Machine learning development

Innowise delivers more than algorithms — we bring a fundamental shift in how you operate. From automating routine tasks to enhancing customer experiences and predicting market trends, we build ML systems that grow with your business, eliminate inefficiencies, and unlock new revenue streams.

40+

completed machine learning projects

40+

AI/ML engineers

75%

mid & senior-level developers

40+

completed machine learning projects

40+

AI/ML engineers

75%

mid & senior-level developers

Transform your business with expert ML development services

Extract actionable insights

Convert complex datasets into strategic advantages. Whether analyzing customer behavior or product usage metrics, our ML solutions transform raw data into actionable intelligence that drives decision-making and uncovers hidden opportunities.

Upgrade customer experience

Deliver exceptional service through intelligent automation. Our ML systems predict customer needs, enable hyper-personalized interactions, and power sophisticated conversational AI – resulting in higher satisfaction rates, reduced response times, and increased loyalty.

Fortify security defenses

Stay ahead of evolving threats with proactive protection. Our ML security solutions detect anomalies in real-time, identify emerging attack patterns, and preemptively address vulnerabilities before they can be exploited, creating a robust security ecosystem.

Scale with confidence

Expand without limitations. Our enterprise-grade ML infrastructure adapts seamlessly to new markets and fluctuating demands, learning from fresh data inputs while maintaining performance across diverse environments.

Automate with intelligence

Free your talent for strategic work. Our ML automation solutions handle routine operations with precision, orchestrating complex workflows behind the scenes while your team focuses on innovation and high-value initiatives.

Increase sales

Convert leads faster with data-driven targeting. Our ML algorithms identify high-intent prospects, personalize offers in real-time, and optimize pricing strategies — helping you close more deals and maximize revenue.

Our featured machine learning development services

Artificial intelligence

Neural network development

Deep learning

Big data & predictive analytics

Computer vision

Speech recognition

Sentiment analysis

Natural language processing

Robotic process automation (RPA)

Artificial intelligence

We craft AI solutions that think, learn, and adapt — helping businesses automate decisions, personalize experiences, and unlock entirely new ways to create value for your business.

Neural network development

Our engineers develop advanced neural networks using architectures like CNNs, RNNs, and transformers — tested in real-world scenarios like fraud detection, medical diagnostics, and industrial monitoring.

Deep learning

We develop deep learning models for image, video, text, and voice — helping you extract value from messy, unstructured data with cutting-edge accuracy and performance.

Big data & predictive analytics

We take your overwhelming volumes of data and turn them into clear, confident forecasts. That way, you're not just reacting — you're making smart moves in high-pressure situations.

Computer vision

From real-time defect detection to complex image recognition, we engineer systems that turn raw visual input into real-time decisions.

Speech recognition

We build systems that convert speech into text your software can understand — accurately, in real time, even in noisy settings or with specialized terms.

Sentiment analysis

Understanding words is one thing, but understanding emotions is another. Our sentiment analysis models tune into what people really mean, giving you the edge to adapt products, services, and messaging on the fly.

Natural language processing

When your systems need to work with language, not just numbers, we use NLP models to help them read, understand, and generate text that makes sense in real business scenarios.

Robotic process automation (RPA)

We roll out RPA that clears out repetitive work — plugging into your systems, taking over the boring bits, and letting your teams focus on what really moves the needle.

Artificial intelligence

We craft AI solutions that think, learn, and adapt — helping businesses automate decisions, personalize experiences, and unlock entirely new ways to create value for your business.

Neural network development

Deep learning

We develop deep learning models for image, video, text, and voice — helping you extract value from messy, unstructured data with cutting-edge accuracy and performance.

Big data & predictive analytics

We take your overwhelming volumes of data and turn them into clear, confident forecasts. That way, you're not just reacting — you're making smart moves in high-pressure situations.

Computer vision

From real-time defect detection to complex image recognition, we engineer systems that turn raw visual input into real-time decisions.

Speech recognition

We build systems that convert speech into text your software can understand — accurately, in real time, even in noisy settings or with specialized terms.

Sentiment analysis

Natural language processing

When your systems need to work with language, not just numbers, we use NLP models to help them read, understand, and generate text that makes sense in real business scenarios.

Robotic process automation (RPA)

We roll out RPA that clears out repetitive work — plugging into your systems, taking over the boring bits, and letting your teams focus on what really moves the needle.

Drowning in messy data with no clear direction?

Let ML turn that chaos into clarity.

Our work in machine learning development

Industries our ML development services transform

Finance
Healthcare
Retail & E-Commerce
Manufacturing
Energy & Utilities
Telecommunications

Finance

Machine learning is flipping finance from reactive to predictive. We help companies outsmart risks, sniff out fraud before it surfaces, and read market moves before the competition even blinks.

Predictive risk management
Real-time fraud detection
Intelligent market forecasting

Healthcare

Machine learning is transforming healthcare from the inside out — driving sharper diagnostics, truly personalized treatments, faster drug discoveries, smarter risk prediction, and freeing up medical teams from routine admin work.

Early disease detection
Personalized treatment strategies
Accelerated drug discovery

Retail & E-Commerce

In retail, AI isn't a trend — it's the new baseline. We help businesses predict what customers want, adjust inventory on the fly, catch fraud before it costs you, and keep prices in sync with real-world demand.

Predictive customer insights
Smart inventory management
Frictionless shopping experiences

Manufacturing

In manufacturing, machine learning is the quiet force reshaping the factory floor. It optimizes production flows in real time, inspects products for defects on the line, and forecasts supply chain disruptions before they cause delays.

Reduced unplanned downtime
Higher product quality
Faster, more efficient production cycles

Energy & Utilities

With ML, the energy sector isn't just getting greener — it's getting smarter as well. Our models forecast demand swings, spot grid vulnerabilities before they spark outages, and help utilities shift to renewables faster without missing a beat.

Early detection of grid failures
Reduced energy waste and costs
Faster response to equipment malfunctions

Telecommunications

As machine learning takes hold, networks can now predict traffic spikes before they hit, reroute bandwidth on the fly, spot fraud before it drains revenue, and fix issues before customers even know there's a problem.

Reduced downtime and service disruptions
Stronger resilience against unexpected network loads
Lower operational and maintenance costs

Machine learning solutions we build

Predictive maintenance

Fraud detection

Demand forecasting

Dynamic pricing

Virtual assistants & real-time chatbots

Marketing automation solutions

Customer behavior analysis

Document, image & video processing

Smart recommender systems

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Philip Tihonovich

Head of Big Data Department

As noted in PluralSight’s AI Skill Report, 97% of companies deploying AI technologies report gains in productivity, service quality, and accuracy. Now, it’s clear: machine learning has shifted from a nice-to-have to a business-critical engine. It’s no longer about building models that look good in a lab — it’s about setting up living, breathing systems that learn, adapt, and drive real results where it matters most.

Philip Tihonovich

Head of Big Data Department

Our approach to machine learning development

At Innowise, we combine deep expertise in data science, MLOps, and model architecture design to build solutions that are not only accurate but also scalable, interpretable, and resilient in production.

Requirement analysis

We start by translating business challenges into ML objectives. Clear goals upfront lead to models that actually deliver measurable impact.

Data preparation & processing

Before any model sees the light of day, we dig into the data — cleaning, structuring, and transforming it into a form that a machine can truly learn from.

Feature engineering

We transform cleaned data into smart inputs — choosing the right features, encoding categories, scaling numbers, and removing noise so the model can focus on real patterns.

Model development

We train models using the right algorithms, tune parameters, and validate performance to build solutions that work in real-world conditions.

Model deployment

Once the model is trained and validated, we prepare it for real-world use. This includes setting up APIs or batch processing pipelines, integrating the model with your existing systems, and more.

Model tuning

Performance isn't a one-and-done deal. We monitor, fine-tune, retrain, and adapt models over time to keep them sharp.

Get your ML algorithms maintained by professionals

With 40+ expert ML engineers and 40+ successful projects, we help businesses turn data into real growth. From smarter decision-making to faster operations, our models are built to solve real-world challenges, boost efficiency, and open new revenue streams.

Platforms we work with

Vertex AI
Google Conversational AI

Google AI for documents
Google AI for industries

Azure Cognitive Services
Azure Machine Learning

Azure Bot Services
Azure Applied AI Services

Amazon SageMaker
Amazon Transcribe & Polly

Amazon Comprehend
Amazon Rekognition

Choose your pricing model

Fixed price

If you already have a clear idea of what you need, a fixed price is the simplest way forward. You’ll lock in the budget and deadlines upfront, so you can stay focused without worrying about unexpected costs.

Time & materials with a cap

If you’re still shaping the project or expect things to change along the way, the time and material model gives you the flexibility to adjust. You’ll pay for the work as it happens, which is perfect for ML projects.

Tired of one-size-fits-all software?

We create ML solutions built around your business needs.

What our customers think

Tim Benedict CTO Vitreus

“Innowise has successfully delivered the client's MVP, marking the project's success. The team has offered excellent project management, as they're highly efficient and always deliver on time. Overall, their passion and depth of expertise are outstanding.”

Industry Business services
Team size 30 specialists
Duration 15 months
Services Architectural design, blockchain, custom development

Ory Goldberg CEO Traxi

“I'm very satisfied with their high-quality work and ability to deliver exactly what I want through a very professional approach. Their flexible and available process is key to the ongoing project's success."

Industry Software
Team size 10 specialists
Duration 24+ months
Services Mobile development, web development

Davide Criscione Founder & CEO DC Services GmbH

“Innowise has found high-quality resources that fit well within their assigned internal teams. They had the resources ready to start in a short period. The team offers responsive and personable project management. Moreover, they're proactive and don't overpromise.”

Industry IT services
Team size 12 specialists
Duration 15+ months
Services Staff augmentation

FAQ

How much does machine learning app development cost?

Budgets typically fall between $40K–$200K. Costs depend on data preprocessing, model architecture (e.g., regression, CNNs, transformers), infrastructure (cloud/on-prem), and integration scope.

How long does it take to build a machine learning model?

There’s no one-size-fits-all answer — simple models with clean data can be built in a few weeks, but real-world projects usually stretch over several months. A lot of time gets spent not on building the model itself, but on wrangling messy data, crafting meaningful features, tuning hyperparameters, and stress-testing the model across different scenarios.

How does Innowise address potential biases in ML models?

We start by checking the data, looking for imbalances or patterns that could cause bias later. When we fine-tune models, we sometimes adjust the data weights or use special techniques like adversarial debiasing to help the model treat different groups more fairly. We also use explainability tools like SHAP to understand why the model makes certain predictions. After launch, we keep monitoring the model to catch any new biases early.

How does machine learning differ from artificial intelligence?

Machine learning is just one part of AI. ML focuses on learning from data—finding patterns, making predictions. AI, more broadly, includes rule-based logic, NLP, and even robotics. In most business cases today, when people say “AI,” they mean ML.

Will machine learning apply to my industry?

If your business generates data, ML is applicable. From predictive maintenance in manufacturing to risk scoring in finance or personalization in eCommerce, ML translates raw data into models that optimize processes, reduce costs, and improve CX.

Feel free to book a call and get all the answers you need.

FAQ

How much does machine learning app development cost?

Budgets typically fall between $40K–$200K. Costs depend on data preprocessing, model architecture (e.g., regression, CNNs, transformers), infrastructure (cloud/on-prem), and integration scope.

How long does it take to build a machine learning model?

How does Innowise address potential biases in ML models?

How does machine learning differ from artificial intelligence?

Will machine learning apply to my industry?