Smart automation for your business
AI-agents
We create software solutions based on artificial intelligence (AI) that can perform various tasks, adapting to business needs
How does an AI agent work?
An AI agent acts as an "intelligent assistant" - making decisions to complete tasks
[ Stages of AI agent work ]
Perception
receives information from the surrounding world through data: text, images, sounds, sensors
Analysis
processes information, searches for patterns or uses ready-made rules and algorithms
Solution
selects an action based on analysis
Action
shows the answer, sends a message, controls the device, etc.
Education
learns from mistakes to improve future decisions (in advanced systems)
In what areas
is an AI agent useful?
Customer
service
More
- Automates responses to typical customer requests
- Automatically distributes requests to departments
- Answers calls, consults clients, records orders
- Analyzes customer behavior and offers relevant services
Sales
and Marketing
More
- Finds potential customers by analyzing data
- Automatically conducts the first stages of negotiations
- Personalizes emails based on customer behavior
- Creates texts, product descriptions and posts on social networks
Internal business
processes
More
- Analyzes resumes, conducts initial selection of candidates
- Automates the creation, processing and storage of documents
- Forecasts needs and generates orders
- Analyzes the budget, forecasts expenses
Business
management
More
- Analyzes the market and offers business solutions
- Builds financial forecasts, assesses risks
- Analyzes data and proposes solutions to top management
- Identifies bottlenecks in business processes and suggests improvements
Production
and logistics
More
- Predicts equipment failures
- Analyzes products for defects
- Controls stocks, optimizes logistics
- Optimizes delivery routes
When developing AI agents, we follow the following basic principles
It can automate routine processes, improve customer interactions and provide analytics, ultimately saving time and resources.
receives information from the surrounding world through data: text, images, sounds, sensors
Each AI agent is created taking into account the individual requirements and characteristics of the client's business
This allows us to offer features and capabilities that are not available in standard solutions.
The process of developing and implementing the AI agent is carried out within the agreed timeframes
We understand that time is money and strive to minimize the time from idea to implementation
The AI agent interface is designed with user-friendliness in mind
which makes it easy to integrate into existing business processes. We also provide training and support so that users can quickly master all the features and start benefiting from them.
Examples of completed projects
AI agent for analyzing customer communications
Objective:
Automate the monitoring of employee correspondence with clients in Telegram to prevent missing important agreements and open questions
Mechanics:
- An AI agent based on DeepSeek (with the ability to integrate other AI models) is added to chats. Company employee data is pre-loaded into the system for accurate identification of parties
- The agent operates in the background without interfering in dialogues
- Every morning, it automatically generates a digest for the previous day with two key blocks:
- List of agreements (deadlines, promises)
- List of open questions (unfinished discussions)
Result:
- Team lead saves 30 minutes per day by eliminating manual chat audits
- Achieved transparency in work processes, reduced risk of missed deadlines and loss of important information
AI Agent Banner Stat
Goal:
AI Agent-based Advertising Placement Scraping
Mechanics:
The Banner Stat system consists of three interconnected AI agents that process advertising placements step-by-step, transforming raw data from web pages into structured advertising reports necessary for:
- Monitoring advertising campaigns
- Competitor analysis
- Discovering new advertising strategies
- Analyzing the effectiveness of advertising placements
- Optimizing media planning
Result:
- Automated collection of advertising banners and associated metadata from web pages using Computer Vision (CV)
- Identification of the advertising banner type (video banner, display, RTB block, branded pages, preroll)
- Extraction of advertising attributes such as brand, product category, and advertiser from the collected data
HR AI agent of M-Social
Goal:
Automate new employee onboarding and optimize the company’s HR processes.
Mechanics:
- Training the AI agent using collected employee data and personalized interaction patterns.
- Utilizing Natural Language Processing (NLP) to automate responses to employee inquiries.
- Integration of the AI agent with existing HR management systems.
- Automation of internal surveys, request handling, and communication support.
Result:
- Reduced new employee onboarding time by 35%.
- Employee satisfaction, based on survey results, increased by 30% for new hires and by 15% for existing staff.
Offline deployment of a local LLM solution
Objective:
Enabling LLM operation on the client's infrastructure
Mechanics:
- AI model selection - using open-source models: Llama, Deepseek, Qwen, etc.
- Installation and configuration of necessary software and containerization of the solution for stable operation
- Connection to client's internal systems through secure APIs
Result:
- Complete data confidentiality (information does not leave the client company's perimeter)
- AI operation independent of internet connection and external services
Get a consultation on AI agents for your business
Leave a request for a free consultation, and we will prepare an individual offer for you!
Answers to frequently asked questions
On average, developing an AI agent takes from 2 to 4 months, depending on the complexity of the project.
Text models: OpenAI, DeepSeek, Claude, Mistral.
Image processing: OpenAI Dall-E 3, AKOOL, Google Vision
Video processing: PixVerse, Google Video AI
Local LLVM: Llama, Mistral
To develop AI agents we use PHP and Java programming languages.
Yes, our AI agents can be integrated with various internal and external systems.
We use modern encryption and data protection methods to ensure the security and confidentiality of information.
Yes, we use neural networks that are already trained in various languages.
We provide technical support and updates to AI agents to keep them relevant and effective.
If necessary, we will train your staff and help set up processes.
We will provide recommendations on the necessary technical resources, including servers, software, and network infrastructure, to ensure the effective operation of AI agents.
Yes, they are possible. We will be able to make minor changes even within the framework of technical support.
Let's discuss your business needs
and how AI agents can be useful in solving them
Leave a request and we will contact you to arrange an online meeting