We revitalized an outdated SaaS platform, GoalEnvision, using .NET, Umbraco, React, and Next.JS, to provide AI-driven insights for business growth. Our solution includes comprehensive goal management, growth prediction, and user-friendly data visualization.
Our team has extensive experience working with the OpenAI API, as well as modern SaaS and self-hosted Ollama-based models, such as LLama, Mistral, Gemma and more, for building retrieval-based architectures that power AI assistant solutions. We design systems that blend external models with your internal data, ensuring your artificial assistant provides accurate, reliable, and business-specific responses every time.
With UKAD, you always know where you stand. We offer clear, transparent pricing models and flexible delivery options to match your project’s needs. We adjust to your pace, budget, and goals!
Security is embedded in every solution we create. Our virtual assistant software artificial intelligence protects sensitive data by maintaining strict governance, compliance, and API security standards. Every AI solution is tested, monitored, and built to safeguard your business against evolving risks.
We tailor every assistant development project to your business needs, goals, and tech stack. We start with a solid, structured approach, whether you're building a standalone AI assistant or embedding it into your workflow. Depending on scope and system complexity, most solutions are delivered in 4–10 weeks.
We begin with a feasibility study and define how AI can add value to your process
Our team connects your assistant to internal data systems like Data Warehouse, Knowledge base, CMS, and not only
We design the interface, integrate GPT-4o or other models, and deploy your AI securely
With models like GPT-4o, you pay only for what you use. Typical costs range from $0.50 to $2 per 1,000 queries, depending on model type and response length. UKAD can deploy your AI assistant software on your existing cloud or provide full infrastructure management for a smooth, scalable rollout.
We help you compare OpenAI model costs and choose the best option for your volume
Run on your infrastructure or let UKAD manage hosting and compliance end-to-end
Once live, we help you track usage and scale your virtual AI assistant as needs grow
A chatbot delivers scripted responses to simple queries, mainly following predefined rules, while an AI Assistant, or personalized AI assistant based on GPT-4o, uses natural language processing and machine learning to provide adaptive, context-aware support. Unlike chatbots, which are limited to basic conversations, AI assistants can retrieve information, manage tasks, integrate across systems, and learn from interactions to deliver smarter, more personalized service over time.
An AI assistant can securely access a wide range of internal and external data sources through API integrations. We connect your AI assistant software to Data Warehouse, document storage systems, CRM, etc.
Most custom assistant projects are delivered within 4 to 10 weeks. Timelines depend on the complexity of the use case, required integrations, and feature depth. At UKAD, we streamline the entire assistant development process. This includes defining your assistant's role and data access needs, selecting the right tech stack, as well as choosing a right language models.
With modern AI assistant based on models like GPT-4o or GPT-4o mini, you only pay for what you use. Typical costs range from $0.50 to $2 per 1,000 queries, depending on model choice and response length. As your AI-powered virtual assistant agency, UKAD helps you choose the most efficient solution for your workload and budget.
Yes, of course! We take data security seriously. Your information is never stored by the assistant or exposed to public systems. All data transfers are encrypted, and we use secure API connections with strict access controls. We follow your internal security protocols and can work within your existing infrastructure to ensure full compliance. You remain in full control of your data at every stage.
Certainly! Every solution we build is tailored to your specific workflows, terminology, and business processes. We shape the assistant’s behavior, language, and integrations around your unique goals, in case you need it to serve customers, support internal teams, or automate domain-specific tasks.
We support GPT-4o, GPT-4.1, GPT-4.1-mini, GPT-4/1-nano, GPT-4o mini, and not only for their performance, speed, and versatility. We can also integrate with other LLMs. If your use case requires a different model, such as Gemini, DeepSeek, Mistral, or LLaMA, we'll help you choose and integrate the best fit based on your budget, data sensitivity, and specific needs.
Yes! We can deploy it within your existing cloud environment, ensuring full alignment with your IT policies, access controls, and compliance needs. If preferred, UKAD can also host and manage the solution end-to-end, with clear ongoing support.
Yes. We can integrate AI Assistants with workflow automation tools such as n8n, enabling actions like sending notifications, updating records, or triggering approval flows. UKAD has practical experience designing such automations to streamline internal processes and reduce manual tasks.
Our blog covers real-world advice on AI development, including LLM use cases, RAG pipelines, fine-tuning, and connecting AI to enterprise data systems.
Thinking about building an AI assistant but unsure what it actually involves or how much it might cost? This guide breaks it down in plain terms. You’ll learn what affects the price, how long development takes, and what technologies are involved. We’ll also look at hosting options, ongoing costs, and smart ways to keep your AI budget under control.
Artificial intelligence (AI) is revolutionizing industries, but many business owners think they need to build custom models from scratch to benefit. In reality, by customizing existing large language models (LLMs), businesses can automate tasks, improve efficiency, and access specialized knowledge without the time and expense of developing their own AI solutions. In this article, we’ll explore how techniques like prompt engineering, fine-tuning, and embedding retrieval can help your business tailor AI to meet its unique needs.
Learn how n8n enables efficient automation of AI workflows through a low-code interface, 420+ integrations, and support for custom logic. Discover how teams can quickly build, deploy, and manage AI-driven processes while maintaining complete control over data and infrastructure. Ideal for DevOps engineers and business leaders integrating AI into real operations.
