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Chatbots and virtual assistants offer interactive help that makes it easy to monitor, operate, and troubleshoot within your customer channels. Receive alerts, retrieve diagnostic information, configure resources, initiate workflows, and receive AI-based recommendations. It becomes easier for your team to stay updated, collaborate, and respond quickly to incidents, security alerts, and customers.
Deploy a multi-channel, multi-language conversational interface (chatbot) that responds to your customer's questions, answers, and feedback, powered by large language models (LLMs).
Accelerates development and streamlines experimentation by helping you ingest your business-specific data and documents, evaluate and compare the performance of large language models (LLMs), rapidly build extensible applications, and deploy those applications with an enterprise-grade architecture.
A conversational AI low-code/no-code platform that automates the creation and management of multilingual digital agents and chatbots while orchestrating integrations with third-party systems across cloud providers.
Optimal Conversation™ Studio from XAPP AI is an automated knowledge capture and curation platform for developing virtual assistants and intelligent search solutions. OC Studio combines the power of intelligent search (Amazon Kendra) to answer informational questions with the power of conversational AI (Amazon Lex) to understand and respond to intentional requests. Supported channels include: web chat, website search, text, social, smart speakers and conversational IVR.
Optimal Conversations for SMBs is a partner-ready, self-service solution that makes it easy for SMB Service Providers to add AI-powered search and chat solutions to their SaaS offerings.
Cognigy is a leading enterprise software provider for Conversational AI automation. Our platform, Cognigy.AI, automates customer and employee communications. Available in on-premises and SaaS environments, Cognigy.AI enables enterprises to have natural language conversations with their users on any channel – webchat, SMS, voice and mobile apps – and in any language.
Cognigy.AI powers intelligent voice and chatbots that communicate consistently and accurately beyond simple FAQ, resulting in reduced contact center costs and increased efficiency while improving user experiences. Cognigy’s worldwide client portfolio includes Daimler, Bosch, Lufthansa, Salzburg AG, and many more.
Conversations by NLX™ enables companies to transform customer contact into personalized customer self-service. The product enables non-technical users to build and manage chat, voice, and multimodal conversational experiences, helping brands track and elevate self-service into a strategic asset.
ServisBOT's Conversational AI (CAI) platform allows businesses using Amazon Lex to build and manage self-service experiences across all channels (chatbots and virtual assistants) faster and more easily. Whether building your first bot, or connecting an existing Lex project for improvement, the platform provides IT with tooling to build and optimize bots while also covering security, integrations to backend systems, access management, and analytics. The platform also offers low-code tooling, blueprints, and reusable components for business users. Our multi-bot architecture makes it easier to create and manage conversational AI experiences across multiple NLPs and third-party bots in complex enterprise environments and supports ease of scaling and improved bot performance without sacrificing quality. In addition, our AI Insights tools include automated machine learning to help improve NLU performance - reducing learning delay while preventing regression. We help businesses solve the tough stuff as it relates to building and maintaining Conversational AI experiences while improving overall CX and reducing TCO.
A generative AI accelerator platform, NeuralSeek provides the tools users need to gain visible proof and enterprise observability to control LLM performance and mitigate risk of hallucination, misinformation, and sensitive data loss. 'Point and click' Governance and Guardrails - allowing users to see Provenance, Coverage and Confidence Scores, and Semantic Analytics with every Retrieval Augmented Generation (RAG) output. Finite details such as real-time updates on LLM token usage, LLM cost to operate, and LLM cost comparison are also provided. Multi-agent LLM orchestration too - build and manage multiple agentic generative AI solutions from a single platform, assign LLMs to agents, string together multiple LLMs, and switch out LLMs for optimization and cost savings - all 'out of the box'. NeuralSeek reduces development time for users to test, scale, and managed their generative AI solutions in production by up to 80%.
This Guidance demonstrates how to use Amazon SageMaker Unified Studio to create a unified development experience for building, deploying, executing, and monitoring end-to-end workflows across AWS data, analytics, and AI/ML services.
This Guidance demonstrates how to efficiently retrieve data by using the agent-driven framework of Amazon Bedrock to convert natural language queries (NLQ) into SQL queries.
This Guidance shows how you can add generative artificial intelligence (generative AI) to your virtual meetings to translate languages, summarize conversations, and capture live insights.
This Guidance demonstrates how to build on existing enterprise resources to automate tasks associated with the insurance claim lifecycle using Agents and Knowledge Bases for Amazon Bedrock.
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).