Business Software for LangChain - Page 6

Arato.ai is an end-to-end platform for structured, reliable, and production-ready LLM development, built to help teams build, evaluate, and scale GenAI apps with confidence. Designed for complex systems but made simple, Arato works with any LLM stack and connects to AI applications as they are, with no rewrites, no heavy setup, and no deep integrations required. It helps teams simulate multi-modal user journeys across text, voice, data, or image, test AI behavior before it reaches customers, and align development with AI compliance requirements such as the EU AI Act and ISO/IEC 42001. Arato Simulate is a black-box simulation platform that runs realistic user traffic against AI applications to test for accuracy, security, compliance, cost, and UX, scored by business impact. It catches what traditional testing misses, including multi-turn conversations, edge cases, adversarial scenarios, persona-specific failures, and large-scale issues.

Use the Pubmed API to get a list of scholarly articles on a given topic. Download a YouTube video from a URL to a given file on your filesystem (relative to the current path), logging progress, and return the file's path. Use the Alpha Vantage API to return the latest stock information based on the provided ticker. Suggest code improvements for one or more code files that are passed in. Returns the path of the current directory, and a tree structure of the descendant files. Retrieves the contents of a given file on the filesystem.

Chainlit is an open-source Python package designed to expedite the development of production-ready conversational AI applications. With Chainlit, developers can build and deploy chat-based interfaces in minutes, not weeks. The platform offers seamless integration with popular AI tools and frameworks, including OpenAI, LangChain, and LlamaIndex, allowing for versatile application development. Key features of Chainlit include multimodal capabilities, enabling the processing of images, PDFs, and other media types to enhance productivity. It also provides robust authentication options, supporting integration with providers like Okta, Azure AD, and Google. The Prompt Playground feature allows developers to iterate on prompts in context, adjusting templates, variables, and LLM settings for optimal results. For observability, Chainlit offers real-time visualization of prompts, completions, and usage metrics, ensuring efficient and trustworthy LLM operations.

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. This is required to stay relevant, change along with changing human needs, keep adoption high, churn low, and retain high NPS and GRR/NRR.

DeepKeep is an AI security platform that helps organizations securely build, deploy, and use AI applications, agents, models, and employee AI tools. It addresses risks traditional security controls were not designed for, including prompt injection, sensitive data leakage, hallucinations, unsafe outputs, agent misuse, malicious models, and shadow AI. DeepKeep secures the full AI lifecycle through automated and Vibe AI Red Teaming, real-time AI Firewall and guardrails, AI Usage Control, AI Agent Scanner, and Model Scanning. It enables security teams to identify vulnerabilities before deployment, map agent attack surfaces, inspect models, control employee AI usage, and protect AI interactions in production. DeepKeep is model-agnostic, multimodal, and natively multilingual. It supports SaaS, private cloud, on-premises, and air-gapped deployments, helping enterprises secure AI while meeting privacy, sovereignty, and regulatory requirements.

Gemini 3.8 Live is Google DeepMind’s real-time speech-to-speech AI model for building conversational voice applications and interactive agents. The model can maintain natural dialogue while reasoning, using tools, and carrying out tasks during an ongoing conversation. Asynchronous function calling allows applications to execute API and tool requests in the background while Gemini continues streaming audio responses to the user. Gemini 3.8 Live can also incorporate live visual context, enabling agents to respond based on what users say and what the system can see. It supports more than 97 languages, maintains accent consistency, and is designed to accurately interpret alphanumeric information such as confirmation codes, claim numbers, and technical data. Gemini 3.8 Live is available through the Gemini Live API and Google AI Studio for developers building customer service agents, assistants, training applications, and other voice-first experiences.