluate, and improve LLM (Large Language Model) applications. It collects and analyzes traces and metrics to provide insights into the ML pipeline, ensuring security through SOC 2 Type II certification. Langtrace supports popular LLMs, frameworks, and vector databases, offering end-to-end observability and the ability to build and deploy AI applications with confidence.

Code Snippets AI is an AI-powered code snippets library for teams. It helps developers master their codebase with contextually-rich AI chats, integrated with a secure code snippets library. Developers can build new features, fix bugs, add comments, and understand their codebase with the help of Code Snippets AI. The tool is trusted by the best development teams and helps developers code smarter than ever. With Code Snippets AI, developers can leverage the power of a codebase aware assistant, helping them write clean, performance optimized code. They can also create documentation, refactor, debug and generate code with full codebase context. This helps developers spend more time creating code and less time debugging errors.

Observance is an AI-powered construction management platform developed by Inkers.ai. It integrates advanced AI technologies to provide features such as 4D BIM, Snag List, Project Milestones, Scan to BIM, Thermals Analytics, and Deviation Analysis. The platform offers real-time tracking, smart scheduling, BIM integration, analytics dashboard, and next-generation construction AI capabilities. Observance helps owners, contractors, and architects in tracking, managing, and executing construction projects efficiently. It also offers defect detection, mesh segmentation, objects identification, and health & safety monitoring using AI algorithms.

viAct.ai is an AI-powered construction management software and app that utilizes computer vision and video analytics for workplace safety. The platform offers scenario-based AI vision technology to simplify monitoring processes in industries such as construction, oil & gas, mining, manufacturing, and more. viAct.ai helps in automating monitoring tasks, empowering jobsites with automated construction management software powered by AI video analytics.

LogicLoop is an all-in-one operations automation platform that allows users to set up alerts and automations on top of their data. It is designed to help businesses monitor their operations, identify risks, and take action to prevent problems. LogicLoop can be used by businesses of all sizes and industries, and it is particularly well-suited for businesses that are looking to improve their efficiency and reduce their risk.

Censius is an AI Observability Platform for Enterprise ML Teams. It provides end-to-end visibility of structured and unstructured production models, enabling proactive model management and continuous delivery of reliable ML. Key features include model monitoring, explainability, and analytics.

Applitools is an AI-powered test automation platform that helps businesses improve the quality of their digital experiences. It uses visual AI to validate user interfaces across any type of screen or device, and it can be deployed on-prem, in the cloud, or as a SaaS solution. Applitools integrates with all of the major development tools and workflows, and it offers a wide range of features and advantages that can help businesses save time and money while improving the quality of their software.

Trag is an AI-powered tool designed to review pull requests in minutes, empowering engineering teams to save time and focus on building products. With Trag, users can create custom patterns for code review, ensuring best practices are followed and bugs are caught early. The tool offers features like autofix with AI, monitoring progress, connecting multiple repositories, pull request review, analytics, and team workspaces. Trag stands out from traditional linters by providing complex code understanding, semantic code analysis, predictive bug detection, and refactoring suggestions. It aims to streamline code reviews and help teams ship faster with AI-powered reviews.

LuckyRobots is an AI tool designed to make robotics accessible to software engineers by providing a simulation platform for deploying end-to-end AI models. The platform allows users to interact with robots using natural language commands, explore virtual environments, test robot models in realistic scenarios, and receive camera feeds for monitoring. LuckyRobots aims to train AI models on real-world simulations and respond to natural language inputs, offering a user-friendly and innovative approach to robotics development.

LatenceTech is a tech startup that specializes in network latency monitoring and analysis. The platform offers real-time monitoring, prediction, and in-depth analysis of network latency using AI software. It provides cloud-based network analytics, versatile network applications, and data science-driven network acceleration. LatenceTech focuses on customer satisfaction by providing full customer experience service and expert support. The platform helps businesses optimize network performance, minimize latency issues, and achieve faster network speed and better connectivity.

Vocapia Research develops leading-edge, multilingual speech processing technologies exploiting AI methods such as machine learning. These technologies enable large vocabulary continuous speech recognition, automatic audio segmentation, language identification, speaker diarization and audio-text synchronization. Vocapia's VoxSigma™ speech-to-text software suite delivers state-of-the-art performance in many languages for a variety of audio data types, including broadcast data, parliamentary hearings and conversational data.

This website is an AI tool that helps senior developers analyze AI tech debt. AI tech debt is the technical debt that accumulates when AI systems are developed and deployed. It can be difficult to identify and quantify AI tech debt, but it can have a significant impact on the performance and reliability of AI systems. This tool uses a variety of techniques to analyze AI tech debt, including static analysis, dynamic analysis, and machine learning. It can help senior developers to identify and quantify AI tech debt, and to develop strategies to reduce it.

Helicone is an open-source platform designed for developers, offering observability solutions for logging, monitoring, and debugging. It provides sub-millisecond latency impact, 100% log coverage, industry-leading query times, and is ready for production-level workloads. Trusted by thousands of companies and developers, Helicone leverages Cloudflare Workers for low latency and high reliability, offering features such as prompt management, uptime of 99.99%, scalability, and reliability. It allows risk-free experimentation, prompt security, and various tools for monitoring, analyzing, and managing requests.

Polymer DSPM is an AI-driven Data Security Posture Management platform that offers Data Loss Prevention (DLP) and Breach Prevention solutions. It provides real-time data visibility, adaptive controls, and automated remediation to prevent data breaches. The platform empowers users to actively manage human-based risks and fosters enterprise-wide behavior change through real-time nudges and risk scoring. Polymer helps organizations secure their data in the age of AI by guiding employees in real-time to prevent accidental sharing of confidential information. It integrates with popular chat, file storage, and GenAI tools to protect sensitive data and reduce noise and data exposure. The platform leverages AI to contextualize risk, trigger security workflows, and actively nudge employees to reduce risky behavior over time.

Netify provides network intelligence and visibility. Its solution stack starts with a Deep Packet Inspection (DPI) engine that passively collects data on the local network. This lightweight engine identifies applications, protocols, hostnames, encryption ciphers, and other network attributes. The software can be integrated into network devices for traffic identification, firewalling, QoS, and cybersecurity. Netify's Informatics engine collects data from local DPI engines and uses the power of a public or private cloud to transform it into network intelligence. From device identification to cybersecurity risk detection, Informatics provides a way to take a proactive approach to manage network threats, bottlenecks, and usage. Lastly, Netify's Data Feeds provide data to help vendors understand how applications behave on the Internet.

CEREBRUMX is an AI-powered platform that offers preventive car maintenance telematics solutions for various industries such as fleet management, vehicle service contracts, electric vehicles, smart cities, and media. The platform provides data insights and features like driver safety, EV charging, predictive maintenance, roadside assistance, and traffic flow management. CEREBRUMX aims to optimize fleet operations, enhance efficiency, and deliver high-value impact to customers through real-time connected vehicle data insights.

Blue River Technology is a company that creates intelligent machinery for agriculture. They use computer vision, machine learning, and robotics to create solutions that help farmers improve yields and minimize their environmental impact. The company is committed to creating a people-first culture where everyone has a common mission: to solve monumental challenges in agriculture.

The LLM Engineer's Handbook is an official repository containing a comprehensive guide on creating an end-to-end LLM-based system using best practices. It covers data collection & generation, LLM training pipeline, a simple RAG system, production-ready AWS deployment, comprehensive monitoring, and testing and evaluation framework. The repository includes detailed instructions on setting up local and cloud dependencies, project structure, installation steps, infrastructure setup, pipelines for data processing, training, and inference, as well as QA, tests, and running the project end-to-end.

The LLM Engineer Toolkit is a curated repository containing over 120 LLM libraries categorized for various tasks such as training, application development, inference, serving, data extraction, data generation, agents, evaluation, monitoring, prompts, structured outputs, safety, security, embedding models, and other miscellaneous tools. It includes libraries for fine-tuning LLMs, building applications powered by LLMs, serving LLM models, extracting data, generating synthetic data, creating AI agents, evaluating LLM applications, monitoring LLM performance, optimizing prompts, handling structured outputs, ensuring safety and security, embedding models, and more. The toolkit covers a wide range of tools and frameworks to streamline the development, deployment, and optimization of large language models.

ReVA (Reverse Engineering Assistant) is a project aimed at building a disassembler agnostic AI assistant for reverse engineering tasks. It utilizes a tool-driven approach, providing small tools to the user to empower them in completing complex tasks. The assistant is designed to accept various inputs, guide the user in correcting mistakes, and provide additional context to encourage exploration. Users can ask questions, perform tasks like decompilation, class diagram generation, variable renaming, and more. ReVA supports different language models for online and local inference, with easy configuration options. The workflow involves opening the RE tool and program, then starting a chat session to interact with the assistant. Installation includes setting up the Python component, running the chat tool, and configuring the Ghidra extension for seamless integration. ReVA aims to enhance the reverse engineering process by breaking down actions into small parts, including the user's thoughts in the output, and providing support for monitoring and adjusting prompts.

**Prompt flow** is a suite of development tools designed to streamline the end-to-end development cycle of LLM-based AI applications, from ideation, prototyping, testing, evaluation to production deployment and monitoring. It makes prompt engineering much easier and enables you to build LLM apps with production quality.

tinyllm is a lightweight framework designed for developing, debugging, and monitoring LLM and Agent powered applications at scale. It aims to simplify code while enabling users to create complex agents or LLM workflows in production. The core classes, Function and FunctionStream, standardize and control LLM, ToolStore, and relevant calls for scalable production use. It offers structured handling of function execution, including input/output validation, error handling, evaluation, and more, all while maintaining code readability. Users can create chains with prompts, LLM models, and evaluators in a single file without the need for extensive class definitions or spaghetti code. Additionally, tinyllm integrates with various libraries like Langfuse and provides tools for prompt engineering, observability, logging, and finite state machine design.

ell is a lightweight, functional prompt engineering framework that treats prompts as programs rather than strings. It provides tools for prompt versioning, monitoring, and visualization, as well as support for multimodal inputs and outputs. The framework aims to simplify the process of prompt engineering for language models.

Athina is an open-source library designed to help engineers improve the reliability and performance of Large Language Models (LLMs) through eval-driven development. It offers plug-and-play preset evals for catching and preventing bad outputs, measuring model performance, running experiments, A/B testing models, detecting regressions, and monitoring production data. Athina provides a solution to the flaws in current LLM developer workflows by offering rapid experimentation, customizable evaluators, integrated dashboard, consistent metrics, historical record tracking, and easy setup. It includes preset evaluators for RAG applications and summarization accuracy, as well as the ability to write custom evals. Athina's evals can run on both development and production environments, providing consistent metrics and removing the need for manual infrastructure setup.

Simulator Controller is a modular administration and controller application for Sim Racing, featuring a comprehensive plugin automation framework for external controller hardware. It includes voice chat capable Assistants like Virtual Race Engineer, Race Strategist, Race Spotter, and Driving Coach. The tool offers features for setup, strategy development, monitoring races, and more. Developed in AutoHotkey, it supports various simulation games and integrates with third-party applications for enhanced functionality.

AI Engineering Academy aims to provide a structured learning path for individuals looking to learn Applied AI effectively. The platform offers multiple roadmaps covering topics like Retrieval Augmented Generation, Fine-tuning, and Deployment. Each roadmap equips learners with the knowledge and skills needed to excel in applied GenAI. Additionally, the platform will feature Hands-on End-to-End AI projects in the future.

LLM Engineering is an 8-week course designed to help learners master AI and LLMs through a series of projects that gradually increase in complexity. The course covers setting up the environment, working with APIs, using Google Colab for GPU processing, and building an autonomous Agentic AI solution. Learners are encouraged to actively participate, run code cells, tweak code, and share their progress with the community. The emphasis is on practical, educational projects that teach valuable business skills.

The Prompt Engineering Holy Grail repository is a curated resource for prompt engineering enthusiasts, providing essential resources, tools, templates, and best practices to support learning and working in prompt engineering. It covers a wide range of topics related to prompt engineering, from beginner fundamentals to advanced techniques, and includes sections on learning resources, online courses, books, prompt generation tools, prompt management platforms, prompt testing and experimentation, prompt crafting libraries, prompt libraries and datasets, prompt engineering communities, freelance and job opportunities, contributing guidelines, code of conduct, support for the project, and contact information.

Lance is a modern columnar data format optimized for ML workflows and datasets. It offers high-performance random access, vector search, zero-copy automatic versioning, and ecosystem integrations with Apache Arrow, Pandas, Polars, and DuckDB. Lance is designed to address the challenges of the ML development cycle, providing a unified data format for collection, exploration, analytics, feature engineering, training, evaluation, deployment, and monitoring. It aims to reduce data silos and streamline the ML development process.

ScaleLLM is a cutting-edge inference system engineered for large language models (LLMs), meticulously designed to meet the demands of production environments. It extends its support to a wide range of popular open-source models, including Llama3, Gemma, Bloom, GPT-NeoX, and more. ScaleLLM is currently undergoing active development. We are fully committed to consistently enhancing its efficiency while also incorporating additional features. Feel free to explore our **_Roadmap_** for more details. ## Key Features * High Efficiency: Excels in high-performance LLM inference, leveraging state-of-the-art techniques and technologies like Flash Attention, Paged Attention, Continuous batching, and more. * Tensor Parallelism: Utilizes tensor parallelism for efficient model execution. * OpenAI-compatible API: An efficient golang rest api server that compatible with OpenAI. * Huggingface models: Seamless integration with most popular HF models, supporting safetensors. * Customizable: Offers flexibility for customization to meet your specific needs, and provides an easy way to add new models. * Production Ready: Engineered with production environments in mind, ScaleLLM is equipped with robust system monitoring and management features to ensure a seamless deployment experience.

The Radicalbit AI Monitoring Platform provides a comprehensive solution for monitoring Machine Learning and Large Language models in production. It helps proactively identify and address potential performance issues by analyzing data quality, model quality, and model drift. The repository contains files and projects for running the platform, including UI, API, SDK, and Spark components. Installation using Docker compose is provided, allowing deployment with a K3s cluster and interaction with a k9s container. The platform documentation includes a step-by-step guide for installation and creating dashboards. Community engagement is encouraged through a Discord server. The roadmap includes adding functionalities for batch and real-time workloads, covering various model types and tasks.

LLMstudio by TensorOps is a platform that offers prompt engineering tools for accessing models from providers like OpenAI, VertexAI, and Bedrock. It provides features such as Python Client Gateway, Prompt Editing UI, History Management, and Context Limit Adaptability. Users can track past runs, log costs and latency, and export history to CSV. The tool also supports automatic switching to larger-context models when needed. Coming soon features include side-by-side comparison of LLMs, automated testing, API key administration, project organization, and resilience against rate limits. LLMstudio aims to streamline prompt engineering, provide execution history tracking, and enable effortless data export, offering an evolving environment for teams to experiment with advanced language models.

LLM App Stack, also known as Emerging Architectures for LLM Applications, is a comprehensive list of available tools, projects, and vendors at each layer of the LLM app stack. It covers various categories such as Data Pipelines, Embedding Models, Vector Databases, Playgrounds, Orchestrators, APIs/Plugins, LLM Caches, Logging/Monitoring/Eval, Validators, LLM APIs (proprietary and open source), App Hosting Platforms, Cloud Providers, and Opinionated Clouds. The repository aims to provide a detailed overview of tools and projects for building, deploying, and maintaining enterprise data solutions, AI models, and applications.

DataHub is an open-source data catalog designed for the modern data stack. It provides a platform for managing metadata, enabling users to discover, understand, and collaborate on data assets within their organization. DataHub offers features such as data lineage tracking, data quality monitoring, and integration with various data sources. It is built with contributions from Acryl Data and LinkedIn, aiming to streamline data management processes and enhance data discoverability across different teams and departments.

ChatOpsLLM is a project designed to empower chatbots with effortless DevOps capabilities. It provides an intuitive interface and streamlined workflows for managing and scaling language models. The project incorporates robust MLOps practices, including CI/CD pipelines with Jenkins and Ansible, monitoring with Prometheus and Grafana, and centralized logging with the ELK stack. Developers can find detailed documentation and instructions on the project's website.

Agno is a lightweight library for building multi-modal Agents. It is designed with core principles of simplicity, uncompromising performance, and agnosticism, allowing users to create blazing fast agents with minimal memory footprint. Agno supports any model, any provider, and any modality, making it a versatile container for AGI. Users can build agents with lightning-fast agent creation, model agnostic capabilities, native support for text, image, audio, and video inputs and outputs, memory management, knowledge stores, structured outputs, and real-time monitoring. The library enables users to create autonomous programs that use language models to solve problems, improve responses, and achieve tasks with varying levels of agency and autonomy.

Agenta is an open-source LLM developer platform for prompt engineering, evaluation, human feedback, and deployment of complex LLM applications. It provides tools for prompt engineering and management, evaluation, human annotation, and deployment, all without imposing any restrictions on your choice of framework, library, or model. Agenta allows developers and product teams to collaborate in building production-grade LLM-powered applications in less time.

Monitoring tools expert with brief responses and guiding hints.

Expert in host monitoring setup, providing seamless network monitoring solutions.

A specialist in DataOps and Data Observability, aiding in data management and monitoring.

Explains SAR technology for elevation monitoring.

Ensures product quality through systematic process monitoring and evaluation.

Expert on computing performance, inspired by Brendan Gregg.

Ensures efficient and effective network performance and security.

Your SRE, DevOps and Observability buddy

It's time to crawl your website, it's time to test your code!

Advance your Python skills and break through tough coding problems with expert mentoring, blending real-world wisdom and cutting-edge techniques.

Mentor for engineering managers in tech.

A formal, expert guide for DevOps pros advancing their skills. Your DevOps GYM

Guides project success through comprehensive performance monitoring.

Guides financial decisions by monitoring and enforcing policies and procedures.

Guides on checking and monitoring credit scores, with a financial and informative tone.

A compassionate companion for mental wellness support and monitoring.

Formal health assistant with data upload for personalized monitoring.

Be Boardroom Brilliant: Specializes in corporate board design, recruitment, and operation, offering expert guidance on board composition, CEO performance monitoring, and risk management tailored to specific business needs and contexts. (v1.10)

Hello I'm Flake Miller, Wheat And Oats Assistant! What would you like help with today?

This is an EPEMC private Research bot (PrRB)