AI Chatbot Development Services

The development timeline depends on the complexity of your project. A basic AI chatbot can be delivered in as little as one month, while more advanced solutions typically require three months or longer. Before Apriorit experts start development, they thoroughly analyze your requirements and provide you with a full breakdown of features, activities, and their time and cost estimates so you get a complete picture of the project, its timeline, and your schedule.

An LLM’s concurrency capacity depends on the chatbot architecture. Key factors include the choice of model (size and efficiency), the deployment setup (cloud vs on-premises), GPU/CPU availability, load balancing mechanisms, and session management strategies. We optimize each of these to ensure your chatbot reliably serves the expected number of users.

By allocating the necessary computing resources and optimizing infrastructure, we make sure your AI chatbot remains responsive and efficient under heavy user loads. Our team continuously monitors and adjusts performance to meet your business demands.

Our AI chatbot development company tailors the model fine-tuning process to your specific accuracy goals. Steps we take include implementing double-check mechanisms like multiple-pass validation and proof-checking to minimize hallucinations. For chatbots that rely on proprietary data, we create a verified knowledge base. When external data is needed, we apply search filters and use trusted sources to avoid misinformation.

To align your chatbot with your unique brand identity, we tailor prompt design, implement content guardrails, and develop a custom FAQ-based knowledge base. We test the chatbot’s tone and answers using realistic conversation flows and adjust prompts or restrictions as needed to ensure the chatbot communicates in a way that feels natural to your users.

We combine manual and automated evaluation techniques to assess the quality of your AI chatbot solution. This includes stress testing under high user loads and scenario-based testing with curated question pools. Each chatbot is validated for answer accuracy, relevance, and response speed, ensuring it meets your business and technical expectations before release.

When a user asks an out-of-the-box AI chatbot something it doesn’t know, the chatbot can hallucinate instead of admitting to a gap in its knowledge. At Apriorit, we prevent hallucination in several ways:

• Enhancing the LLM’s memory so it can remember the current conversation
• Extending the chatbot’s knowledge base with records about the client’s business, products, services, etc.
• Fine-tuning the AI model to make it consume fewer resources when generating answers
• Testing the chatbot’s responses to unexpected prompts before release

At Apriorit, we cultivate UI/UX design skills alongside software and business development. When tasked with designing an AI chatbot, we focus on creating intuitive and user-friendly chatbot interfaces that enhance the overall user experience. We prioritize user-centric design principles and conduct thorough usability testing to ensure that the chatbot meets users’ needs and expectations.

Creating a custom training dataset during AI chatbot development improves the accuracy and efficiency of the final product. This process is challenging for any company, but it’s completely doable with the help of AI development experts.

Apriorit developers recommend following these best practices to create a custom dataset:

• Determine the AI chatbot’s purpose and desired capabilities
• Collect relevant data
• Eradicate possible data bias
• Categorize and annotate records
• Test the dataset
• Update the dataset regularly

Also, we can assist you in creating your custom dataset that will minimize the risk of hallucinations and other dataset-related issues.

It’s impossible to completely secure your data when working with an AI chatbot developed by a third party since you need to send your data to their servers. Also, it’s unclear whether third parties retain data they receive from their clients.

Creating a custom AI chatbot or deploying a commercial model on-premises allows you to implement the following security measures:

• Encrypt user data
• Anonymize or pseudonymize user data to protect sensitive information
• Redact sensitive data and personally identifiable information
• Store data in secure environments with access controls and intrusion detection systems
• Perform regular audits and compliance checks

Since AI-powered chatbots can be trained on a huge set of sensitive data, they need to be able to recognize user roles or job titles to avoid oversharing.

At Apriorit, we address this risk by customizing chatbot behavior and implementing role-based access control mechanisms. They allow security officers to create user roles and groups with different security permission levels. This way, a chatbot can share sensitive information with a user only if this user has a corresponding role.

For example, a chatbot might provide financial information only to accountants.

Yes, we specialize in integrating AI chatbots with various systems and platforms.

Apriorit developers have expertise in API integration, ensuring smooth communication between a chatbot and other systems. We can add an AI chatbot to your web or mobile application, SaaS solution, or enterprise system (CMS, CRM, HRMS, or any other type of product).

The cost of AI chatbot services depends on your requirements and expectations of the product itself, your development budget, and your expected delivery dates. Here are the key factors that influence the cost:

• Chatbot complexity
• Natural language processing capabilities
• Required integration with existing systems
• Number of programming languages used
• Degree of customization
• Scalability requirements
• Security and compliance requirements

We can offer comprehensive support and maintenance services post-deployment both for our solutions and for your existing product. Apriorit’s software maintenance services can include bug fixing, ongoing monitoring, improvements to a working product, and regular updates.

Ensuring that your AI chatbot gets quality support after the initial release will allow you to keep your product up to date and in line with modern requirements in terms of cybersecurity, usability, and competitiveness.