You’ve probably seen the buzz around AI models like ChatGPT or Gemini. They’re powerful, but here’s the truth: those generic models are built for everyone, not for your business. For small and mid-sized companies, that often means irrelevant answers, data privacy issues, and wasted potential.
TL;DR
- AI models are systems trained to recognise patterns and make predictions or generate content.
- Generic models are broad and often miss the context, tone, or data accuracy SMBs need.
- A custom model uses your business data to improve performance, accuracy, and relevance.
- Kleritt helps design, train, and deploy models tailored to your workflows and goals.
What Are AI Models?
An AI model is an algorithm trained on large sets of data to perform a specific task, like recognising text, predicting behaviour, or automating decisions. Think of it as a brain that learns from examples.
There are different types:
- Language models (like GPT) that generate or summarise text.
- Predictive models that forecast outcomes (e.g. sales, churn, demand).
- Recommendation models that suggest products or actions.
- Vision models that detect or classify images.
Each model learns patterns from data, then applies that knowledge to new inputs. The quality of the model depends heavily on the data it’s trained on, which is exactly where generic AI often fails small businesses.
Why Generic AI Models Don’t Fit SMBs
Big tech models are trained on massive, general-purpose datasets. That makes them broad and flexible, but not precise. For SMBs, that creates several issues:
- Lack of context: Generic AI doesn’t know your products, processes, or tone of voice. It gives generic outputs that often miss the mark.
- Data privacy concerns: Using public AI tools may expose sensitive business or customer data to third-party systems.
- Limited integration: Off-the-shelf models can’t easily connect to your CRM, ERP, or internal data sources.
- No measurable ROI: Because they’re not tuned to your goals, it’s hard to track or improve performance.
For example: a logistics company asking a general AI model to optimise delivery routes won’t get accurate results, because it lacks local data, real-time constraints, and company-specific rules.
Why a Custom AI Model Is Better
A custom AI model is trained on your business data, your emails, customer records, documents, or sales history. That allows it to understand your unique patterns, priorities, and terminology.
Key advantages:
- Accuracy: Predictions and outputs reflect your real-world data.
- Control: You decide what data is used, stored, and updated.
- Efficiency: Models can automate processes specific to your operations.
- Compliance: Data stays within your environment, meeting GDPR and security standards.
- Brand alignment: The tone, wording, and responses match your company’s voice.
By training a smaller, targeted model, SMBs achieve far more value than trying to adapt a massive general-purpose system.
How Kleritt Builds Custom AI Models for Your Business
At Kleritt, we design AI solutions that are tailored, not templated. Our approach keeps things practical and transparent, no hype, just results.
Here’s how we do it:
- Discovery: We analyse your workflows and identify where an AI model can add measurable value (e.g. automating support, predicting demand, classifying data).
- Data mapping: We help you organise and clean your data, ensuring it’s safe, compliant, and ready for training.
- Model selection & fine-tuning: Depending on your needs, we adapt an existing open-source model or build a lightweight one from scratch, optimised for your use case.
- Integration: We connect the model to your current systems using APIs or no-code tools, so it fits seamlessly into daily operations.
- Testing & training: We validate accuracy and train your team to use and maintain it.
- Continuous improvement: As your business grows, the model learns and evolves with new data.
The result: a model that’s yours, not another generic tool in the cloud.
When to Consider a Custom Model
You should think about a tailored AI model if you:
- Handle unique or sensitive data (e.g. pricing, clients, or documents).
- Need consistent tone or output (e.g. branded content or client reports).
- Want to automate specific processes that off-the-shelf tools can’t handle.
- Care about privacy and want full control over your data and results.
FAQ
Q: Do I need to build a model from scratch?
A: Not always. Kleritt often fine-tunes existing open-source models, faster, cheaper, and perfectly suited for SMB budgets.
Q: How long does it take?
A: A pilot model can be ready in 4–8 weeks, depending on the use case and data readiness.
Q: Is my data safe?
A: Yes. All data stays within secure European environments and complies with GDPR.
Q: Can I keep improving the model later?
A: Absolutely. The model can be retrained as your business collects new data, so it keeps learning and improving.
