It is believed that artificial intelligence and neural networks are a prerogative only of large corporations with large budgets. In reality, everything is different: machine learning technologies are available to small businesses, and often it is the small companies that get the greatest return from implementing AI. In this article, we will understand why the use of neural networks is becoming increasingly in demand among small and medium-sized businesses (SMB), what is the advantage of custom solutions over ready-made ones, and we will give examples of real cases. At the end, you will find a link to a cost calculator that will help you orient yourself in the budget for developing a neural network.
1. Why neural networks are now available not only to corporations
1.1. Development of cloud services
In recent years, major cloud providers (AWS, Google Cloud, Yandex Cloud, and others) have begun offering ready-made modules for machine learning. This lowers the entry barrier: companies can avoid spending on servers and infrastructure, and pay only for actual usage. This model is especially convenient for small businesses, as it does not require significant initial investments.
1.2. Appearance of diverse frameworks and libraries
Open-source frameworks (TensorFlow, PyTorch, etc.) have significantly simplified the development of neural networks. As a result, developers create and configure AI modules faster. Even if there is no in-house data scientist in the company, you can hire a contractor – for example, our EasyByte team – which will develop the necessary solution "turnkey".
1.3. Increased competition
In a competitive market, small companies are looking for ways to stand out from competitors. A neural network can be that "accelerator" that optimizes business processes and increases revenue. Moreover, the gain in productivity and quality of service may be even more noticeable than in large corporations, since in SMB solutions are implemented faster and more flexibly.
2. Main tasks that neural networks solve in SMB
- Automation of routine processes
- Processing applications and emails from customers.
- Primary analysis of resumes of applicants (for HR).
- Text recognition from documents (e.g., scans of contracts).
- Personalized product and service recommendations: even if you have a small online store, a properly configured recommendation system will increase the average check.
- Chatbots for customer interaction 24/7.
- Analysis of the customer base, forecasting demand and interest in new products.
- Forecasting revenue, expenses, and demand.
- Reducing the risk of loan and debt arrears (if the SME operates in the financial sector).
- Monitoring requests and feedback, identifying problem areas.
- Automatic sorting of requests for quick response.
- Analysis of call quality (speech recognition, identification of keywords).
3. Myth #1: "Neural networks require huge budgets and a team of specialists"
At first glance, it may seem that artificial intelligence is a complex technology that "costs a million" and requires a whole staff of highly paid experts. But let's figure out why this is not always the case:
- Scalability
If you need to process a small stream of data, you can get by with an inexpensive cloud solution. You pay for the resources you actually use. - Competition and Availability
There are a large number of contractors on the market who know how to develop inexpensive AI solutions. Their competencies allow them to perform a turnkey project, and if necessary - retrain your models and scale them as your business grows. - Return on Investment (ROI)
Implementing a neural network can pay off much faster than traditional IT systems. Reducing manual labor, increasing conversion and customer satisfaction directly affect profit growth.
4. Ready-made solutions vs. custom development: what to choose?
Small and medium-sized businesses often face the question: to take a ready-made "off-the-shelf" software solution (e.g., a ready-made chatbot or predictive analytics service) or to order a custom neural network adapted to their tasks?
4.1 Ready-made solutions
- Pros
- Quick start: you can connect immediately and start using it.
- Low cost in the initial stages, while business processes are not complex.
- Cons
- Limited functionality. If you have a specific process or non-standard data, a ready-made solution may not cope with it.
- Scalability difficulties. When the business starts to grow, the capabilities of a ready-made service may quickly be exhausted.
- Periodic subscriptions and additional paid features can become a significant expense in the long term.
4.2 Custom solutions
- Pros
- Flexible configuration: the model learns from your data, taking into account all nuances and subtleties.
- Scalability to business needs: you can increase power and add new modules.
- Uniqueness: you are not dependent on ready-made services and do not pay endless license fees.
- Cons
- Higher initial cost compared to implementing a ready-made standard solution.
- Time is needed for designing and training the model, as well as for collecting and labeling data.
However, if you consider the investments in the long term, custom development is often more profitable, as it better solves the tasks of your business, improves service quality and reduces manual labor.
5. Examples of successful AI implementation in small business
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Store of author's craft goods
- Task: increase the average check.
- Solution: using a custom recommendation system trained on purchase history, the store began to offer customers "related products".
- Result: 15% increase in average check and increased customer engagement.
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Small travel agency
- Task: Answer customer inquiries around the clock.
- Solution: Implementation of a chatbot with NLP (Natural Language Processing) elements. The bot selected tours based on specified criteria and answered common questions.
- Result: 40% reduction in workload for managers and an increase in the number of applications during non-working hours.
6. How to implement a neural network in SMEs: practical tips
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Define a specific goal
Don't «just try AI». Clearly formulate the task: increase sales, reduce manual routine, improve customer service, etc. -
Analyze data
Even small businesses typically already have some data (CRM, Excel spreadsheets, Google Analytics). It is important to understand whether this data is sufficient and in what quality. If necessary, you can use external datasets or collect additional information. -
Assess resources
- What is your budget at the initial stage?
- Are there specialists who will participate in the project or do you need to attract them from outside?
- How much time are you willing to spend on integration?
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Think about infrastructure
Neural networks can be trained on your own servers or in the cloud. For small companies, the cloud is usually more profitable due to the absence of capital costs for equipment. -
Choose a reliable contractor or internal team
For most SMEs, it is easier and cheaper to turn to professionals than to delve into the intricacies of developing and training models independently. -
Plan staff training
It is important that employees understand how the new system works and how to use its results.
7. Why custom neural networks can be an ideal solution for SMEs
- Unique Feature Accounting
Every business is unique: from assortment to ways of interacting with customers. Ready-made solutions rarely can adapt to all nuances. - Deep Integration
Custom development allows you to embed a neural network into an existing infrastructure: from CRM and ERP to internal databases and web services. - Long-term Savings
Yes, a custom solution requires certain investments at the start. But in the future, you only pay for the development and improvement of your system, not for periodic subscriptions, which are often present in ready-made solutions. - Flexibility and Scalability
The model can be adjusted and scaled as the company grows, adding new modules (recommendation service, computer vision, etc.) without rigid restrictions.
8. Conclusion: How to Avoid Missing Out on Your Profit
Small and medium-sized businesses often react faster to technological innovations than large corporations. Neural networks, with the correct task setting and грамотной integration, allow you to gain a competitive advantage, increase sales, optimize costs and improve service.
If you are considering implementing a neural network or want to assess possible expenses, we offer an online cost calculator on our website EasyByte. With its help, you can get an approximate budget estimate, which can then be clarified during detailed communication with our experts.
Don't delay: technologies are developing rapidly, and companies that are the first to master AI tools can already occupy a significant share of the market tomorrow. If you have questions or need specialists to develop a custom neural network for your tasks — contact us at EasyByte, we will help your company become even more efficient.