Langfuse Integrations

Claude Duet is a proactive AI assistant developed by Anthropic to automate personal productivity tasks, coordinate professional responsibilities, and complete multistep assignments across connected applications. The platform is powered by Claude Opus 5.5 and operates through a dedicated cloud computer that enables autonomous interaction with external services. Unlike traditional conversational assistants that primarily respond to user prompts, Claude Duet can proactively identify important developments and deliver personalized updates when attention or decisions are required. Its morning briefing functionality reviews relevant emails, calendar events, ongoing projects, and other connected information to summarize priorities and outstanding tasks. Users can delegate work through text or voice messages, including scheduling meetings, researching topics, preparing financial reports, and managing administrative workflows. The assistant can generate documents, spreadsheets, presentations, dashboards, and other deliverables using information retrieved from authorized applications. Claude Duet supports more than 6,000 connectors and plugins, including integrations with Gmail, Google Calendar, Slack, HubSpot, Salesforce, Shopify, QuickBooks, Notion, and Microsoft 365. Its persistent memory incorporates existing Claude conversations, saved context, skills, and connected tools to maintain continuity across tasks and interactions. The platform can continue working while users are away, monitor assigned activities, identify emerging issues, and provide notifications when tasks are completed or require intervention. Security and governance features include approval requirements for sensitive activities, isolated cloud execution, activity visibility, and the ability to review or redirect automated operations.

Grok Bot is an AI teammate platform from SpaceXSI that helps users delegate operational work to bots that can act across apps, websites, tools, and routines. Instead of functioning only as a chat assistant, Grok Bot is designed to take real projects from start to finish and come back when user approval is needed. Bots can sign in to tools, use software like a person would, and work across desktop, mobile, and a persistent cloud computer. Users can create different bots for different responsibilities, such as sales outbound, talent scouting, paid media, expense management, product performance, bug reproduction, account health, and chief-of-staff tasks. A sales outbound bot, for example, can research accounts, score contacts using signals, draft emails and LinkedIn messages in the user’s voice, and hold messages for approval before sending. Grok Bot can learn workflows by watching a user complete a task once, then saving the process as a routine that can run again later. Bots can also work in parallel, collaborate in shared threads, and pass tasks between each other when a workflow requires more than one role. The platform supports scheduled routines so bots can continue working 24/7 across repeatable processes. Each user’s bots share one persistent cloud computer with shared files, browser sessions, and logins, allowing context to carry across work. Grok Bot is available across macOS, Windows, iOS, Linux, and other supported environments, with pricing options that include Cursor Ultra and Cursor Premium Teams. By combining agentic execution, tool access, persistent context, workflow learning, scheduled routines, multi-bot collaboration, and human approval, Grok Bot helps individuals and teams automate meaningful work across their stack.

OpenAI is committed to ensuring that artificial general intelligence (AGI)—characterized by its ability to perform most tasks that are economically important with a level of autonomy that surpasses human capabilities—benefits all of humanity. Our primary goal is to create AGI that is both safe and beneficial; however, we also view our mission as a success if we empower others to reach this same objective. You can take advantage of our API for numerous language-based functions, such as semantic search, summarization, sentiment analysis, content generation, translation, and much more, all achievable with just a few examples or a clear instruction in English. A simple integration gives you access to our ever-evolving AI technology, enabling you to test the API's features through these sample completions and uncover a wide array of potential uses. As you explore, you may find innovative ways to harness this technology for your projects or business needs.

Claude is a powerful AI assistant designed by Anthropic to support problem-solving, creativity, and productivity across a wide range of use cases. It helps users write, edit, analyze, and code by combining conversational AI with advanced reasoning capabilities. Claude allows users to work on documents, software, graphics, and structured data directly within the chat experience. Through features like Artifacts, users can collaborate with Claude to iteratively build and refine projects. The platform supports file uploads, image understanding, and data visualization to enhance how information is processed and presented. Claude also integrates web search results into conversations to provide timely and relevant context. Available on web, iOS, and Android, Claude fits seamlessly into modern workflows. Multiple subscription tiers offer flexibility, from free access to high-usage professional and enterprise plans. Advanced models give users greater depth, speed, and reasoning power for complex tasks. Claude is built with enterprise-grade security and privacy controls to protect sensitive information. Anthropic prioritizes transparency and responsible scaling in Claude’s development. As a result, Claude is positioned as a trusted AI assistant for both everyday tasks and mission-critical work.

Flowise is an open-source development platform designed to help organizations build, test, and deploy AI agents and LLM-based applications through a visual workflow interface. The platform provides a drag-and-drop environment that simplifies the process of designing complex AI workflows and conversational systems. Developers can create chatbots, automation tools, and multi-agent systems that collaborate to perform advanced tasks. Flowise supports a wide range of AI technologies, including more than 100 large language models, embeddings, and vector databases. This flexibility allows teams to build AI applications that integrate seamlessly with different AI frameworks and data sources. The platform includes retrieval-augmented generation capabilities that enable agents to access external knowledge from documents and structured datasets. Human-in-the-loop features allow organizations to monitor, review, and refine agent decisions during execution. Flowise also provides observability tools that track execution traces and integrate with monitoring platforms such as Prometheus and OpenTelemetry. Developers can extend functionality through APIs, embedded chat widgets, and SDKs available in languages like TypeScript and Python. The platform supports scalable deployment across cloud and on-premises environments, making it suitable for enterprise AI applications. Flowise’s modular architecture allows teams to rapidly prototype new ideas while maintaining the ability to scale to production systems. By combining visual development tools with powerful AI integrations, Flowise enables organizations to create intelligent applications faster and more efficiently.

LangChain is a versatile framework that simplifies the process of building, deploying, and managing LLM-based applications, offering developers a suite of powerful tools for creating reasoning-driven systems. The platform includes LangGraph for creating sophisticated agent-driven workflows and LangSmith for ensuring real-time visibility and optimization of AI agents. With LangChain, developers can integrate their own data and APIs into their applications, making them more dynamic and context-aware. It also provides fault-tolerant scalability for enterprise-level applications, ensuring that systems remain responsive under heavy traffic. LangChain’s modular nature allows it to be used in a variety of scenarios, from prototyping new ideas to scaling production-ready LLM applications, making it a valuable tool for businesses across industries.

DocsGPT is Arc53's open-source platform for AI over company documents: assistants that answer with citations, agents that act on business systems, and search across every connected source. It runs where the data must stay: Arc53's EU cloud, a dedicated managed instance, the organisation's own servers, or a fully air-gapped network. It reads PDFs, Office files and scanned documents (with OCR), and syncs content from SharePoint, Google Drive, Confluence, GitHub, S3 and other services. Agents call tools and APIs under per-action approval rules, visual workflows automate repeatable document tasks, and agents can produce Word, Excel, PowerPoint and PDF files. It works with any cloud model (OpenAI, Anthropic, Google and more) or a local model through Ollama or vLLM. Governance includes single sign-on (OIDC), SCIM 2.0 provisioning, role-based access, guardrails, usage quotas and an exportable, append-only audit log. Released under the MIT licence, with 18,000+ GitHub stars.

GrowthBook helps product and engineering teams build smarter, ship safely, and grow at the speed of AI with feature flags, A/B testing, and product analytics in one platform. Teams use GrowthBook to roll out changes, test everything, and learn faster. Because analysis runs in your own data warehouse, results match your company’s definitions of success, and customer data stays under your control. Predictable cost: Per-seat pricing with unlimited flags, experiments, and traffic. One platform: Feature flags, experimentation, and product analytics in one place. Your data, your control: Self-host or use GrowthBook Cloud w. SOC 2 Type II certified. Fits your stack: 24+ SDKs, connections to Snowflake, BigQuery, Redshift, Databricks, and more. AI-ready: Test AI models and prompts against business metrics, and manage experiments from AI coding tools. Start free. Paid plans add advanced statistics, SSO, approval workflows, and dedicated support.

evalship is a GitHub App for teams that ship LLM features and test them with evals. It works in three parts. Review: your coding agent checks the scorers, judges and prompts in your evals and lists their flaws with a fix for each. Pull requests: evalship comments on every pull request with what really broke and why, separating real regressions from flaky evals, and its check can gate the merge. Optimize: your agent tries changes such as a newer or cheaper model, a lower reasoning effort or less context, and evalship says which win beyond chance, with the gap in pass rate, cost and time. A Monitor page per repository and a weekly report email keep the team current. Results come from pytest, Vitest, Jest, promptfoo, Langfuse, Braintrust or LangSmith. Free for public repositories, from $19 a month for private ones.

Hugging Face is an AI-driven platform designed for developers, researchers, and businesses to collaborate on machine learning projects. The platform hosts an extensive collection of pre-trained models, datasets, and tools that can be used to solve complex problems in natural language processing, computer vision, and more. With open-source projects like Transformers and Diffusers, Hugging Face provides resources that help accelerate AI development and make machine learning accessible to a broader audience. The platform’s community-driven approach fosters innovation and continuous improvement in AI applications.

Introducing a robust managed Platform as a Service (PaaS) that incorporates a low-code visual builder, VectorDB, and offers integrations for a variety of applications and models, specifically crafted for the development, testing, and deployment of high-performance AI applications at the edge. This innovative solution streamlines workflows by eliminating tedious and error-prone tasks, enabling users to effortlessly drag and drop models, applications, data, and agents to uncover the most effective combinations. Deploying solutions takes under 60 seconds, significantly minimizing latency in the process. The platform also allows for seamless monitoring, testing, and iterative processes, ensuring users maintain visibility and leverage tools that assure accuracy and reliability. Users can make informed, data-driven decisions supported by comprehensive reports detailing requests, interactions with language models, and usage analytics, while also being able to access real-time traces by node. With an experimentation feature that simplifies the optimization of various components, such as embeddings, prompts, and models, continuous improvement is ensured. This platform encompasses all necessary elements for launching and iterating at scale, and is bolstered by a dynamic community of innovative builders who share invaluable insights and experiences. The collective wisdom within this community refines the most effective strategies and techniques for AI application development, leading to a sophisticated solution that empowers the creation of agentic systems with the efficiency of a large team. Moreover, its intuitive and user-friendly interface promotes effortless collaboration and management of AI applications, making it easy for all participants to contribute effectively to the process. As a result, users can harness the full potential of AI technology, driving innovation and enhancing productivity across various domains.

LiteLLM acts as an all-encompassing platform that streamlines interaction with over 100 Large Language Models (LLMs) through a unified interface. It features a Proxy Server (LLM Gateway) alongside a Python SDK, empowering developers to seamlessly integrate various LLMs into their applications. The Proxy Server adopts a centralized management system that facilitates load balancing, cost monitoring across multiple projects, and guarantees alignment of input/output formats with OpenAI standards. By supporting a diverse array of providers, it enhances operational management through the creation of unique call IDs for each request, which is vital for effective tracking and logging in different systems. Furthermore, developers can take advantage of pre-configured callbacks to log data using various tools, which significantly boosts functionality. For enterprise users, LiteLLM offers an array of advanced features such as Single Sign-On (SSO), extensive user management capabilities, and dedicated support through platforms like Discord and Slack, ensuring businesses have the necessary resources for success. This comprehensive strategy not only heightens operational efficiency but also cultivates a collaborative atmosphere where creativity and innovation can thrive, ultimately leading to better outcomes for all users. Thus, LiteLLM positions itself as a pivotal tool for organizations looking to leverage LLMs effectively in their workflows.

Voker functions as an advanced Agent Analytics Platform dedicated to supervising and enhancing the performance of AI agents in real-world applications, ensuring that these agents are not just reactive, but instead offer significant benefits. This platform provides developers with the tools to observe AI agents' interactions, highlight areas that require enhancement, detect anomalies, and evaluate progress over time, all while avoiding the cumbersome task of analyzing extensive logs or depending solely on user input. By connecting agents' performance metrics to real business outcomes, Voker enables teams to align conversational insights with user data, clarifying whether an agent is effectively aiding in achieving objectives such as user activation, retention, conversion rates, support quality, and other crucial performance metrics. The intuitive self-service analytics cater to product managers, analysts, and business teams, furnishing them with practical insights without the complications of support queries or workflow disruptions. Moreover, developers have the convenience of integrating Voker into their systems seamlessly through the SDK; they can achieve this with a straightforward pip install command or by utilizing an AI coding tool to swiftly set up the SDK, enter the required API key, and configure an agent in just a matter of minutes. As a result, Voker not only simplifies the monitoring process but also empowers teams to use data for the ongoing enhancement of their AI agents, ultimately fostering a culture of continuous improvement and innovation within organizations.

AI Workers are autonomous agents designed specifically for your organization, functioning as true team members rather than just simple chatbots waiting for commands. Each of these sophisticated AI units possesses a unique professional identity, complete with an email address, phone number, and profiles on communication platforms such as Slack and Teams, showcasing their proactive nature and ability to operate continuously without direct prompts. Rather than requiring exhaustive instructions for their tasks, you only need to outline your goals, allowing them to independently create the necessary workflows to tackle various responsibilities, including generating daily reports, conducting weekly follow-ups, updating CRM systems, managing client relations, performing research, overseeing content production, handling financial duties, coordinating HR tasks, supporting design initiatives, and assisting in development processes. This framework comprises a wide array of specialized AI Workers, each tailored for specific functions in fields such as marketing, development, design, HR, and finance, ensuring practical application in their designated roles. Additionally, they can effortlessly integrate with over 3,000 different tools, including Slack, Microsoft Teams, Gmail, Notion, HubSpot, Salesforce, and many other business applications, making them a seamless addition to your existing operational workflows. Their remarkable versatility and adaptability significantly enhance productivity and streamline processes, making them essential assets in any business setting, and their ongoing development promises even more innovative solutions in the future.

Dograh is an open-source platform that allows users to self-host a voice agent, equipped with a no-code workflow builder aimed at crafting production-ready voice agents. Teams can choose from a variety of inbound channels, speech-to-text services, language models, text-to-speech solutions, and telephony providers, or they can utilize advanced speech-to-speech models for direct audio communication that ensures smooth turn-taking, effective interruption management, and low latency. The platform supports both inbound and outbound calling and includes features such as widgets, telephony integrations, observability, tracing capabilities, and real-time analytics, along with a hybrid model that merges pre-recorded voice with TTS, accommodating over 70 different languages. Moreover, the MCP server supports multiple agent runtimes, including Claude Code, Cursor, OpenClaw, and Codex, allowing users to create, modify, and deploy voice agents directly from their development environments. Dograh can be deployed on personal servers, within a private cloud or virtual private cloud, or in a managed environment, enabling complete hosting of models within the user's own infrastructure. Its comprehensive features and flexibility make Dograh an excellent choice for teams eager to push the boundaries of voice technology, fostering innovation and enhancing user engagement in various applications.

Reflexio acts as a comprehensive platform tailored for developers dedicated to the creation and oversight of AI agents, employing multiple input approaches including an SDK, REST API, CLI, or integration with compatible tracing platforms to collect data from agent actions, execution logs, tool interactions, and user feedback. By pinpointing frequent errors, it produces reusable playbooks and user profiles which significantly contribute to the learning curve. When an agent is actively functioning, it can draw on relevant insights derived from these experiences to enhance its responses. The Hosted Enterprise portal offers teams the ability to investigate, alter, approve, reject, search, and evaluate the accumulated knowledge efficiently. Reflexio empowers agents to make essential adjustments throughout various interactions without the need to modify the foundational model weights. Additionally, teams enjoy the option of using the managed cloud service, configuring their model-provider keys, or pursuing self-hosting options on platforms such as AWS, Google Cloud, or Azure. Moreover, enterprise trace imports are compatible with sources like Braintrust, Langfuse Cloud, and LangSmith Cloud, while Reflexio includes a mem0 wrapper and integration with OpenClaw, providing an extensive array of tools designed to enhance agent efficacy. This diverse strategy not only enables developers to fine-tune their AI agents but also maximizes the adaptability of deployment choices, ultimately leading to more robust and efficient AI solutions. By combining all these features, Reflexio paves the way for innovative advancements in AI agent development.

Modulos is a risk-centric AI governance platform for regulated enterprises in financial services, insurance, government, telecommunications and industry. It registers AI systems, maps them to controls across the EU AI Act, ISO/IEC 42001, NIST AI RMF, DORA, NIS2 and the OWASP Top 10 for LLM and agentic applications, and tests those controls against production on a schedule. The Risk Agent prices each AI risk as an expected annual loss, using scenario analysis or Monte Carlo simulation, and compares it with risk limits and with the value each system delivers, so teams can decide which AI systems to scale, fix or retire. Evidence, policies, vendor records and the audit trail sit in one place for auditors and supervisors. Modulos runs as SaaS with SSO and role-based access, and in a private cloud on request. The company was founded in 2018 as a spin-off of ETH Zurich and is SOC 2 Type II certified.

TierZero Production Agents are dedicated to monitoring incidents, managing alerts, and autonomously resolving production challenges, thus allowing your engineering teams to implement updates at a faster pace. When an incident arises, TierZero promptly initiates a comprehensive investigation that covers your entire stack—evaluating logs, traces, metrics, deployments, code changes, and prior incidents. In contrast to traditional AI SRE tools that only focus on triage, Production Agents manage the complete post-merge workflow, which includes investigation, remediation, support Q&A, and proactive discovery. The Context Engine provided by TierZero synthesizes information from code, infrastructure, discussions, and documentation into a fluid knowledge graph that adapts and enhances with each issue resolved. Installation in your environment can be completed in under an hour, and every AI-driven investigation is completely auditable. This innovative solution is tailored for highly regulated sectors, such as fintech, healthcare, and cryptocurrency, where security must be prioritized. Additionally, TierZero’s continuous learning features not only tackle current incidents but also equip your teams to foresee and mitigate potential future challenges effectively. Ultimately, this proactive approach ensures a more resilient production environment that evolves with your organization’s needs.

Overmind is an all-encompassing platform designed for both the training and deployment of AI agents, tailored specifically for teams active in this domain. It utilizes OpenTelemetry to process production traces, creating datasets from a variety of sources such as trace data, file uploads, and integrations with platforms like Langfuse, LangSmith, Braintrust, and Galileo. Teams can monitor agent context and performance in real-time, while also preparing and evaluating datasets and testing prompts and models against their customized examples, continuously improving agent behavior through evaluated adjustments. The platform supports both LoRA and full fine-tuning of open-weight models, providing benchmarking with custom evaluators and deployment options via an OpenAI-compatible endpoint; users can also download trained weights as needed. Additionally, users may choose to utilize the hosted console or implement the platform within their own infrastructure using Docker Compose. Specifically crafted for AI engineering and product teams managing agents in active environments, Overmind enables users to rigorously experiment, enhance, and tailor models with their unique data to achieve the best results. This versatility allows teams to modify their workflows to align with their individual requirements and preferences, fostering a more personalized approach to AI agent management. Ultimately, Overmind stands out as a vital tool for teams looking to maximize the potential of their AI initiatives.

LlamaIndex functions as a dynamic "data framework" aimed at facilitating the creation of applications that utilize large language models (LLMs). This platform allows for the seamless integration of semi-structured data from a variety of APIs such as Slack, Salesforce, and Notion. Its user-friendly yet flexible design empowers developers to connect personalized data sources to LLMs, thereby augmenting application functionality with vital data resources. By bridging the gap between diverse data formats—including APIs, PDFs, documents, and SQL databases—you can leverage these resources effectively within your LLM applications. Moreover, it allows for the storage and indexing of data for multiple applications, ensuring smooth integration with downstream vector storage and database solutions. LlamaIndex features a query interface that permits users to submit any data-related prompts, generating responses enriched with valuable insights. Additionally, it supports the connection of unstructured data sources like documents, raw text files, PDFs, videos, and images, and simplifies the inclusion of structured data from sources such as Excel or SQL. The framework further enhances data organization through indices and graphs, making it more user-friendly for LLM interactions. As a result, LlamaIndex significantly improves the user experience and broadens the range of possible applications, transforming how developers interact with data in the context of LLMs. This innovative framework fundamentally changes the landscape of data management for AI-driven applications.

Mirascope is a groundbreaking open-source library built on Pydantic 2.0, designed to deliver a streamlined and highly customizable experience for managing prompts and developing applications that leverage large language models (LLMs). This versatile library combines power and user-friendliness, simplifying the interaction with LLMs through a unified interface that supports various providers including OpenAI, Anthropic, Mistral, Gemini, Groq, Cohere, LiteLLM, Azure AI, Gemini Enterprise Agent Platform, and Bedrock. Whether you are focused on generating text, extracting structured data, or constructing advanced AI-driven agent systems, Mirascope provides you with vital resources to optimize your development process and create robust, impactful applications. Furthermore, Mirascope includes advanced response models that allow you to effectively organize and validate outputs from LLMs, making sure that the responses adhere to specific formatting standards or contain crucial fields. This feature not only boosts the reliability of the generated outputs but also significantly enhances the overall quality and accuracy of the applications you are building. By empowering developers to create more sophisticated and tailored solutions, Mirascope represents a significant advancement in the field of AI application development.

Omega is an advanced AI agent seamlessly integrated into Slack, specifically created to elevate sales workflows by automating tedious tasks, delivering insightful analytics, and promoting the effortless adoption of best practices among team members. Its seamless integration with vital applications like Slack, Google Drive, Apollo, Salesforce, and various transcript systems allows it to effectively streamline labor-intensive processes such as creating call agendas, summarizing discussions with experts, locating relevant documents, and tracking deal progress. Functioning as a modular, multi-agent framework, Omega utilizes specialized roles coordinated through systems like AutoGen to plan, execute, and validate actions across the sales workflow. This cutting-edge framework is designed on a cloud-native, serverless architecture that utilizes AWS Lambda and Step Functions, which provides substantial flexibility and scalability for varying business needs. Furthermore, the system’s capacity for observability and iterative enhancements is bolstered by advanced tools such as Langfuse, Promptfoo, CI/CD pipelines, and Terraform, ensuring that the sales process remains adaptive and continuously improving. With the comprehensive integration of these sophisticated tools, Omega stands out as an essential resource for teams aiming to maximize their operational efficiency and sales performance. Ultimately, its design and functionality reflect a commitment to innovation in enhancing collaborative workflows within sales environments.

Claude for Legal is a sophisticated AI assistant crafted by Anthropic, tailored for the needs of legal professionals to enhance their document management and research capabilities. This innovative tool excels at summarizing lengthy documents, extracting and comparing essential information, drafting and editing text, and assisting with the analysis of contracts and various legal papers. Legal teams across law firms and corporations can utilize Claude for Legal to optimize their document workflows and access vital knowledge, ensuring they have important context and source materials readily available. Furthermore, users are encouraged to evaluate the AI-generated outputs as an integral part of their overall workflow, which adds a layer of scrutiny to the process. Accessible on both desktop and mobile devices, Claude for Legal not only simplifies information processing and content creation but also emphasizes the importance of user verification. It's crucial for users to exercise their professional judgment and make well-informed legal decisions independently within their practice. Thus, while the AI can significantly boost efficiency, the ultimate accountability for legal accuracy and compliance continues to rest with the individual practitioner. In this way, Claude for Legal acts as a powerful ally, enhancing productivity while still necessitating human oversight in legal matters.