Machine Learning Consulting & Software Solutions

We’ll organize your data to make better decisions. Then build Machine Learning & AI software to improve your business.

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We build AI and Machine Learning solutions for your business

Building computer systems that learn & adapt without following explicit instructions by using algorithms & statistical models to analyze & reveal insights from patterns in data.

Predictive Analytics

Look into the future using past and current data. Get rid of assumptions and discover how your customers are really behaving.

Marketing Analysis

Teach systems to realize text and images as customers go through a check-out flow. Analyze customer behaviors and trends to make smart decisions.

Computer Vision

Analyze data from images or video to look for actionable alerts, find anomalies, or discover trends.

Machine Learning Will Transform Your Business. You Need An Expert Now.

After working on dozens of ML projects (and having a dedicated team), our ML scientists know how to train the models to uncover your problem. Our team is constantly testing "what's possible" and willing to go the extra 1% in accuracy.

Our data scientists can handle all of your data-related requirements including software development, labeling, and modeling. After the algorithm is tested, we wrap the solution in a cloud infrastructure to deliver a fully functioning ML solution.
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NineTwoThree is a Machine Learning Agency

And we apply everything using startup mentality to get the biggest returns for your precious $$$.

Vendor Agnostic

We’re not tied to any providers. We’ll only recommend AI services & tech that’s right for your business.

Industry Agnostic

Years of experience, across several industries, including Health Care, FinTech, Logistics & Supply Chain.

In-House Skills

We have a team of data scientists, researchers, engineers and computer scientists that know what they’re doing

Big Picture

More than just AI. Our software analysts, engineers & project managers will build your entire solution for your entire business.

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Why Machine Learning

Aquafalcon, Sea Lice Detection

​​Lots of fishies under the sea. And they need our help from above the sea. Aquafalcon use underwater cameras to monitor fish in pens—real-time. This helps count & identify fish while also detecting harmful lice. So farms can act proactively by recognizing risks early.

Sea Lice Detection

Live Traffic on Google Maps

​​A billion+ miles driven, across 200+ countries—Every. Day.
A lot of data out there. A lot of patterns to make sense of. A lot of traffic to predict. Google Maps crunches on data to learn historical patterns. Then uses that data to predict best options for people to get where they need to go.

Live Traffic

​​Netflix Movie Selector

​Why think so much between shows? Netflix has the data. And they’ve developed the algorithms to use that data. No more scrolling through endless choices. Netflix curates what you’ve seen to predict what you’ll want next. The more you watch, the more the system learns what you’ll want next.

Mobile Apps

​​Video Surveillance

​​​Imagine a single person monitoring multiple video cameras at once? Video surveillance systems powered by AI help detect crime —before it happens. Imagine alerts for unusual behavior like: hovering around the building, standing still too long or snapping off curious photos. The right people get the right information to take the right action, even if it’s just validating what’s going on.

​​Video Surveillance

​​Tinder’s Swiping Algorithm

​​​​Whoa, 55 Billion+ matches made! Tinder is the king-of-the-hill for meeting new people. Machine learning identifies great matches based on profile pictures. The system learns through A/B testing. As more people see & swipe more photos, algorithms curate and make better matches. Better match-making made with better technology. How nice.

​​Tinder’s Algorithm

Ready to build smart systems
for your biz?

You might not need to predict traffic, suggest shows or match lovers.
But we’re sure you want to use computers + data to improve your business.

Guess less

Make business decisions based more on data & lesson opinions

Product Strategy

Apps that look & work great—earning the same respect as Uber, Pinterest & the rest

Systemize more

Have automated solutions that adjust real-time based on users’ need & wants


Deliver features that are personalised & optimized for each customer

Simplify complexity

Use computers to quickly figure things out that’s too complicated for humans

Work faster

Convert slow manual processes into efficient automated ones


Real Estate Revolution

Dataflik helps real estate investors improve their business marketing operations. NineTwoThree built the machine learning model that generates prioritized lists of motivated sellers faster and more accurately than a human expert.

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Real Estate Revolution

Smart Baby Monitor

Dorel pioneered the segment with a baby camera that sensed the heartbeat and breathing. We made an App that parents loved. (The 2016 version, not the one on the store now.)

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Smart Baby Monitor

Laundry Revolution

Hydrofinity provides cleaner, softer linens in a single wash, while reducing utilities costs and improving customer satisfaction - NineTwoThree built a CES Award Winning Application for best innovation in 2018.

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Laundry Revolution

Video in a Snap

Videosnap creates social media content with overlaid text extracted from just an audio file. We innovated the process in less than three months and created an MVP that raised.

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Video in a Snap

Accelerated AI
Innovation Playbook


Discovery Call

We’ll jump on the call. Yes, Andrew and Pave - the founders. Not some sales rep.

Tell us everything about your vision, the company, your ambitions and your target audience.  

We aim to make CEOs and CTOs look like heroes to their customers.  We excel at helping companies solve complex engineering problems that result in world class mobile and web applications.

Try us out, it's free to contact us - we love ideating.

Contact Andrew

Meet & Plan

We will introduce you to a few data scientist that will work on your business objectives. We typically will ask for a small subset of data and a copy of how your data is stored. (Don’t worry we sign NDA’s too.)

Once we get an understanding of your business objective, NIneTwoThree will present the 30-day prototype plan and delivery milestones along the way.

With Machine Learning, not everything is a success. Experimentation will happen - but our goal is to gain your confidence that we can produce a result that will amaze your co-workers. (We seem to have that effect)



Once the engagement begins our team will conduct an entire scan of the technologies available to use for the mission. This could include Chat-GPT or Open-AI or a legacy NLP  or even humans. Experience here matters, and being able to use the scientific method to create hypothesis is the critical outcome of this step.


Rapid Prototyping

Using a subset of your data and one of the selected algorithms the data scientist will create a series of experiments to prove the best AI choice for your business needs. This includes talking to domain experts, adding additional context, or simply learning from what “doesn’t” work for your business needs.

We predicted which houses would be sold in Ohio better than Zillow.


Project Roadmap

The result of our accelerated innovation AI playbook is a clear development plan. The roadmap will include the recommended approach from the experimentation above and provide you with the necessary information to decide how much profit ML & AI will generate for your business.

Every project we have built so far (over 15) has created more profit for the company than the bill paid to NineTwoThree. From German railroads, to Electric Vehicle charging stations - we work on massive datasets that provide real world solutions to business challenges.

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How Can Artificial Intelligence and Machine Learning Apps Transform Businesses?

Machine learning and artificial intelligence have already established themselves as powerful tools for businesses to harness in their search for efficiency, cost-reduction, and improved operations. 

By relying on these high-tech solutions in the form of applications suitable for everything from early-stage startups to mass enterprises, machine learning is quickly becoming a vital part of the world of business. But how and why these technologies, and is it possible to use them in any industry?

Many companies are data and process-heavy but still rely on traditional methods of managing them. With artificial intelligence apps built by expert agencies housing master machine learning engineers, several industries are already being transformed, from supply chain management to healthcare, eCommerce, and education to name just a few. 

These technologies are helping real-world businesses better understand customer data, automate tedious processes, and have the added benefit of iterating as they scale. That means that if you choose artificial intelligence technology as a solution for your business, it will grow with you.

What is Artificial Intelligence vs Machine Learning?

Machine learning is as the name implies ultimately a learning process. In essence, code is used to create an algorithm that can extract information from labeled or unlabelled data. What makes machine learning techniques different from other types of algorithm models is that the code is made to adapt and change as it gains more information. 

This foundation helps the application identify and analyze patterns, make behavioral predictions or take on other intended goals.

There are also different types of machine learning tools and these different categories have distinct purposes. We discuss artificial intelligence and the key differences in our FAQs below.

What Are The Different Types Of Machine Learning?

Machine learning as a solution is usually divided into four categories: supervised, semi-supervised, unsupervised, and reinforcement learning.

Supervised learning refers to a machine learning algorithm that is manually taught information. Much like a child learning in school, the application is given known datasets and told the desired outcome. Then it’s up to the supervised machine learning algorithm to arrive at the intended destination.

Semi-supervised machine learning solutions are rather similar to supervised learning ones, except the data provided for the algorithm is a mix of known and unknown data sets. The goal here is to teach the algorithm to understand the known data and then to use that as a basis from which to label or categorize the unknown data.

Then there is unsupervised learning. This is the wild west of machine learning, where the algorithm is left to study and interpret large data sets without any input or supervision. The idea here is that the machine learning app will find a way to categorize the data into some sort of structure.

And last but not least there is reinforcement learning. Here, the algorithm is given a set of actions, requirements, limitations, and the expected final values. The machine learning solution tries to achieve the end result through various methods in order to find the most efficient one. The app is allowed to learn through trial and error, which iteratively helps it get to the best end result.

For the difference between machine learning algorithms and machine learning models, check out this post.

How are Machine Learning Algorithms Used In Machine Learning Projects?

Machine learning and artificial intelligence both already have existing footprints in the business world, from smaller companies to some of the largest enterprises around the globe. In fact, different types of AI and supervised learning algorithms are already used to customize experiences on smartphones, web browsers, and other online platforms.

From Tesla’s machine learning models for their autopilot modes to social media platforms adapting to show users content they might like, there is machine learning in more applications today than ever before.

Streaming giant Netflix is said to have saved as much as $1 billion due to its machine learning algorithm for content recommendations,  while Google and other search engines commonly use machine learning to improve their search results, maps, and language translation capabilities. And they aren’t the only ones - companies like Salesforce and Hubspot use it to enable user automation that improves marketing flows.

Why is Machine Learning Mastery Essential for Businesses?

Machine learning is an incredible tool because it is both flexible and adaptable. This type of technology can be applied to any industry, and all industries can enjoy the benefits of improved efficiency, data-tracking, cost reductions, and much more. 

What makes these algorithms even more powerful is that they can go from as simple as tracking sales or social media performance to complex solutions for language or audio recognition. 

The most important thing to know about machine learning for businesses is that it is vital to work with a machine learning agency that has a proven track record in delivering machine learning and AI solutions for various industries. Choosing the wrong machine learning partner can be highly detrimental and end up costing businesses thousands of dollars in wasted time and effort. 

NineTwoThree Venture Studio is an experienced machine learning agency most recently honored for the second time by Inc. 5000 and having been ranked as the top development and mobile app development company in Boston by 

Let us organize your data to make better decisions or build Machine Learning and AI software to improve your business.

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5 FAQ About Machine Learning App Solutions

1. What is AI vs machine learning?

Artificial intelligence and machine learning are often grouped together but there are slight differences to be aware of. Artificial intelligence is most often targeted at simulating human behavior while machine learning is more like a computer using the information to improve its own intelligence.

2. Why is machine learning used?

Machine learning is becoming a widely-used tool because it has so many applications along with the potential to grow and improve as a solution with time. Implemented correctly, machine learning solutions can bring plenty of benefits that can improve or automate business processes and more.

3. Who uses machine learning?

Machine learning is used in all kinds of technology use cases, from social media networks to self-driving cars, banking, online shopping, and even voice recognition or language processing. This means these solutions are implemented by a variety of industries around the world.

4. What is the purpose of artificial intelligence?

There is a general overarching goal when it comes to artificial intelligence, and that is to create software that is not only able to process inputs and outputs but also to develop its own reasoning behind those decisions without a human guiding it.

5. What is deep learning and how does it work?

Deep learning is a subset of artificial intelligence and machine learning that use detailed and multi-layered data structures in order to represent that data in multiple ways when outputting the end result. It’s essentially a neural network that makes use of at least three layers and is a simpler mimic of the human brain’s functioning.