Machine learning consulting
Building ML models is one thing — making them work at scale is another. Messy data pipelines, slow deployment, and unpredictable performance can turn machine learning operations into a bottleneck instead of a business driver.
Our consulting cuts through complexity, focusing on strategy, infrastructure, and seamless integration — all with engineering peace of mind at the core so your AI delivers real value, every time.
Fundamental needs we address with our machine learning consulting services
Bridging the gap between ML strategy and implementation
Struggling with ML adoption roadblocks, whether it’s a lack of in-house expertise, time constraints, or the high cost of trial and error? We guide you every step of the way, turning strategic plans into tangible results.
Integrating ML-driven features into existing software
We understand how much user satisfaction means to you. No matter it’s a software product or an internal app, we ensure its users experience no disruptions to their routines and benefit from great new features, such as predictive analytics, recommendation engines, and automation tools.
What’s more, our machine learning consultants help resolve challenges related to data quality and integration with legacy systems.
Improving machine learning operations
Need better accuracy, scalability, or cost efficiency? We fine-tune your models, optimize infrastructure, and ensure your ML systems scale with your business, delivering real, measurable improvements.
Let Vention be your ML powerhouse. With 100+ AI experts on board, we’re ready to provide professional guidance and develop or optimize ML models. And we need just two weeks to kick off.
Our machine learning consulting services
Here’s how our ML experts turn ambitious AI visions into practical, high-performing solutions:
Machine learning strategy and technology consulting
-
Match your — or your clients’ — business goals with ML opportunities;
-
Validate ML feasibility (its technical, economic, and operational aspects) for a software product or enterprise business case;
-
Guide you through the maze of machine learning technology stack (frameworks, tools, and platforms) to select the best-fitting options that align with long-term goals;
-
Audit data sources and recommend steps to improve the quality of data sets or handle bias or data scarcity;
-
Help make an informed “build a custom model vs. use a pre-built one” decision;
-
Suggest the deployment option — on-premises, cloud, or hybrid — to meet security and performance requirements.
Machine learning development consulting
-
Develop proof of concept (PoC) or a minimum viable product (MVP) for an ML initiative;
-
Prepare data, be it data cleaning, labeling, or augmentation;
-
Engineer features to ensure the model’s high performance;
-
Select the best-fitting ML algorithms or architecture;
-
Implement retrieval augmented generation (RAG);
-
Reinforcement learning consulting to train the model based on rewards or penalties it gets from the environment;
-
Automate model training and deployment with CI/CD pipelines;
-
Develop a custom machine learning model tailored to business needs;
-
Move ML models from research to production-ready deployment.
Machine learning operations consulting
-
Set up real-time performance tracking tools with automated alerts;
-
Detect and mitigate model drift, bias, and concept shift over time;
-
Implement MLOps for seamless model maintenance;
-
Troubleshoot and improve underperforming ML models;
-
Audit and refine existing ML models and ML-based enterprise applications and software products;
-
Optimize and scale infrastructure for performance and efficiency;
-
Adopt AI-driven automation to improve efficiency and reduce costs.
Machine learning security consulting
-
Implement robust security controls, e.g., role-based access and data encryption;
-
Set up monitoring and logging tools to track the model’s behavior and recognize suspicious activity, like unusual query patterns and adversarial attacks;
-
Perform security testing to reveal vulnerabilities like data poisoning or model inversion;
-
Deploy models in secure containers to minimize their exposure to cyber threats.
Any machine learning type at your service
At Vention, we’re proficient in all three machine learning types: supervised, unsupervised, and deep learning. By blending the best of these approaches, we help you gain a competitive edge, spark innovation, and drive your business forward.
Supervised learning
Essence: An approach when an ML model is trained on a labeled training data set to learn to make predictions on new data.
Example: We use historical data points marked as “fraud” and “legitimate” to teach the model to recognize fraudulent behavior.
Supervised learning techniques we specialize in:
-
Linear regression
-
Logistic regression
-
Decision tree
-
Random forest
-
Gradient boosting
-
Support vector machine
-
ARIMA
-
SARIMAX
-
Naïve Bayes
-
K-nearest neighbors
-
Neural network models
-
Ensemble learning
Unsupervised learning
Essence: An approach when an ML model finds hidden patterns in unlabeled data.
Example: We use historical data points to help the model identify unusual user behavior or transaction patterns that can signify fraud.
Unsupervised learning techniques we specialize in:
-
K-means clustering
-
Gaussian mixture
-
Hierarchical clustering
-
Principal component analysis
-
Mean shift
-
Singular vector decomposition
-
Collaborative filtering
Deep learning
Essence: An approach reliant on multi-layered neural networks for complex pattern recognition. It’s usually used for solving natural language processing and computer vision tasks.
Example: We can identify complex transaction fraud patterns and analyze sequences to uncover hidden trends in time-series data.
Deep learning techniques we specialize in:
-
Convolutional neural networks
-
Recurrent neural networks
-
Encoder-decoder architectures and transformers
-
Common architectures (ResNet, U-Net, YOLO, Mask-RCNN, MTCNN, BERT)
-
Autoencoders
-
Generative adversarial networks
Already envisioning how ML can transform your operations but unsure where to start?
Let’s chart the right course together.
Our step-by-step approach to machine learning development consulting
Our machine learning consulting and development process is a well-structured journey from project assessment to model development, seamless integration, and ongoing support. This approach ensures that your machine learning initiatives are successful at launch and continue to evolve and deliver value as your business grows and changes.
Discovery
Before diving into machine learning development, our ML consultants partner with your organization to understand your specific objectives, existing data sources, and business constraints. We assess the quality and availability of data, identifying any gaps that need to be filled. This stage also involves defining success metrics and setting realistic project goals.
By the end of the discovery phase, we provide you with a clear project plan, including timelines and resource requirements, ensuring that all stakeholders have a shared understanding of the project's scope and expected outcomes.
Modeling
Our machine learning engineers and data scientists design and build machine learning models tailored to your business needs. This involves data mining (if needed) and preprocessing, feature engineering, and selecting the most suitable machine learning algorithms for the task at hand. We then train and fine-tune the models using historical data, incrementally evolving the accuracy and performance of the solution.
Model selection depends on the specific problem: classification, regression, recommendation, or any other task. Based on this, we implement robust validation techniques to ensure the models generalize well to new data. The modeling phase is characterized by rigorous testing and validation, resulting in models that are ready for deployment.
Integration
Once the machine learning models have been validated, the integration phase focuses on seamlessly incorporating them into your existing systems and workflows. Our machine learning engineers ensure that the models are production-ready, optimizing their performance and scalability. Depending on your machine learning project requirements, we design APIs and interfaces for easy integration with your software applications, databases, or IoT devices. Real-time or batch processing capabilities can also be implemented to suit your operational needs.
The integration process includes extensive testing in a production-like environment to identify and resolve any issues before deployment. We aim to ensure that machine learning solutions become integral to your business processes, delivering actionable insights and automation where needed.
Support
Our commitment to your success continues with ongoing support and maintenance even after deployment. Upon your request, we initiate the support phase, which encompasses monitoring the performance of deployed models, identifying and addressing any drift or degradation in model accuracy, and fine-tuning as needed. We also provide comprehensive documentation and training for your teams to effectively utilize and maintain your new machine learning solutions.
Our support services extend to troubleshooting, debugging, and addressing any unforeseen challenges during the operational phase. Regular updates and enhancements are part of our support strategy to ensure that your machine-learning solutions remain ahead of the curve and aligned with your evolving business goals.
We work together, your way: Choose the model that fits your goals
An approach where an external ML team handles the entire project, from strategy planning to model deployment.
Best for: Companies without in-house ML expertise or those seeking a turnkey solution with minimal involvement from their internal IT team.
A partnership where an external team exclusively works on your ML initiatives, acting as an extension of your company.
Best for: Businesses that require ongoing ML development and continuous improvements.
A flexible model where ML engineers, MLOps specialists, or other roles are added to your existing team to fill skill gaps.
Best for: Companies with an established ML strategy that need specialized expertise or additional resources to accelerate development.
Need a tech partner with deep domain knowledge? You’ve found it
With hands-on experience across 30+ industries, we know firsthand how machine learning drives transformation. Smarter decisions, streamlined operations, and significant cost savings — ML delivers tangible results, and we make it happen.
Here are just a few ways we apply our expertise:
Machine learning tools we specialize in
ML solutions go beyond algorithms — they thrive in the right ecosystem. Successful implementation depends on a well-curated mix of ML frameworks, cloud infrastructure, and deployment tools, ensuring efficiency and scalability.
ML and AI frameworks
TensorFlow
scikit-learn
XGBoost
PyTorch
Keras
LightGBM
Programming languages
Python
R
C++
Natural language processing
NLTK
Transformers (by Hugging Face)
Large language models (LLMs)
spaCy
Gensim
Computer vision
OpenCV
Detectron2
YOLO
Mask R-CNN
Generative AI technologies
OpenAI GPT
DALL-E
Stable Diffusion
Midjourney
Cloud services
Amazon SageMaker
Azure Machine Learning
Google AI Platform
Google Cloud AutoML
Big data
AWS: Amazon EMR, AWS Lambda, Amazon S3, AWS Glue, Amazon Kinesis, Amazon DynamoDB, Amazon Redshift, Amazon QuickSight
Microsoft: Azure HDInsight, Azure Data Lake Storage, Azure Data Factory, Azure Cosmos DB, Azure SQL Database
Google: BigQuery, Dataproc, Dataflow, Cloud Storage
Continuous integration/ continuous delivery (CI/CD)
GitLab CI/CD
GitHub Actions
Travis CI
CircleCI
Terraform
AWS CloudFormation
AWS CodeBuild
AWS CodeDeploy
AWS CodePipeline
Concourse
Jenkins
Containerization tools
Docker
Kubernetes
Amazon ECS
Amazon EKS
Google Cloud Run
Google Kubernetes Engine (GKE)
Why Vention?
A proven track record
-
20+ years of experience in custom software development
-
500+ award-winning clients
Continuously recognized for impact
-
Four-time honoree on the Global Outsourcing 100 list by the International Association of Outsourcing Professionals
-
Five-time honoree among the Americas’ fastest-growing companies, according to the Financial Times
-
Six-time honoree among America’s fastest-growing private companies, according to Inc. 5000
Top-tier talent
-
100+ AI experts on tap
-
71% of software developers are senior-level and team leads
Operational excellence
-
CVs within 48 hours
-
2 weeks from contact to kickoff
-
Zero operational overhead
-
$600K average client savings per year
Unparalleled data security and management
ISO 27001-certified security management system.
Our clients
What our clients say
Every business takes a different path, but with each project, our goal remains the same: to turn ML potential into decisions that drive ROI, enhance operational agility, and elevate workforce capabilities. We've partnered with 500+ enterprises, SMBs, and startups, so every challenge refines our expertise and powers the next generation of tech leaders.
Paul Steckler
Founder & Senior Partner, Ramp Catalyst
“They have done multiple projects around AI, ML and VR spaces. We worked on leading-edge voice agent technology. They recently built an AI agent with Ph.D.-level research and development skills; the result was a breakthrough for that industry.”
Vadim Berman
CEO, Tisane Labs
“We develop and distribute artificial intelligence (AI) software to extract actionable intelligence for brands, and to detect abuse on the internet. Despite our very niche and specialized application domain, the developer assigned to us has been doing a great job understanding our needs and developing a quality product.”
Christopher Vroom
Founder, CollectorIQ, Inc.
“Vention has played a critical part in the development effort that’s complemented our internal resources. They’ve been involved in both the ideation and development of features and functionalities, which involve aggregating customer information and unique data. With our team, they’ve helped develop algorithms that help predict value for our customers’ assets, while at the same time creating the aggregation technology and machine learning to discern value very quickly.”
Lior Harel
CTO, Staircase AI
“The programmers are a fantastic addition to the group. They were promptly integrated and brought up to speed. They also quickly replace any developer that isn't a good fit. They manage the engagement well through regular meetings and communication. The level of expertise of the developers they let me interview is impressive. And the ones we eventually hired.”
Check out our latest projects
AI-powered app development for healthcare
Our AI developers built a mixed-reality app that transforms CT and MRI scans into interactive 3D models. Medical professionals can zoom, rotate, and explore tissue layers in detail, unlocking deeper anatomical insights.
Ideas spark innovation, but execution drives results. Let’s turn your ML vision into a solution that works seamlessly and at scale.