Artificial Intelligence Consulting Services

An experienced AI consulting partner, Winklix designs state-of-the-art solutions fully tailored to our clients' unique needs and figures out the ways to speed up AI development, ensure optimal project cost, and minimized risks.

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APPLICATION SERVICES

Why Choose Winklix

Winklix is proud to be recognized as a 3-Year Champion in The Americas’ Fastest-Growing Companies Rating by the Financial Times.
10+ years in IT business.
10+ years in CRM services.
200+ professionals on board.
Expertise across industries such as manufacturing, retail, professional services, healthcare, banking, telecommunications, and more.

Our Other Expertise in Salesforce Clouds

Provide a personalized Salesforce experience that seamlessly aligns with your organization's goals and objectives.

Sales Cloud

Service Cloud

Marketing Cloud

Community Cloud

Financial Services Cloud

NonProfit Cloud

Salesforce CPQ

Salesforce Commerce Cloud

Salesforce Mulesoft

Salesforce Lightning

Salesforce Einstein Analytics

Health Cloud

Our Capabilities

Codezix’s Salesforce team is ready to support you in implementing:

Chatbots

Industry-specific virtual assistants

Conversational AI

Text-to-speech and speech-to-text

Speech recognition

Generative AI

Business automation

Predictive analytics engines

AIOps solutions

AIoT solutions

Copilots

Autonomous vehicles

Image analysis systems

Computer vision systems

Fraud detection

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End-to-End AI Consulting Services by Winklix

The scope of Winklix artificial intelligence consulting services varies depending on our clients’ business needs, maturity of the data management practices, and the current AI environment. The AI development steps may include:

Business analysis

For businesses: define and analyze the specific needs that can be addressed with an AI solution; assess the current AI landscape (if any) within the company, evaluate established data management practices, and review the technologies and tools currently in use.
For software product companies: develop a competitive advantage framework, including defining the target audience (TA) and identifying key features that will help outperform the competition.

AI solution conceptualization and development project planning

Designing the architecture and feature set for the AI solution while selecting the optimal tech stack for its implementation.
AI project planning: outlining deliverables and KPIs, estimating costs and timelines, and developing a risk management strategy.
Defining the approach for AI models: deciding whether to develop proprietary models or utilize publicly available services and open-source models.
Designing an intuitive and user-friendly UX/UI.
Delivering the AI solution Proof of Concept (PoC), if applicable.

Data preparation management (for proprietary models)

Conducting exploratory analysis of existing data sources (data types, volume, etc.).
Gathering and cleansing data (standardizing, addressing missing or inconsistent variables, anonymizing sensitive information) for machine learning model training.
Splitting data into training, validation, and testing sets.

AI solution development

For proprietary models: refine, test, evaluate, and deploy machine learning models.
For open-source models: integrate ML models/services and perform additional training if necessary.
Developing the non-AI components, including implementing DevOps and coding the server-side infrastructure.

AI solution quality assurance

Continuous testing throughout the development process.
End-to-end AI system testing.
Evaluating the quality of the AI solution's output based on pre-defined KPIs.

AI solution support and optimization

Continuous monitoring and optimization of the AI solution.
Incorporating new data sources to enhance the accuracy and insights of the AI solution.
Developing new machine learning models to address emerging business needs.

AI Service Costs

Pricing models Winklix

Time and Materials

Best for:

Agile development of AI-based solutions.
Continuous consulting during AI implementation.
Iterative AI software evolution, reengineering, bug fixing.

Time and Materials

Best for:

Agile development of AI-based solutions.
Continuous consulting during AI implementation.
Iterative AI software evolution, reengineering, bug fixing.

Time and Materials

Best for:

Agile development of AI-based solutions.
Continuous consulting during AI implementation.
Iterative AI software evolution, reengineering, bug fixing.

Sample cost ranges of AI consulting

$15,000

AI product consulting for startups.

$6,000–$140,000

Consulting on an enterprise AI solution:

Ideation and feasibility study:$6,000–$24,000
Implementation:$18,000– $140,000
Evolution: $24,000/year– $140,000/year

Sample cost ranges for AI development

$30,000–$200,000

Building an AI-based software component (forecasting, optimization, etc.).

~$120,000–$300,000

Developing an AI-powered virtual assistant (chatbot).

~$200,000–$600,000

Creating an AI-enabled automation solution of average complexity.

~$800,000–$1,000,000+

Implementing a large-scale analytics system powered with AI and big data.

AI Technologies we use

Mobile development languages and key toolkits

PROGRAMMING LANGUAGES

COMMUNICATION

AI Service Costs

Pricing models Winklix

Non-neural machine learning

Supervised learning algorithms include decision trees, linear regression, logistic regression, and support vector machines.
Unsupervised learning algorithms encompass techniques like K-means clustering and hierarchical clustering.
Reinforcement learning methods, such as Q-learning, SARSA, and temporal difference methods, are also commonly used.

Neural networks, deep learning

Convolutional and recurrent neural networks, including LSTM and GRU.
Autoencoders, such as VAE, DAE, SAE, and others.
Generative adversarial networks (GANs).
Deep Q-Networks (DQNs).
GFeed-forward neural networks, including Bayesian deep learning techniques.
Modular neural networks.

AI Services

Winklix Approach to Artificial Intelligence Consulting

Data protection

When building AI-powered solutions, we apply the three-pillar approach to effective data security management:

Transparency – personal data collection and processing occur only with user consent.
Robust Security – Winklixintegrates security practices (DevSecOps) into development to ensure a secure environment for data processing and storage.
Compliance – AI-powered solutions are fully compliant with industry standards and legal regulations, including HIPAA, GLBA, GDPR, and others.

Data quality

To ensure high data quality, we work with certified data engineers and data scientists who utilize a variety of tools to automate data validation, cleansing, and deduplication processes.

Guaranteed value of the AI solution

To ensure the viability of your future AI solution, the speed and quality of the AI-enabled insights, we:

Initiate an AI project by creating a proof of concept to demonstrate how the solution will function, estimate its potential value, address concerns, and more.
Achieve a balance between the system’s transparency and output accuracy by combining white-box AI models, which offer clear relationships between variables and predictions, with black-box deep learning models that, by nature, are less explainable.
Evaluate the quality and feasibility of the developed solution based on the established quality KPIs.
Lightning Web Components

Your Benefits from Partnering With Winklix

1.5–2x faster AI development

Thanks to high productivity, a well-established Agile and DevOps culture, and the exceptional technical expertise of our AI consultants and IT professionals.

20–50% reduction in AI project costs

Due to Winklix expert advice on the project cost optimization and pragmatic approach to the tech stack selection.

Choose Your AI Service Option

Winklix, an artificial intelligence consulting company, offers a wide range of services, from AI strategy consulting to complete AI software development.

AI consulting

We develop a customized AI launch strategy, design the ideal architecture and tech stack for your AI solution, and evaluate its economic feasibility. Additionally, we provide expert guidance on AI security and compliance, along with a comprehensive project plan for a smooth, risk-free AI implementation.

PoC delivery

We develop and train small AI software components to demonstrate the technical feasibility of the idea, minimizing the risk of costly changes later. These proof-of-concept modules can be reused during development to accelerate the delivery process.

MVP development

Launching an AI MVP is an efficient way to deploy software quickly and start seeing early returns. We can deliver an MVP of your AI solution in over 3 months, handling the entire process, including app development, AI model design and implementation, as well as all required QA procedures.

AI-based software development

Based on your requirements, we can either integrate AI into your existing app or develop fully-featured AI-powered software from the ground up. Our experienced AI developers are equipped to create industry-specific AI solutions of any type and complexity, ensuring successful deployment at scale.

AI model training

Our data scientists are ready to assist you in training both proprietary and open-source AI models, or retraining your existing models to achieve over 95% accuracy. We will curate a representative training dataset, select the right hyperparameters, and fine-tune the models to avoid underfitting and overfitting.

AI audit and revamp

We offer expert audits of your AI solution to pinpoint the root causes of operational issues and identify practical solutions for improvement. Our team can quickly upgrade the software and enhance AI models, helping you unlock greater value from your existing AI solution.

Technologies and Tools We Use

Apex code
Visualforce
Customer 360 Platform
Lightning Web Components

Site.com
REST/SOAP API
JavaScript frameworks
Salesforce 1

Machine learning libraries

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