Custom Machine Learning Solutions that Learn & Adapt to Your Business

Use your organization’s data to automate tasks, identify trends, and predict future outcomes. Our team  of machine learning consultants, data scientists and engineers will  develop software that streamlines operations, increases  profits, and makes better decisions.
Trusted By
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We’ve Been Building Machine Learning Solutions Since 2017

This isn’t our first rodeo! We launched our first machine learning solution in 2017. We’ll partner with you to build self-learning systems that use algorithms and statistical models to identify patterns in data and make predictions.
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Predictive Analytics
Identify the likelihood of future outcomes based on historical data
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Large Language Models
Build custom solutions that help drive efficiency such as  chatbots and intelligent assistants
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Forecasting and Trends
Analyze data from images or video to look for actionable alerts, find anomalies, or discover trends.
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Smart Insights
Analyze customer behaviors and deliver personalized experiences that drive loyalty
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Recommendation Engines
Create systems that recommend the next best action based on past results
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Anomaly and Fraud Detection
Determine outliers and or fraudulent data points to take action sooner

Machine Learning Solutions

Recognizing Harmful Lice

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Recognizing
Harmful Lice

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Aquafalcon monitors fish in pens in real-time so they can detect harmful lice and proactively protect their fish farms.
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Aquafalcon monitors fish in pens in real-time so they can detect harmful lice and proactively protect their fish farms.

Real-Time Routing

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Real-Time Routing

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Google Maps crunches on data to learn historical patterns, then predicts the best options for people’s routes.
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Google Maps crunches on data to learn historical patterns, then predicts the best options for people’s routes.

Personalized Playlists

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Personalized
Playlists

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Spotify knows what you like based on your listening patterns and uses that knowledge curate the perfect playlist.
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Spotify knows what you like based on your listening patterns and uses that knowledge curate the perfect playlist.

eCommerce Discounts

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eCommerce
Discounts

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eCommerce companies can send promotions to customers based on their inclination to buy with or without coupons.
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eCommerce companies can send promotions to customers based on their inclination to buy with or without coupons.

Hospital Re-Admittance

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Hospital Re-
Admittance

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Hospitals can treat patients based on the likelihood of re-admittance and prioritize those who will need more care.
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Hospitals Can Treat Patients Based On The Likelihood Of Re-Admittance And Prioritize Those Who Will Need More Care.
TANDHONI RAO, FORMER CTO OF XEROS TECHNOLOGIES

"They're able to synthesize requirements and provide alternative ways of thinking about things. They really go through that extra effort to make those suggestions, so you should take advantage of that. Their insights are very valuable and that distinguishes them from other providers."

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Get Predictive Super Powers

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.
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Custom
Your business is unique. Your web and mobile apps should be too. That’s why we build everything from scratch, every time.
Flexible
Flexible
Your needs can change based on the market. We grow or shrink with you because your needs are our priority.
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Transparent
We meet weekly and give you access to our tools so you always know what’s going on with your app.
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Flat-Rate
We’ve been doing this for so long that we know exactly what it takes. Our last 27 projects finished 7% within budget.
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Talented
We are the best because we hire the best and all of our developers have been on the team for over a year.
Effective
Effective
We get it right the first time so you can forecast the future and meet your goals.

An Award Winning Software Design, Engineering & Marketing Studio

We help established brands iterate like startups and startups scale like established brands. Partnering with industry leaders and visionary entrepreneurs we focus on profit producing applications that are a delight to use. We leverage this transformation through the power of agile methodology, design thinking and impeccable engineering to help our clients rapidly identify and validate new products. And we have the stats to back it up...
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70

Experts

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75

Products

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14

Startups

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12

Years in business

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#1

Boston Agency

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4

Years in a row

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Clutch global spring 2025
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Meet Your Data Science and Machine Learning Team

Our data scientists can handle all of your  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 Machine Learning solution.
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Alex

Senior level solution architect with a vast history of Machine Learning projects. Most notably, Alex implemented a model that allows EV station owners to predict which stations were available to charge the vehicles. This was a massive undertaking that operates the largest EV market in Europe.

8 Years Experience with NineTwoThree
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CERTIFICATIONS
• AWS Certified Solutions Architect
• Machine Learning with TensorFlow Google Certified
• Google Data Analytics Professional Certificate
• AWS Certified Cloud Practitioner
• Master in Computer Science, with MBA
data scientist

George

Senior Level Data Scientist with world renowned results for NLP models in both the Human Resource hiring process for a major USA company and replicating therapists - scoring equivalent to humans using GPT-3. Also supported the EV charger station project for the US market.
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4 Years Experience with NineTwoThree
• Machine Learning Neural Networks Certificate
• Improving Deep Neural Networks Certificate
• Convolutional Neural Networks Certificate
• Natural Language Processing with Vectors Spaces (Deeplearning.ai)
• Statistical Inference from John Hopkins University
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Vova

Skilled Data Scientist with 4-years experience in computer vision, clustering analysis, object detection and tabular data classification. Also well acquainted with classification, decision trees, data pre-processing, cleaning, as well as neural networks.
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4 Years Experience with NineTwoThree
• MLOps Professional Training Program
• AWS Cloud Practitioner
• Computer Vision and Artificial Intelligence from Abto
• Natural Language Processing with Vectors Spaces (Deeplearning.ai)
• Statistical Inference from John Hopkins University
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Slava

Skilled Data Scientist with experience in computer vision, clustering analysis, object detection and tabular data classification. Built out a prediction model for 3d CT scans to predict the lungs capacity to detect pulmonary fibrosis for a major medical research company in Sweden.
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2 Years Experience with NineTwoThree
Deep Learning DeepMind Certified Course
• CNN DeepMind Course Certification
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Oleksii

Skilled Machine Learning Engineer with experience in computer vision (text recognition, face recognition) and natural language processing (text classification with neural networks and gradient boosting machines, recommendation systems, cognitive search). Contributed to cutting-edge projects in text analysis and recognition for various applications.

2 Months Experience with NineTwoThree

CERTIFICATIONS
Generative AI with Large Language Models
• Deep Learning Specialization
• Machine Learning Specialization
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Vitalijus

Data Scientist with over 5 years of experience focused on ML, holding a PhD in Deep Learning. Experience in startup and enterprise environments across globally distributed teams. Proactive individual with quick adaptation to new environments, both technically and socially. Skilled in leading projects, managing data teams, and providing mentorship.

1 Year Experience with NineTwoThree

CERTIFICATIONS
Build and Deploy Machine Learning Solutions on Vertex AI
• Functional Program Design in Scala
• DE100 Data Engineering & Big Data Course
• IBM AI Engineering Specialization
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Jurgis

Machine Learning Engineer with over 5 years of industry experience. Proven track record of deploying robust end-to-end Data Science/ML pipelines and driving transformative data initiatives across multiple companies. Skilled in leading projects and managing data teams.

1 Year Experience with NineTwoThree

CERTIFICATIONS
Machine Learning Specialisation
• LLM Application Development
• HashiCorp Terraform Associate
• Tensorflow 2 & Keras Deep Learning
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Our Machine Learning and AI Case Studies

Everytown

Gaurdrailed an LLM to Surface Political Facts

Everytown wanted a way to quickly surface facts from their inventory of articles and facts. NineTwoThree built a vector knowledgebase and semantically searched tables and blogs to help researchers save time finding answers.

Consumer Reports

Next Generation Conversational AI

NineTwoThree was selected by the CR Innovation Lab to help build an experimental chatbot that combines the power of AI with CR's expertise to answer your questions and offer product recommendations. NineTwoThree helped design and implement the system alongside CR’s engineering and product team.

Protect Line

Protect Line Saves $Millions Using GenAI Chat for Customer Service

Protect Line wanted to reduce costs and improve their online chat experience, NineTwoThree built a GenAI Chatbot that improved sales efficiency creating $5,000,000 of additional Revenue.

Rank Logic

Improving SEO Content With AI And Dashboards

Rank Logic, founded by Spencer Haws, is a keyword and content-tracking plugin made for WordPress. The tool allows users to track new SEO strategies, including which author performs better, understand page-level metrics, and optimize content based on best practices. This is the ideal tool for bloggers, niche site creators, and anyone who has a content-heavy website.

LaunchLabs

Making More Powerful Lookalike Audiences With Machine Learning

Launchlabs wanted to improve their advertising platform with better audience attribution. NineTwoThree created an audience based on ML algorithms that performed better than Facebook's audience by 7x.

Cymbiotika

Cymbiotika Uses ML to predict 1000s of Sales

Cymbiotika wanted to predict which product customers might be interested in after receiving bits of customer data. NineTwoThree analyzed previous behaviors and created a Machine Learning model that predicted products better than current methods - thus increasing sales.

Prisonology

Prisonology Decreased Legal Consultation Time by 90% with AI

Prisonolgy needed a venture partner to grow operations. NineTwoThree created an AI model that reduced consultation time by 90% using reasoning tactics in OpenAI and increased sales 2x in 4 months.

PMI

PMI Reduced Self-Assessment Test Time By 80%

PMI transformed the way students prepare for its certification exam by adopting gamification. We built a new assessment together that reduced test time by 80% and offered instant feedback.

Mental Health Company

Built an AI Chat with a 4.7/5 Human Rating

NineTwoThree developed a conversational AI for a mental health company that expedites connecting individuals with certified professionals for ESA Letters

Dataflik

Predicting Houses For Sale With 85% Accuracy

Dataflik helps real estate investors improve their business marketing operations. NineTwoThree built the machine learning model that predicts which houses in America will be listed for sale with 85% accuracy.

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Bring Your Innovation to Life in 6 Steps

1
Brainstorm

Ideate With Us

We’ll jump on a call. Yes, our founders, Andrew and Pavel – not some sales rep.

Tell us about your vision, the company, your data sources, and anything else that can help us know more about you.

We’ll brainstorm with you in real-time and figure out what you need to get your machine learning solution off the ground.

We’ve built numerous solutions and can tell you all the ways we can bring your idea to life.
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formulate

Project Scoping

After our first call we’ll sign the NDA’s and bring on our team. Our engineers and data scientists will ask questions to learn more about your business processes, understand your goals, and understand any constraints. We will ask for and review sample data and try to get a grasp about your existing systems. Together we can narrow down what’s feasible and realistic within the context of your larger vision.
3
proof of concept

Prototyping & Planning

If there’s a good fit, then we’re ready to start work! During the prototyping and planning phase we’ll focus on measuring the predictive ability of your data. Based on our ideas from solution blueprinting, we’ll create a small, achievable prototype that takes 4-6 weeks to build. We’ll assign a team including an engineer, product manager, and project manager that will experiment with your data and make sure we can achieve your goals with the right models. We’ll then build out a roadmap on how to implement machine learning into your business based on data sources, data storage, and machine learning modeling best practices.
4
Launch

Taking it to Production

From here, we will work to build together based on our agreed upon roadmap. We’ll build the necessary data, training, retraining, and machine learning pipelines that willproduce the insights you need and work on performance optimization. Our implementation will focus on creating a user-centric system with the ability to handle real-world workflows that comply with security and regulatory standards. As we move into production we will shift to continuous integration and deployment processes, and ongoing performance monitoring that ensure the system is efficient and reliable in your environment.
5
develop

Build & Grow

Model Routing Strategies:
Each task is detailed with all the screen designs, stories, descriptions and acceptance criteria ready for QA to test its completion. This radical transparency allows you to see the same picture we see and assures you we are on track.
6
scale

Product Growth Strategy

Now that we understand the business model that helps your company innovate - we can prototype the product that serves that purpose. We will build a “Golden Path Prototype” that lets us all understand how the app will look and feel. More importantly, we can perform usability testing on customers to get immediate feedback to ensure we are in the right direction.

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

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