If you’ve been paying attention to the headlines for the past few years, you’ll know we are now experiencing another revolution in computing. As computer power increases, artificial intelligence techniques that once seemed out of reach are now increasingly becoming commonplace. It’s clear that to remain competitive, you need to be using these techniques wherever you can.
Beyond General Purpose
The rise of general purpose algorithms like ChatGPT, Anthropic’s Claude, and Google’s Gemini has made using generative AI more approachable than ever before. These foundational models have democratized access to artificial intelligence, enabling businesses of all sizes to experiment with automation, content generation, and intelligent assistance without requiring deep technical knowledge or significant upfront investment.
However, moving beyond what a general-purpose algorithm can do for your business requires technical expertise and careful effort. While these models excel at broad tasks and demonstrate impressive capabilities across diverse domains, they often fall short when it comes to understanding the nuances of specific industries, company cultures, or proprietary processes that define competitive advantage.
The latest capabilities in AI leverage not only the general knowledge developed by the major AI companies, but also the ability to reach inside your own datasets to provide more tailored and more reliable responses to your prompts. This represents a fundamental shift from one-size-fits-all solutions to customized AI systems that understand your unique business context.
First, You Must Understand What Problem You Hope To Solve
It’s also important to know what problem you are trying to solve. You may not know exactly what patterns your data contains, but it is helpful to know what you are hoping to achieve. For example, you might have a goal of saving fuel across a fleet of vehicles, or reducing customer service calls, or shortening the time needed to complete an industrial process. In order to get to your destination, you’ll need to know what direction to start traveling. We often find that a simple conversation about your biggest headaches as a business leads to the identification of a key problem.
There Are Many AI Techniques To Choose Between
A whole range of techniques exist in the AI and Machine Learning space, and depending on the problem, some are more effective than others.
At the lowest end of the complexity scale are rule-based systems, which have the benefit of being extremely fast and inexpensive to run.
In the intermediate range of complexity, statistical analysis of data leads to pattern identification within your data. This is a key step in many systems, where the main goal is to identify when something happens so that action can be taken. These techniques, including support vector machines, random forests, and Bayesian networks, represent the mathematical foundation of modern machine learning. They excel at finding relationships and correlations that human analysts might miss, particularly in datasets with multiple variables and complex interactions.
At the far end of the complexity scale are the generative AI models that have become extremely important for generating text, images, and even code. While writing a Large Language Model is likely outside what is achievable for the Small to Medium-sized business, interacting with these models through new techniques like MCP (Model Context Protocol) is a way to augment general purpose tools for your business’ specific needs.
Putting Together a Plan
Given the huge spectrum of sophistication that is out there, it can be extremely intimidating to begin a journey into these advanced technologies. SynaTree can help you develop a plan to gather the right data, and implement a sophisticated solution. We can help you develop a program that is appropriate for the scale of your business and that uses many of the most advanced techniques.
We can help you:
- Optimize processes to reduce costs or improve performance
- Recognize patterns
- Predict what will happen next
- Understand the content of documents and photographs
- Identify hidden variables
- Utilize the offerings of third-party AI vendors
- Integrate AI into every level of your operation
- Build interconnections between LLMs and Chat bots and your proprietary data
Partnering Up
As with our Software as a Service offerings more generally, AI tools are developed using our low cost development approach.