When we hear about custom AI solutions in business, we often think of robotic automation and machines replacing manual tasks. However, today’s AI models have become far more advanced.
AI systems utilize various technologies, including generative AI, large language models, voice recognition, computer vision, machine learning, and deep learning. These systems exist as software, such as AI-powered virtual assistants, facial recognition tools, and image processing applications. Developers use AI software in physical devices such as autonomous robots, drones, or self-driving vehicles. Businesses seek innovative solutions to apply to tasks requiring intelligent decision-making:
- automating repetitive processes,
- reducing operational costs,
- improving workflows,
- enhancing the overall customer experience,
- analyze real-time data,
- forecast trends,
- uncover patterns, etc.
How AI Tools Refine Business Processes: Statistics
In 2024, 13.48% of enterprises in the EU with 10 or more employees or self-employed professionals reported using at least one type of AI technology. These include:
- Text analysis tools (e.g., text mining) for processing and interpreting written language.
- Speech recognition systems that convert spoken language into machine-readable formats.
- Natural language generation for producing written or spoken content automatically.
- Image-based technologies for identifying people or objects through image recognition and processing.
- Machine learning algorithms, such as deep learning, are used for advanced data analysis.
- AI-powered automation tools, such as robotic process automation (RPA), streamline workflows and aid decision-making.
- Autonomous systems enable machines to move and act independently by interpreting their surroundings.
Source: Eurostat
Companies are embracing generative AI in areas where it delivers the most significant impact—for instance, in service operations within media and telecom, software development in tech firms, and knowledge management across professional services. The adoption of generative AI also differs by company size. Survey data reveals that enterprises with annual revenues exceeding $500 million are integrating generative AI more broadly across their operations than smaller companies. Source: McKinsey.
| Education | In EdTech, LaSoft builds AI-powered chatbots, virtual tutors, and personalized learning platforms. These tools provide custom-tailored student experiences and automate time-consuming tasks for educators, such as grading, tracking progress, and delivering content. Our adaptive learning solutions use machine learning to identify student pain points and recommend personalized study paths, promoting better engagement and retention. |
| Fintech | LaSoft helps fintech and insurtech companies leverage AI and machine learning to streamline internal operations and make more informed decisions. AI models analyze vast datasets to deliver actionable insights into clients’ profiles and histories. We develop AI-driven chatbots for client support and create forecast tools that predict creditworthiness using behavioral data, thereby enhancing loan and investment processes. |
| Insurtech | We support insurtech providers with AI models that automate claims processing, detect fraud, and offer dynamic policy pricing. By analyzing personal and non-personal data using ML models, insurers can personalize coverage plans, assess risks more efficiently, and enhance customer communication through virtual assistants. |
| Retail and E-Commerce | Our clients partner with our dedicated team to build AI-driven platforms that analyze consumer behavior, predict trends, and automate operations. We implement machine learning solutions that support personalized recommendations, pricing, and inventory management. Generative AI also assists in creating content for product descriptions, marketing copy, and customer communication. |
| Logistics | AI implementation helps manage fleet operations, optimize delivery routes, and predict supply chain disruptions. We use conversational AI solutions to automate customer interactions and coordinate driver communications. Machine learning models help predict peak season demand and manage warehouse inventory more efficiently, thereby improving delivery times and customer satisfaction. |
| Telecom | AI transforms telecom operations by enhancing network performance, predicting outages, and improving customer experience. We help providers deploy AI-powered systems that analyze user behavior to predict churn, automate technical support through chatbots, and route calls more efficiently. |
| Real Estate and Proptech | AI-powered search, price prediction, and virtual tour assistants benefit real estate platforms. We help proptech companies implement computer vision tools to assess property conditions, analyze buyer preferences, and match listings to prospects. AI also streamlines document analysis and contract management, saving agents time and improving deal flow. |
| Martech | LaSoft creates AI tools that automate campaign targeting, generate content, and analyze customer interaction. Our NLP tools enable personalized messaging, while predictive analytics improve lead scoring and ad placement. Through AI-enhanced decision-making, the marketing team gains actionable insights to refine campaigns and achieve a better return on investment (ROI). |
| HRtech | We have expertise and cases in our portfolio where we develop AI-driven platforms that screen resumes, assess candidate fit, and predict employee resignation. Our systems automate routine HR tasks, deliver insights into employee performance, and suggest improvements in retention strategies. AI solutions also enhance diversity hiring and reduce bias in recruitment processes. |
| Transportation | LaSoft supports transport clients with machine-learning models that track driver behavior, predict vehicle maintenance, and analyze traffic patterns. We also develop AI virtual and text assistants to help carriers and brokers communicate. The AI assistant contacts carriers to collect updates on active loads, ensuring brokers have accurate and timely information to share with clients. This feature enhances operational efficiency by reducing manual follow-ups. |
Maximizing Business Value with AI: LaSoft’s Strategic Approach
An AI voice assistant allows users to interact with systems using their voice. Unlike text chatbots that rely on written text, voice assistants use natural speech to understand user commands, support speaking interaction with users, and perform tasks hands-free. Behind the scenes, AI voice assistants rely on Natural Language Processing (NLP) to interpret spoken language and extract meaning, and Machine learning (ML) algorithms learn from user behavior to offer increasingly personalized and context-aware responses.
Businesses use AI-driven voice interfaces in interactive voice response (IVR) systems, automating customer service, streamlining call routing, managing appointments, and offering customer services—all without requiring human support for basic tasks. AI voice assistants enhance efficiency while maintaining a human-like interaction.
At LaSoft, we possess the expertise to devise strategies for implementing artificial intelligence to automate and innovate business operations and workflows across various industries. AI solutions bring measurable improvements in productivity and cost efficiency, solving real business challenges. Let’s explore how various industries are already benefiting from AI and how LaSoft’s team contributes to this transformation.
Transforming Businesses with AI: Real Business Cases from LaSoft
We have attached presentations of our real-world cases for various industries to demonstrate how you can utilize innovative technologies to develop AI and ML-powered solutions that address genuine business needs. From intelligent customer support systems to predictive HR tools and smart logistics automation, our AI projects are helping companies enhance efficiency, reduce costs, and deliver improved user experiences.
Discover how AI agents and virtual assistants, in our AI and ML cases, add operational efficiency to industries like logistics, the pharmaceutical industry, the museum guide app, and the platform for aging people.
Types of AI Assistants and How They Empower Businesses
Artificial intelligence assistants are trained on large datasets, such as company-specific knowledge bases or public information, to understand user intent and respond accordingly. They can be rule-based (following a decision tree) or generative, using models like GPT to produce context-aware responses. Key technologies involved include:
- NLP/NLU (Natural Language Processing/Understanding)NLU is the backbone of any intelligent assistant. It helps the system understand user intent, extract relevant data, and craft responses that feel natural and helpful.
- Automatic Speech Recognition (ASR) and Speech Synthesis. ASR converts spoken language into text, while text-to-speech (TTS) systems turn the assistant’s responses back into lifelike audio. These two technologies allow for seamless, real-time voice interaction.For global businesses, accuracy and adaptability are key:
- Speech engines must recognize diverse accents and perform well in noisy environments.
- Multilingual support helps connect with customers worldwide.
- Speech synthesis tools should produce natural-sounding, brand-consistent voices.
- Seamless System Integration. To be helpful in a business setting, AI voice assistants must connect to the tools companies already use, like CRMs, knowledge bases, or ERP systems. Integration through APIs makes this possible, allowing assistants to pull real-time data or trigger system actions.
Once deployed, these assistants can settle complex challenges:
- Automate repetitive queries
- Guide users through processes
- Trigger actions (e.g., book a meeting, fetch a report)
- Personalize responses based on user behavior and buyer history
Choosing the right artificial intelligence assistant depends on your business data, goals, industry, and user needs. Here’s an overview of the most common types and how they are applied:
Chatbots
Chatbots are AI-driven tools that communicate through text, providing immediate, 24/7 support for users. Their applications include:
- Customer Support: Answer FAQs, guide users, and handle basic issue resolution
- Sales: Recommend products, handle pre-sale questions, and assist during checkout
- Internal Use: Help employees with quick HR or IT-related queries
Voice Assistants
Voice assistants respond to spoken commands, offering hands-free convenience and real-time interaction. Examples include Siri, Google Assistant, and Alexa. Common tasks:
- Setting reminders, alarms, and calendar events
- Managing smart devices
- Providing news, weather, and traffic updates
- Sending messages or retrieving data
AI Avatars
AI avatars are digital personas that represent AI assistants, providing a more immersive and engaging experience, particularly valuable for branding, training, and entertainment purposes.
- Gaming: As interactive characters or guides
- Customer Service: Bringing a human touch to digital interfaces
- Virtual Events: Enhancing interaction in VR and digital environments
Virtual Industry-Specific Assistants
These AI assistants are designed to deliver expert-level support in specific industries, thereby enhancing precision, efficiency, and user satisfaction. Applications include:
- Healthcare: Appointment scheduling, diagnostic assistance, patient monitoring
- Finance: Portfolio management, fraud detection, real-time advisory
- Education: Customized learning paths, assessment support, grading automation
- Legal: Contract review, compliance tracking, and document management
AI Agents for Business Operations
AI agents go beyond basic automation—they’re designed for autonomy and intelligent decision-making. These systems play a crucial role in optimizing operations and driving business strategy. Use cases include:
- Data Analysis: Processing complex datasets to uncover AI-driven insights and support growth decisions;
- Workflow Automation: Automating onboarding, supply chain logistics, and back-office operations;
- Targeted Marketing: Creating personalized campaigns based on customer behavior;
- Predictive Maintenance: Monitoring systems and equipment to forecast failures and avoid downtime.
AI Assistants Industry Use Cases and Business Value
At LaSoft, we help businesses build custom AI assistant solutions tailored to industry needs, with user-centric design, smart automation, and ethical AI practices at the core.
Industry |
Value | Example |
EdtechVirtual tutors guide students through lessons, answer FAQs, and provide personalized support. Educators utilize artificial intelligence chatbots for tasks such as grading, scheduling, and distributing course content. |
|
Lasoft’s case involves a chatbot builder for universities, enabling admins to create course-specific bots without coding knowledge and provide real-time help to students. |
Finance & BankingAI assistants can provide account summaries, assist with transactions, offer financial advice, and support onboarding or fraud detection. Banking institutions face growing demands to modernize as customers expect seamless digital experiences, instant support, and more innovative self-service options. Generative AI assistants help banks meet these expectations by delivering intelligent, automated customer interactions across channels. |
|
A chatbot helps users apply for loans, ask questions about savings, and retrieve personalized options. |
HR techVirtual assistants screen resumes, schedule interviews, answer employee FAQs about policies or benefits, and support onboarding processes. |
|
AI bots that engage with candidates during application and onboarding processes, or internal assistants that remind teams about upcoming training. |
Retail & E-commerceAI chatbots assist customers in finding products, provide real-time assistance, facilitate returns management, and deliver order updates. Virtual shopping assistants can recommend products based on behavior and preferences. |
|
AI text assistant on an e-commerce platform guides potential buyers to best-fit products based on personalized preferences and budgets. |
Logistics & TransportationAI assistants are used to verify delivery details, schedule cargo transportation, guide truck drivers, provide live shipment tracking, communicate with carriers and brokers on shipments, and handle common customer questions about logistics. |
|
AI agent connects shippers, brokers, and carriers. By leveraging technologies like machine learning, natural language processing, and advanced optimization algorithms, AI streamlines the entire logistics communication process.
Instead of relying on time-consuming phone calls or manual coordination, the AI assistant automates key interactions—verifying MC# numbers, providing load updates, managing transport requirements, and handling initial price discussions. It significantly reduces operational workload and speeds up the booking process. |
Real Estate & ProptechVirtual assistants can handle property inquiries, qualify leads, schedule tours, and guide users through mortgage options. |
|
A chatbot that asks users what they’re looking for and immediately shows relevant listings. |
How LaSoft Built a Chatbot Builder Platform for Edtech
We want to share our case for the education industry, where communication, personalized experience, and time management are essential; AI helps transform how teachers engage with students. Let’s examine what value our chatbot builder brings to the education space and how other industries can benefit from similar solutions.
How We Can Simplify AI-Powered Communication in Higher Education
An edtech client approached LaSoft with a practical idea: to build a no-code platform that allows system administrators to create and manage chatbots to assist in 24/7 communication between students and university professors. These bots would provide course-specific support, answer common questions, and improve student engagement without requiring technical knowledge from educators.
The key challenges were:
- Making the chatbot creation process intuitive and fast;
- Ensure admins can train chatbots on specific course material;
- Providing complete administrative control with user management, embedding capabilities, and chat history;
- Adding a knowledge base so the chatbot can analyze the vast amount of relevant information from the new resource;
- Ensuring privacy and compliance with academic standards.
Custom AI Chatbot: LaSoft Creates Innovative Solutions
LaSoft developed a web-based chatbot builder that empowers professors to create, customize, and manage AI chatbots. The platform integrates with OpenAI APIs, offering a seamless experience for both educators and students.
Key features we delivered:
| Chatbot creation dashboard | Admins can upload documents, add URLs, and train their chatbot to answer specific course-related questions. |
| Custom chatbot UI builder | Admins can choose from various layouts and color themes and instantly generate an embed code. |
| User roles and access | Admins, professors, and students all have specific permissions, ensuring secure access and simplified user management. |
| Multi-chat management | Admins can manage multiple bots with their own history, configuration, and content. |
| AI integration | The platform connects to OpenAI models, enabling natural, smart, and context-aware replies based on trained data. |
| Scalable infrastructure | The system, hosted on AWS with a modular architecture, is designed for performance, growth, and data privacy. |
Educators and students derive significant value from LaSoft’s custom AI chatbot development services, specifically designed for the EdTech sector.
For educators and administrators, the platform enables them to build and train AI chatbots using their course materials, like PDFs and URLs, in just a few clicks. Professors can ensure that students receive accurate, 24/7 answers to frequently asked questions about the course, thereby freeing up valuable time that is typically spent replying to repetitive emails. The intuitive no-code builder enables non-technical staff to easily create visually branded bots, assign access roles, and monitor student interactions, all while maintaining complete control over data and compliance standards.
Students benefit from instant support and improved access to course information and knowledge bases. Instead of waiting for office hours or emails, they can ask the chatbot questions about deadlines, assignments, reading lists, and exam formats and get instant, reliable responses anytime from any device. This solution enhances their learning autonomy, reduces confusion, and helps them stay better organized throughout the academic term.
How to Build an AI Voice Assistant: A Step-by-Step Guide
LaSoft helps clients simplify the process of developing voice assistants. Here’s a clear roadmap we follow to create scalable, intelligent, and voice-first experiences:
Step 1. Define Purpose and Scope
Start by identifying your assistant’s goal. Determine if it will answer support tickets, manage bookings, facilitate interaction between carriers and brokers, or assist with account inquiries. You can focus on the essential goal, then expand gradually based on user feedback and ROI. Clear objectives ensure that your voice assistant delivers real value from the start.
Step 2. Choose the Right Tech Stack
We select platforms and tools that support scalability, data privacy, and integrations. With LaSoft, you get a tailor-made stack that fits your business’s technical needs.
Step 3. Design Conversational Flows
Voice interfaces require simple, direct conversations. Unlike text, users can’t scroll back or see visual cues.
We design flows that are concise and actionable, avoiding lengthy responses. Users can interrupt or ask for clarification.
Step 4. Train the Assistant
Training data defines how smart your assistant becomes. We use real customer queries, call transcripts, and product documentation to train your models.
With LaSoft’s support, you get high-quality training sets and continuous learning cycles that improve performance over time.
Step 5. Test and Iterate
Before full deployment, AI voice assistants should run usability tests to check response speed, accuracy, and interaction quality.
We help you fine-tune your assistant using analytics, performance metrics, and regular updates, ensuring it evolves alongside your business needs.
Final Thoughts: Why Voice Assistants Are the Future of Interaction
AI voice assistants are no longer just a tech trend as they’re becoming an essential part of digital business strategy. They help companies automate customer service, improve accessibility, and create more human-centric digital experiences.
At LaSoft, we specialize in designing, developing, and scaling voice assistant solutions tailored to your goals—whether you’re in finance, retail, healthcare, logistics, or education. Ready to explore how an AI voice assistant could work for your company?
FAQ
What are AI voice and text assistants, and how do they work?
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