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Proven by 10 years of building software
AI Assistant Development Services
We help SMBs develop custom AI assistants for business use cases, such as 24/7 customer service, personalized sales process, employee support with a Q&A interface, and more.
Get professional help adapting various LLMs to your specific business needs and integrating solutions from major vendors like OpenAI, Perplexity, Grok, Claude, Google AI, and Copilot with your existing systems.
Get professional help adapting various LLMs to your specific business needs and integrating solutions from major vendors like OpenAI, Perplexity, Grok, Claude, Google AI, and Copilot with your existing systems.
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— Our Services
Our AI Assistant Development Services
— Industry Expertise
AI Assistants We Create
[01]
Voice Assistants
Leverage speech recognition and voice synthesis to enable your users to set reminders, make notes, control smart devices, or search information hands-free by interacting with the AI assistant in voice mode.
[02]
Virtual Assistants
Integrate the AI assistant with your company databases to provide personalized, real-time assistance and human-like conversations when handling customer support, FAQs, or service inquiries.
[03]
Concierge Bots
Leverage speech recognition and voice synthesis to enable your users to set reminders, make notes, control smart devices, or search information hands-free by interacting with the AI assistant in voice mode.
[04]
Social Media Bots
Support consistent, real-time, and human-like interaction with your audience onplatforms like Facebook, Instagram, or Twitter to drive user activity 24/7 and increase profile visibility.
— Our solutions
What Features Do You Need in Your
AI Assistant?
Intent recognition and entity extraction
Leverage NLP mechanisms to enable your smart assistant to interpret users’ messages so they understand what the user needs to achieve (the intent) and identify specific details to include in the response (entities).
Adaptive learning
Create AI assistants that can learn from past interactions and improve over time to understand user preferences, predict their behavior, and handle new topics or complex queries without explicit programming.
Sentiment analysis
Enable your virtual assistant or bot to tailor its responses and actions to the situation by detecting and interpreting the emotional tone of user messages, such as positive, negative, or neutral sentiment.
Multilingual support
Level up your AI assistant with accessibility and global reach by enabling it to understand and respond in multiple languages while ensuring accurate, context-aware interactions regardless of the user’s language.
Multichannel support
Allow your users to switch between communication channels without losing context and maintaining a consistent conversation with their smart assistant, be it through web, a mobile app, social media, or a messenger.
Multimodality
Integrate multimodal large language models to enable your AI assistant to interpret and generate diverse content formats like text, audio, and images, or handle complex tasks like visual question answering.
— Success stories
Our AI Assistant Case Studies
[01]
RAG-powered Chatbot for Efficient Data Retrieval
We created an AI-powered enterprise virtual assistant with a Q&A interface that helps the client’s personnel find accurate and up-to-date information in the company’s extensive and continuously updated knowledge base.
[02]
Fine-Tuned LLM Assistant for Streamlined Medical Diagnostics
We prepared a training dataset and fine-tuned a general-purpose LLM to create a virtual assistant adapted to the device-driven diagnostics domain. The service helps clinicians to process device readings faster, with more accuracy, and in compliance with rigid industry regulations.
— advantages
Why Choose Axon As your
Development Partner
[01]
LLM Expertise
Our engineers know the nuances and have hands-on experience in working with large language models and natural language processing tools from key technology vendors, like Google, Azure, Microsoft, Amazon, OpenAI, Anthropic, Mistral, Meta, and Grok.
Engineers who continually upskill and apply hands-on experience in AI software development.
[02]
ML Proficiency
Understanding the mechanics of ML algorithms, knowing their capabilities and limitations, and mastery of the techniques to manipulate them help our engineers develop context-aware, task-focused AI assistants that meet business expectations.
Refined delivery process with attention to detail and tailored problem-solving.
— process
Our Process
STEP 1
Problem Analysis
We start with interviewing your key stakeholders to study your business model and operations, analyze data assets, identify specific business needs, establish a shared solution vision, and formulate a clear list of requirements.
STEP 2
Data Preparation
High-quality and relevant data is the prerequisite for a successful artificial intelligence app development services delivery. Therefore, at this stage, we set up your data provision pipeline, including data collection from various sources, its integration, cleaning, labeling (if applicable), normalization, balancing and augmentation, and logging for quality control.
STEP 3
AI Model Setup
Depending on your model deployment strategy (real-time inference, batch inference, or on-device deployment), we adjust and validate your AI model setup (model weights, hyperparameters, performance, accuracy) and prepare model packages for deployment.
STEP 4
AI Integration
For the AI model to function in sync with other system elements, it has to be wrapped in an inference pipeline. This step is needed to configure the model’s input and output processing, error handling, logging, security aspects, and its connection with the overall system logic.
— Our Services
AI Chatbots for Industries We Serve
E-Learning
Offer your users tailored learning suggestions and formats, easy administration, and simplified access to information with AI assistants.
- Course recommendations and enrollment guidance
- Personalized learning assistance and quiz feedback
- Student progress tracking and reminder notifications
Communication
Leverage event-triggered AI bots to create safe and accessible communication spaces with personalization and automation features.
- Community forums or chat group moderation
- New user onboarding and platform guidance
- Event scheduling, reminders, and content feed personalization
— technologies
Technologies We Use for
Programming Languages
Python
Node.js
Go
Java
C#
Cloud Platforms
Microsoft Azure:
Azure OpenAI
Microsoft Azure
AWS:
SageMaker
Bedrock
Google Cloud Platform:
Vertex AI
Frameworks
LlamaIndex
LangGraph
Apache Airflow
Vector Databases
Chroma
Pgvector
Weaviate
Data Preparation & Labeling
Label Studio
MCP
Azure OpenAI
— The team
Meet Axon team
Viacheslav Knysh
Head of Engineering
“We believe in pushing boundaries in the tech world and delivering excellence in every line of code.”
Maksym Shamanovskyi
Head of Java Chapter
“I lead a team passionate about creating software that stands the test of time.”
Vlad Khitev
Head of Frontend Chapter
“We’re not just crafting interfaces, we’re composing stories that users will remember.”
— REVIEWS
We are trusted
4.8 / 5.0
Based on 41 clients reviews
"Axon is a transparent, dedicated partner. They are predictable and ensure on-time deliveries of new product updates."
CEO, Fazile
"Their dedication and responsible attitude to work have proven that our choice was right."
VP R&D, Guidde Knowledge LTD
"They demonstrate an experienced approach to ensure that we always get high-quality results from their services."
Founder & CEO, Nightbus
"At Axon, we have met professional software developers who have done their work responsibly and competently."
CTO, Shinez.io
"The team pays attention to all business requirements and how they will meet the needs of our end users."
CTO, Fabnite AS
"Axon is a transparent, dedicated partner. They are predictable and ensure on-time deliveries of new product updates."
CEO, Fazile
"Their dedication and responsible attitude to work have proven that our choice was right."
VP R&D, Guidde Knowledge LTD
"They demonstrate an experienced approach to ensure that we always get high-quality results from their services."
Founder & CEO, Nightbus
"At Axon, we have met professional software developers who have done their work responsibly and competently."
CTO, Shinez.io
"The team pays attention to all business requirements and how they will meet the needs of our end users."
CTO, Fabnite AS
— faq
Questions & Answers
We actively work with clients from PropTech, EdTech, e-Commerce, Sports Fan Engagement, and Social Communications, but we also have experience in developing AI solutions for organizations in Healthcare, Legal, Logistics, Agriculture, and building SaaS products.
The timeline really depends on the complexity, scope, and integration level of the assistant, but in general, AI assistant development timeframes can be as follows:
4-6 weeks for a simple rule-based or LLM-powered chatbot with a limited scope that can serve basic customer support, appointment booking, or product inquiries.
8-12 weeks for a mid-level AI assistant with API connections (CRM, CMS, databases), custom business logic, and possibly multilingual or multi-channel setup.
3-6 months for an advanced AI assistant that uses dynamic workflows, process automation logic, custom ML models or fine-tuned LLMs, advanced analytics, and multi-platform deployment.
Yes. As key security measures, we make sure all user data is encrypted in transit and at rest, and that access is limited through strong authentication and role-based permissions, in which we have a solid expertise. Also, our AI assistants only collect data strictly necessary for their function, with explicit user consent and clear privacy disclosures. We anonymize personal identifiers, with users able to access, correct, or delete their data. To ensure ongoing adherence to GDPR standards, we conduct security audits, data retention reviews, and compliance monitoring.
Yes, building AI assistants into our clients’ business processes is our key focus. In each case, we establish secure API connections that allow the assistant to read from and write to the target platforms in real time. We make sure the integration maps the client’s data structures correctly, ensuring their customer information, conversation history, and interaction context get synchronized across systems. We also configure business rules and workflows so the assistant can trigger actions like creating leads, sending follow-ups, or posting updates.
Yes, at early post-launch, we monitor your AI assistant’s performance, analyze user interactions, and identify errors or gaps in responses. If needed, we do updates improving conversation flows, adjusting intents, refining prompts, and retraining models. As an additional service, we can provide ongoing support to ensure the assistant continues to deliver a reliable, seamless, and optimized experience for users while adapting to evolving business needs. This includes technical maintenance, where we update APIs, ensure integrations are functional, and address security patches.
Looking for AI specialists to integrate an AI assistant for you?
Get professional help at Axon.
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