Utveckling av maskininlärning

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

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

Drowning in messy data with no clear direction?

Let ML turn that chaos into clarity.

Googles logotyp. Hays logotyp. PayPal-logotyp. Siemens logotyp. Nike-logotyp. Volkswagen-logotyp. LVMH:s logotyp. Nestle-logotyp. Novartis logotyp. Spotify-logotyp.
Googles logotyp. Hays logotyp. PayPal-logotyp. Siemens logotyp. Nike-logotyp. Volkswagen-logotyp. LVMH:s logotyp. Nestle-logotyp. Novartis logotyp. Spotify-logotyp.
Aramcos logotyp Mercedes logotyp. Costco Wholesale logotyp. Logotyp för skal. Accentures logotyp. NVIDIA-logotyp. SPAR-logotypen. Mastercard-logotyp. CVS Healths logotyp. Walt Disney-logotypen.
Aramcos logotyp Mercedes logotyp. Costco Wholesale logotyp. Logotyp för skal. Accentures logotyp. NVIDIA-logotyp. SPAR-logotypen. Mastercard-logotyp. CVS Healths logotyp. Walt Disney-logotypen.
Googles logotyp.Hays logotyp.PayPal-logotyp.Siemens logotyp.Nike-logotyp.Volkswagen-logotyp.LVMH:s logotyp.
Googles logotyp.Hays logotyp.PayPal-logotyp.Siemens logotyp.Nike-logotyp.Volkswagen-logotyp.LVMH:s logotyp.
Nestle-logotyp.Novartis logotyp.Spotify-logotyp.Aramcos logotyp.Mercedes logotyp.Costco Wholesale logotyp.
Nestle-logotyp.Novartis logotyp.Spotify-logotyp.Aramcos logotyp.Mercedes logotyp.Costco Wholesale logotyp.
Logotyp för skal.Accentures logotyp.NVIDIA-logotyp. SPAR-logotypen.Mastercard-logotyp.CVS Healths logotyp.Walt Disney-logotypen.
Logotyp för skal.Accentures logotyp.NVIDIA-logotyp. SPAR-logotypen.Mastercard-logotyp.CVS Healths logotyp.Walt Disney-logotypen.

Maskininlärningslösningar vi bygger

Förebyggande underhåll
Bedrägeribekämpning
Prognostisering
Dynamisk prissättning
Virtual assistants & real-time chatbots
Marketing automation solutions
Analys av kundernas beteende
Document, image & video processing
Smarta rekommendationssystem
Visa alla Visa mindre
Philip Tihonovich
Chef för Big Data-avdelningen

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 för Big Data-avdelningen

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.

Analys av krav

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.

Funktionsgenerering

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.

Utveckling av modeller

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

Modell distribution

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.

Modell stämning

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

Lämna dina ML-algoritmer till proffsen

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.

Plattformar som vi arbetar med

AWS maskininlärning
  • Vertex AI
  • Google AI för konversation
  • Google AI för dokument
  • Google AI för branscher
Azure maskininlärning
  • Azure Cognitive Services
  • Azure Machine Learning
  • Azure Bot Services
  • Azure Applied AI Services
Google maskininlärning
  • Amazon SageMaker
  • Amazon Transcribe & Polly
  • Amazon Comprehend
  • Amazon Rekognition

Välj din prismodell

Fast pris

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.

Tid & material med lock

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.

Vad våra kunder tycker

Tim Benedict CTO Vitreus
företagets logotyp

"Innowise har framgångsrikt levererat kundens MVP, vilket markerar projektets framgång. Teamet har erbjudit utmärkt projektledning, eftersom de är mycket effektiva och alltid levererar i tid. Sammantaget är deras passion och djupa expertis enastående."

  • Industri Företagstjänster
  • Teamstorlek 30 specialister
  • Varaktighet 15 månader
  • Tjänster Arkitektonisk design, blockchain, anpassad utveckling
Ory Goldberg VD Traxi
företagets logotyp

"Jag är mycket nöjd med deras högkvalitativa arbete och förmåga att leverera exakt vad jag vill ha genom ett mycket professionellt tillvägagångssätt. Deras flexibla och tillgängliga process är nyckeln till det pågående projektets framgång."

  • Industri Programvara
  • Teamstorlek 10 specialister
  • Varaktighet 24+ månader
  • Tjänster Mobil utveckling, webbutveckling
Davide Criscione Grundare och vd DC Services GmbH
företagets logotyp

"Innowise har hittat högkvalitativa resurser som passar väl in i deras tilldelade interna team. De hade resurserna redo att starta på kort tid. Teamet erbjuder lyhörd och personlig projektledning. Dessutom är de proaktiva och lovar inte för mycket."

  • Industri IT-tjänster
  • Teamstorlek 12 specialister
  • Varaktighet 15+ månader
  • Tjänster Förstärkning av personalen

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.

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.

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.

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.

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.

Boka gärna ett samtal och få alla svar du behöver.

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.

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.

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.

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.

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.

Boka gärna ett samtal och få alla svar du behöver.

Спасибо!

Cообщение отправлено.
Мы обработаем ваш запрос и свяжемся с вами в кратчайшие сроки.

Tack!

Ditt meddelande har skickats.
Vi behandlar din begäran och kontaktar dig så snart som möjligt.

Tack!

Ditt meddelande har skickats. 

Vi behandlar din begäran och återkommer till dig så snart som möjligt.

pil