Utvikling av maskinlæring

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.

Google-logo. Hays logo. PayPal-logo. Siemens-logo. Nike-logo. Volkswagen-logo. LVMH-logo. Nestle-logo. Novartis logo. Spotify-logo.
Google-logo. Hays logo. PayPal-logo. Siemens-logo. Nike-logo. Volkswagen-logo. LVMH-logo. Nestle-logo. Novartis logo. Spotify-logo.
Aramco-logo Mercedes-logo. Costco Wholesale-logo. Skall-logo. Accenture-logo. NVIDIA-logo. SPAR-logo. Mastercard-logo. CVS Health-logo. Walt Disney-logoen.
Aramco-logo Mercedes-logo. Costco Wholesale-logo. Skall-logo. Accenture-logo. NVIDIA-logo. SPAR-logo. Mastercard-logo. CVS Health-logo. Walt Disney-logoen.
Google-logo.Hays logo.PayPal-logo.Siemens-logo.Nike-logo.Volkswagen-logo.LVMH-logo.
Google-logo.Hays logo.PayPal-logo.Siemens-logo.Nike-logo.Volkswagen-logo.LVMH-logo.
Nestle-logo.Novartis logo.Spotify-logo.Aramco-logo.Mercedes-logo.Costco Wholesale-logo.
Nestle-logo.Novartis logo.Spotify-logo.Aramco-logo.Mercedes-logo.Costco Wholesale-logo.
Skall-logo.Accenture-logo.NVIDIA-logo. SPAR-logo.Mastercard-logo.CVS Health-logo.Walt Disney-logoen.
Skall-logo.Accenture-logo.NVIDIA-logo. SPAR-logo.Mastercard-logo.CVS Health-logo.Walt Disney-logoen.

Maskinlæringsløsninger vi bygger

Forutseende vedlikehold
Påvisning av svindel
Etterspørselsprognoser
Dynamisk prising
Virtual assistants & real-time chatbots
Marketing automation solutions
Analyse av kundeatferd
Document, image & video processing
Smarte anbefalingssystemer
Vis alle Vis mindre
Philip Tihonovich
Leder for avdelingen for stordata

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
Leder for avdelingen for stordata

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.

Behovsanalyse

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.

Funksjonsteknikk

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.

Utvikling av modeller

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

Implementering av modellen

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.

Modellinnstilling

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

Få dine ML-algoritmer vedlikeholdt av fagfolk

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.

Plattformer vi samarbeider med

AWS maskinlæring
  • Vertex AI
  • Google Conversational AI
  • Google AI for dokumenter
  • Google AI for industrier
Azure maskinlæring
  • Azure kognitive tjenester
  • Azure maskinlæring
  • Azure Bot-tjenester
  • Azure-tjenester for anvendt kunstig intelligens
Googles maskinlæring
  • Amazon SageMaker
  • Amazon Transcribe & Polly
  • Amazon Comprehend
  • Amazon Rekognition

Velg 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 og materialer med tak

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.

Hva kundene våre mener

Tim Benedict CTO Vitreus
selskapets logo

"Innowise har levert kundens MVP, noe som markerer prosjektets suksess. Teamet har tilbudt utmerket prosjektledelse, ettersom de er svært effektive og alltid leverer i tide. Alt i alt er lidenskapen og den dype ekspertisen deres enestående."

  • Industri Forretningstjenester
  • Lagets størrelse 30 spesialister
  • Varighet 15 måneder
  • Tjenester Arkitekturdesign, blokkjede, tilpasset utvikling
Ory Goldberg CEO Traxi
selskapets logo

"Jeg er veldig fornøyd med den høye kvaliteten på arbeidet deres og deres evne til å levere akkurat det jeg ønsker gjennom en svært profesjonell tilnærming. Deres fleksible og tilgjengelige prosess er nøkkelen til prosjektets suksess."

  • Industri Programvare
  • Lagets størrelse 10 spesialister
  • Varighet 24+ måneder
  • Tjenester Mobilutvikling, webutvikling
Davide Criscione Grunnlegger og administrerende direktør DC Services GmbH
selskapets logo

"Innowise har funnet ressurser av høy kvalitet som passer godt inn i de interne teamene de har fått tildelt. De hadde ressursene klare til å starte i løpet av kort tid. Teamet tilbyr responsiv og personlig prosjektledelse. Dessuten er de proaktive og lover ikke for mye."

  • Industri IT-tjenester
  • Lagets størrelse 12 spesialister
  • Varighet 15+ måneder
  • Tjenester Forsterkning av personalet

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.

Bestill gjerne en samtale og få alle svarene du trenger.

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.

Bestill gjerne en samtale og få alle svarene du trenger.

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