< bridges the gap between computers and humans. By translating natural human language into machine-readable instructions, chatbots, voice assistants, and IVR systems allow users to ask questions, perform tasks, and access features with minimal effort, streamlining workflows and improving productivity.

<, an AI chatbot that can help workers navigate vast amounts of manufacturing equipment and system data faster. Employees can ask questions in natural language and receive answers drawn directly from company datasets. For added accuracy, users can specify which documents the chatbot should reference when generating responses.

<Andonix

<Andonix< built Andi, an AI-powered chatbot for manufacturing plants. It accesses company data, including technical documentation, quality systems, and process manuals, to give workers relevant responses to factory-related problems. Workers can use natural language to ask Andi questions about machine performance, downtime causes, and maintenance procedures. They can also request checklists and work instructions.

<Fluent.ai

<Fluent.ai< to develop a speech-to-intent system that enabled voice commands on factory machinery. Operators can verbally instruct machines to lift, move appliances, or execute other tasks. This allows the workers to interact with equipment hands-free, reducing physical workload during fast-paced assembly tasks.

<Ultimately, adopting this system led to faster production and improved working conditions. With hands-free AI assistance, workers could complete tasks faster, which reduced transition time by up to 75%. The system also eliminated repetitive physical motions, reducing workers’ risk of strain.

<Inbenta

<Inbenta< partners with utilities companies to enable customers to execute tasks via natural language. Customers using Inbenta’s chatbots can download their power bills, make payments, and report outages around the clock. They can also schedule appointments with technicians without mediation from a human operator.

<Floatbot

<Floatbot< partners with utilities companies to provide automated voice support for customer service calls. The system makes outbound calls, asks qualification questions, and books appointments without human intervention.

< offload simple customer inquiries. By handling billing questions, outage reports, and payment support, the company’s chatbot reduced the amount of time customers spent waiting for human agents. This allowed human agents to focus on complex or sensitive requests that needed professional judgment.

< helps providers manage heavy patient workload. Usually, chatbots and voice assistants help with simple patient inquiries so staff can focus on care.

<Philips<, for example, integrates AI chatbots with their patient monitoring platforms to streamline communication and hospital workflows. These systems can schedule appointments, send schedule reminders, perform symptom triage, and answer frequently asked questions.

<Vsenk

<Vsenk< to deploy an AI-powered voice assistant for patient scheduling and symptom triage. The system connects to the organization’s electronic medical records and answers patient calls in natural language. It also diverts to human staff when needed.

< eliminate tedious clerical work. Their ZyE chatbot helped them manage patient information, collect symptom information before visits, answer patient questions, and route patients to relevant specialties and services. The ZyE chatbots work in English, Hindi, and Gujarati to broaden communication.

<FourKites

<FourKites< built a generative AI natural language interface that helps transportation companies extract insights from FourKites’ repository of supply chain data.

<Telnyx

<Telnyx<, for example, uses NLP to let drivers and dispatchers automate tasks like driver check-ins, bookings, ride confirmations, shipment updates, and warehouse coordination via speech. Drivers can speak to the system in everyday language to manage delivery appointments.

<DispatchTrack

<DispatchTrack< uses AI-powered voice assistants to streamline delivery briefs for drivers. Before each stop, the voice assistant provides short audio summaries of relevant information, including parking instructions, access notes, traffic considerations, and other delivery details. This feeds drivers critical job details without removing their focus on the road.

<Erica<. Launched in 2018, Erica helps customers with a variety of simple tasks, such as checking balances, transferring money, making payments, and finding nearby ATMs or Bank of America branches. Erica can also provide personalized financial advice, such as spending habit breakdowns and recurring subscription monitoring.

< rolled out an upgraded generative AI version of its chatbot, DBS Joy, to serve small- to medium-sized enterprise clients with corporate banking needs. The chat assistant handles basic questions about corporate banking products, fees, and account processes. It also provides status updates and reroutes complex concerns to human agents.

<, for example, developed an AI-powered voice agent that connects directly to backend systems. Its access to secure financial data allows it to help banking customers check balances, review transactions, and perform payments through natural conversation. It also supports sensitive actions, such as updating contact information and reviewing credit limits.

<Buildots

<Buildots<’ generative AI construction management tool, Dots, hopes to achieve. Launched in 2024, the system analyzes data from sites using advanced AI and computer vision, then provides insights related to the project. Workers can ask about project progress, task completions, risk, and other details in everyday language. By simplifying both data retrieval and presentation, the system gives everyone more visibility into the project’s health, enhancing their capacity to craft smart strategies and effective decisions.

<, for example, developed an AI-powered app that lets field workers execute tasks via voice commands. Field workers can speak into their smartphones to create punch-list items, submit requests for information, and log daily progress. The system will then generate reports with metadata for timestamps, locations, photos, and trade details.

<DocsBot<, for example, trains models on each organization’s existing content and documentation to provide answers about project status, inspection protocols, compliance standards, or supplier and material data. Users like project managers, site staff, and supervisors can ask questions in natural language through the DocsBot conversational AI interface.

<Feretti

<Feretti<, for example, uses a web-based AI tool that guides customers through an interactive quiz. Shoppers answer questions about their hair type, condition, and preferences, and then receive tailored product recommendations.

<, for example, provides 24/7 automated support for retail customer service lines, handling simple inquiries like order status, returns, and store policies. This eliminates long wait times, increasing customer satisfaction and retention.

<ShipSprint

<ShipSprint<, for example, built a shipping chatbot that notifies customers about delivery statuses, timelines, and logistics issues in real-time. With retrieval augmented generation, it can ensure update accuracy and prevent spreading misinformation in high-volume support environments. Customers may interact with the bot 24/7, eliminating the wait for support staff.

<ActionBot< to deploy multilingual, round-the-clock customer support chatbots. This tool helps customers with common queries, such as bill payments, plan upgrades, and service troubleshooting. It can also provide product or service recommendations based on customer data.

<Comcast

<Comcast<, for example, leverages voice assistants to help agents answer complex questions with greater speed and accuracy. Agents can ask the AI for advice on customer service issues, retrieve relevant troubleshooting steps, or clarify customer account information.

<Telstra

<Telstra< deployed AI-powered assistants to support human agents during customer calls. These tools listen in on live calls and display relevant troubleshooting steps, billing details, and support documentation in the agent’s interface in real-time. This guidance helped agents resolve many customer issues on first contact, reducing follow-up calls by 20%.

<Legal

<, for example, uses NLP to extract legal documents for key points and important insights. With this information, it can review and analyze contracts, speed up research, and monitor compliance.

<Chatlaw

<Chatlaw<. This large language model allows both lawyers and clients to ask questions about legal workloads in natural language. Users can request summaries of statutes, explanations of legal concepts, or relevant precedents. The system integrates with a knowledge graph, which improves accuracy.

<MissNoCalls

<MissNoCalls<, for example, answers incoming calls, captures case details, and schedules consultations, allowing firms to respond to clients quickly while collecting information for intake. It also routes urgent matters to human staff when necessary.

<Bronson.AI< to explore how AI can strengthen your business. Our specialists can guide you through a wide range of options, from conversational and generative AI to advanced analytics and business intelligence. We shape every solution around your goals, so you get the most value from your AI investment.