LangChain Integrations

Pillar Security serves as a comprehensive AI security platform designed to safeguard the agentic workforce throughout the entire AI lifecycle, encompassing stages from development to deployment and ongoing runtime protection. By integrating business context during phases of discovery, testing, and protection, it ensures that security intelligence accumulates across various AI applications, including agents, models, prompts, frameworks, tools, MCP servers, skills, coding agents, and both SaaS and cloud environments. The platform enables organizations to identify and manage AI assets effectively, even those that are unapproved or fall under shadow AI, while also evaluating risks related to supply chain and overall security posture. Additionally, it maps out the attack surfaces associated with agentic systems and verifies critical vulnerabilities that need addressing. With its AI Security Posture Management features, Pillar scrutinizes interconnected agents, tools, permissions, data sources, prompts, models, and supply chain elements to reveal high-risk pathways, policy breaches, misconfigurations, and potential threats posed by coding agents, all of which enhance the understanding of the impact when a single component encounters a breach. Ultimately, Pillar Security empowers organizations to maintain a robust security framework while navigating the complexities of AI technology.

Arato.ai serves as a comprehensive platform for the development of structured, dependable, and production-ready large language models (LLMs), aimed at empowering teams to confidently create, assess, and expand generative AI applications. While it is designed to handle intricate systems, Arato simplifies the process by seamlessly integrating with any LLM stack and connecting to existing AI applications without the need for rewrites, extensive setup, or intricate integrations. This platform allows teams to simulate multi-modal user experiences through text, voice, data, or images, enabling them to evaluate AI behavior prior to customer interaction and ensure alignment with AI regulatory standards such as the EU AI Act and ISO/IEC 42001. One of Arato's standout features, Arato Simulate, functions as a black-box simulation tool that emulates realistic user traffic to rigorously test AI applications for accuracy, security, compliance, costs, and user experience, all assessed based on their business impact. By identifying issues that traditional testing methods often overlook—such as multi-turn conversations, edge cases, adversarial situations, persona-specific shortcomings, and large-scale challenges—Arato enhances the reliability and effectiveness of AI applications. Ultimately, this innovative platform not only streamlines the development process but also ensures that AI solutions are robust and ready for real-world deployment.

Utilize the Pubmed API to retrieve a collection of academic articles related to a specified subject. Additionally, download a YouTube video from a provided URL to a designated file location on your local system, ensuring progress is logged, and return the path to the saved file. Implement the Alpha Vantage API to fetch the most recent stock data corresponding to the specified ticker symbol. Offer suggestions for enhancing one or more code files that are submitted for review. Furthermore, return the current directory's path along with a hierarchical structure of its subfiles. Lastly, access and retrieve the contents of a specified file located on the filesystem.

Chainlit is a versatile open-source Python library that accelerates the creation of production-ready conversational AI solutions. By utilizing Chainlit, developers can swiftly design and implement chat interfaces in mere minutes rather than spending weeks on development. The platform seamlessly integrates with leading AI tools and frameworks such as OpenAI, LangChain, and LlamaIndex, facilitating diverse application development. Among its notable features, Chainlit supports multimodal functionalities, allowing users to handle images, PDFs, and various media formats to boost efficiency. Additionally, it includes strong authentication mechanisms compatible with providers like Okta, Azure AD, and Google, enhancing security measures. The Prompt Playground feature allows developers to refine prompts contextually, fine-tuning templates, variables, and LLM settings for superior outcomes. To ensure transparency and effective monitoring, Chainlit provides real-time insights into prompts, completions, and usage analytics, fostering reliable and efficient operations in the realm of language models. Overall, Chainlit significantly streamlines the process of building conversational AI applications, making it a valuable tool for developers in this rapidly evolving field.

Adopt AI helps modern applications deliver an agentic experience to their end users within days. Using Adopt, end users of applications can execute complex actions across their application via natural language commands, automate workflows and unlock new possibilities for application innovation. In this future, AI agents will understand application/website workflows, know which components to call, create dynamic plans, and execute those plans to achieve desired outcomes. This approach means that humans will no longer need to learn how to use applications; instead, they can interact with AI in natural language to accomplish tasks or have AI automatically perform tasks based on schedules or triggers. Adopt AI is helping companies race against time to build their own AI copilot and set of autonomous/semi-autonomous agents.

DeepKeep is an advanced security platform designed to assist organizations in the secure development, deployment, and utilization of AI applications, agents, models, and tools for employees. It effectively tackles challenges that conventional security measures are ill-equipped to handle, such as prompt injection, the risk of sensitive data leaks, hallucinations, unsafe outputs, agent misuse, malicious models, and shadow AI practices. The platform ensures the security of the entire AI lifecycle by incorporating features like automated and Vibe AI Red Teaming, a real-time AI Firewall with guardrails, AI Usage Control, an AI Agent Scanner, and comprehensive Model Scanning. These tools empower security teams to detect vulnerabilities ahead of deployment, analyze agent attack surfaces, scrutinize models, oversee employee AI usage, and safeguard AI interactions in live environments. DeepKeep's versatility is evident as it is model-agnostic, multimodal, and equipped with multilingual capabilities. Furthermore, it accommodates various deployment options such as SaaS, private cloud, on-premises, and air-gapped environments, enabling enterprises to secure their AI while adhering to privacy, sovereignty, and regulatory standards. With its robust framework, DeepKeep not only enhances security but also fosters trust in AI technologies across diverse sectors.

Gemini 3.8 Live is a native speech-to-speech AI model from Google DeepMind designed for low-latency conversational agents and real-time voice applications. The model can reason and execute tasks while maintaining the natural flow of an audio conversation. Its asynchronous function calling capability allows external APIs and tools to run in the background without forcing the agent to stop speaking while it waits for results. Developers can combine streamed audio with structured information through incremental content updates, allowing responses to adapt as new data becomes available. Visual context support enables applications to ground conversations in live images or video so agents can understand both what users say and what they are looking at. Gemini 3.8 Live supports more than 97 languages and is designed to maintain consistent accents across multilingual experiences. The model also emphasizes alphanumeric precision for accurately understanding information such as account identifiers, confirmation codes, technical values, and claim numbers. A related Gemini 3.8 Live Extended Thinking model adds configurable reasoning for more complex, multi-step tasks while continuing to interact with the user. Gemini 3.8 Live is available through the Gemini API, Google AI Studio, and integrations with real-time development platforms such as LiveKit, Pipecat, Agora, LangChain, and Vercel.