Entwicklung von maschinellem Lernen

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

Künstliche Intelligenz

Entwicklung neuronaler Netze

Deep Learning

Big data & predictive analytics

Computer Vision

Spracherkennung

Sentimentanalyse

Verarbeitung natürlicher Sprache

Robotergestützte Prozessautomatisierung (RPA)

Künstliche Intelligenz

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.

Entwicklung neuronaler Netze

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.

Spracherkennung

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

Sentimentanalyse

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.

Verarbeitung natürlicher Sprache

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.

Robotergestützte Prozessautomatisierung (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.

Künstliche Intelligenz

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.

Entwicklung neuronaler Netze

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.

Spracherkennung

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

Sentimentanalyse

Verarbeitung natürlicher Sprache

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.

Robotergestützte Prozessautomatisierung (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

Finanzwesen
Gesundheitswesen
Retail & E-Commerce
Fertigung
Energie & Versorgung
Telekommunikation

Finanzwesen

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
Vorschriften Betrugserkennung in Echtzeit
Intelligent market forecasting

Gesundheitswesen

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

Einzelhandel & 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

Fertigung

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
Höhere Produktqualität
Faster, more efficient production cycles

Energie & Versorgung

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

Telekommunikation

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

Unsere Machine Learning-Lösungen

Prädiktive Wartung

Betrugserkennung

Bedarfsprognose

Dynamische Preisgestaltung

Virtual assistants & real-time chatbots

Marketing automation solutions

Auswertung des Verhaltens der Kunden

Document, image & video processing

Intelligente Empfehlungssysteme

Alles anzeigen Weniger anzeigen

Philip Tihonovich

Leiter der Big Data-Abteilung

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

Leiter der Big Data-Abteilung

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.

Anforderungsanalyse

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.

Modellentwicklung

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

Modell-Einsatz

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.

Optimierung des Modells

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

Überlassen Sie Ihre ML-Algorithmen den Profis

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.

Verwendete Plattformen

Vertex AI
Google Konversations-KI

Google AI für Dokumente
Google AI für Branchen

Azure Kognitive Dienste
Azure Machine Learning

Azure Bot-Dienste
Azure Angewandte KI-Dienste

Amazon SageMaker
Amazon Transcribe & Polly

Amazon Comprehend
Amazon Rekognition

Wählen Sie Ihr Preismodell

Festpreis

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.

Zeit und Material

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.

Was unsere Kunden sagen

Tim Benedict CTO Vitreus

"Innowise implementierte problemlos ein MVP, was den Erfolg des Projekts kennzeichnete. Das Team hat ein hervorragendes Projektmanagement mit Hocheffizienz und pünktlicher Arbeit gewährleistet. Insgesamt sind ihre Leidenschaft und ihr umfassendes Fachwissen herausragend."

Branche Geschäftsservices
Teamgröße 30 Spezialisten
Dauer 15 Monate
Services Architekturdesign, Blockchain, kundenspezifische Entwicklung

Ory Goldberg CEO Traxi

"Ich bin sehr zufrieden mit ihrer hochwertigen Arbeit und ihrer Fähigkeit, durch einen sehr professionellen Ansatz genau das zu liefern, was ich will. Ihr flexibler und verfügbarer Prozess ist der Schlüssel zum Erfolg des laufenden Projekts."

Branche Software
Teamgröße 10 Spezialisten
Dauer 24+ Monate
Services Mobile Entwicklung, Webentwicklung

Davide Criscione Gründer & CEO DC Services GmbH

"Innowise hat hochwertige Ressourcen gefunden, die gut in die ihnen zugewiesenen internen Teams passen. Sie hatten die Ressourcen innerhalb kurzer Zeit startbereit. Das Team bietet ein reaktionsschnelles und sympathisches Projektmanagement. Darüber hinaus sind sie proaktiv und versprechen nicht zu viel."

Branche IT Services
Teamgröße 12 Spezialisten
Dauer 15+ Monate
Services Personalaufstockung

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.

Wodurch unterscheidet sich maschinelles Lernen von künstlicher Intelligenz?

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.

Wird maschinelles Lernen auch für meine Branche wichtig?

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.

Vereinbaren Sie einen Anruf und erhalten Sie alle Antworten.

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?

Wodurch unterscheidet sich maschinelles Lernen von künstlicher Intelligenz?

Wird maschinelles Lernen auch für meine Branche wichtig?