Développement de l'apprentissage automatique

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

Intelligence artificielle

Développement de réseaux neuronaux

Apprentissage profond

Big data & predictive analytics

Computer vision

Reconnaissance vocale

Analyse des sentiments

Traitement du langage naturel

Automatisation des processus robotiques (RPA)

Intelligence artificielle

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.

Développement de réseaux neuronaux

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.

Apprentissage profond

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.

Reconnaissance vocale

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

Analyse des sentiments

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.

Traitement du langage naturel

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.

Automatisation des processus robotiques (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.

Intelligence artificielle

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.

Développement de réseaux neuronaux

Apprentissage profond

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.

Reconnaissance vocale

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

Analyse des sentiments

Traitement du langage naturel

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.

Automatisation des processus robotiques (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

Finances
Soins de santé
Retail & E-Commerce
Fabrication
Énergie et services publics
Télécommunications

Finances

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
Détection de la fraude en temps réel
Intelligent market forecasting

Soins de santé

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

Commerce de détail & Commerce électronique

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

Fabrication

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

Énergie et services publics

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

Télécommunications

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

Solutions d'apprentissage automatique que nous créons

Maintenance prédictive

Détection des fraudes

Prévision de la demande

Prix dynamique

Virtual assistants & real-time chatbots

Marketing automation solutions

Analyse du comportement des clients

Document, image & video processing

Systèmes de recommandation intelligents

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Philip Tihonovich

Chef du département Big Data

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

Chef du département Big Data

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.

Analyse des besoins

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 ingénierie

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.

Développement de modèles

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

Déploiement du modèle

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.

Tuning de modèle

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

Faites entretenir vos algorithmes ML par des professionnels

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.

Plateformes avec lesquelles nous travaillons

Vertex AI
Google Conversational AI

Google AI pour les documents
Google AI pour les industries

Azure Cognitive Services
Azure Machine Learning

Azure Bot Services
Services Azure Applied AI

Amazon SageMaker
Amazon Transcribe & Polly

Amazon Comprehend
Amazon Rekognition

Choisissez votre modèle de tarification

Prix fixe

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.

Temps et matériel avec un plafond

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.

Les avis de nos clients

Tim Benedict DIRECTEUR TECHNIQUE Vitreus

"Innowise a livré avec succès le MVP du client, marquant ainsi la réussite du projet. L'équipe a offert une excellente gestion de projet, car elle est très efficace et respecte toujours les délais. Dans l'ensemble, leur passion et la profondeur de leur expertise sont remarquables."

Industrie Services aux entreprises
Effectif de l'équipe 30 spécialistes
Durée 15 mois
Services Conception architecturale, blockchain, développement personnalisé

Ory Goldberg PDG Traxi

"Je suis très satisfait de la qualité de leur travail et de leur capacité à fournir exactement ce que je souhaite grâce à une approche très professionnelle. Leur flexibilité et leur disponibilité sont des éléments clés de la réussite du projet en cours."

Industrie Logiciel
Effectif de l'équipe 10 spécialistes
Durée 24+ mois
Services Développement mobile, développement web

Davide Criscione Fondateur et PDG DC Services GmbH

"Innowise a trouvé des ressources de haute qualité qui s'intègrent bien dans les équipes internes qui leur sont affectées. Les ressources étaient prêtes à démarrer dans un court délai. L'équipe offre une gestion de projet réactive et personnalisée. De plus, ils sont proactifs et ne font pas de promesses excessives."

Industrie Services informatiques
Effectif de l'équipe 12 spécialistes
Durée 15+ mois
Services Augmentation du personnel

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.

En quoi l'apprentissage automatique diffère-t-il de l'intelligence artificielle?

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.

L'apprentissage automatique s'appliquera-t-il à mon secteur d'activité?

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.

N'hésitez pas à prendre rendez-vous pour obtenir toutes les réponses dont vous avez besoin.

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?

En quoi l'apprentissage automatique diffère-t-il de l'intelligence artificielle?

L'apprentissage automatique s'appliquera-t-il à mon secteur d'activité?