Machine Learning Consulting

ML models for predictive analytics

Machine learning consulting services supercharge Artificial Intelligence (AI), making this powerful technology accessible for organizations seeking ROI improvements.

Machine Learning (ML) may look different from traditional software development, but it is well within reach for any sized organization. ML models’ performance improves as they are exposed to more data over time. And modern tools now make the experience of building and deploying these predictive models “a snap.”

Our data science and machine learning consulting services help develop and leverage ML tools to improve your bottom line by:

automating org-wide processes
streamlining workflows for efficiency
creating systems to proactively monitor for issues
allowing for data-driven decision-making at scale

Prior investment in data quality or reporting is not required. Since most AI applications are built from raw operational system data, data warehouses are not a crucial source of data.

Our Data science, AI, and machine learning consultants have the business and technical expertise to guide you through solving complex problems using the power of artificial intelligence and advanced data analytics.

Our Machine Learning Consulting Services

Roadmap & Implementation

Creating a Machine Learning and AI implementation roadmap starts with identifying opportunities for where ML and AI have a high potential for improving ROI.

Our machine learning consultants work with you to define and articulate a modernization roadmap to start your journey the right way.

We’ll build business cases to help you understand how ML & AI can transform specific workflows and processes to create financial and operational lift.

Our business cases are informed by our industry vertical experts and market research, ensuring you will be armed with a financial analysis to make a strong claim for funding and buy-in.

We help you plan a roadmap that introduces AI and ML into your organization.

Topics include funding and anticipated returns, pilot programs, introducing change, establishing an internal competency, governing data, and technical approach.

Rapid Pilot Program

We understand the importance of having your first AI/ML project be successful.

AI continues to be recognized for its ability to drive major financial lift, but you might still have a few skeptics. Through a Centric Rapid Pilot, you will approach AI and ML conservatively, strengthening your case to expand.

We start by workshopping with select executives by identifying opportunities for meaningful process improvements, sourcing data, and clarifying how AI and ML would fit operationally into a future state.

Once we have settled on an AI use case, we conduct a brief analysis of available data to determine if the necessary signals exist for a viable PoV.

If not, you can pivot to a different use case with relatively small investment. If it makes sense to proceed, Centric will build an initial model to prove efficacy and value.

Phase 2 of most pilots will be operationalization accompanied by light process engineering, change management, and monitoring.

Process Improvement & Re-Engineering

AI may be used to implement new business processes, like alerting you to adverse business conditions or proposing optimizations.

Other times, AI and ML augment existing business processes, helping them to become more efficient or effective.

Our Data science, AI, and machine learning consultants bring all the right ingredients.

During a technical implementation, our technical teams bring expertise in AI and machine learning, robotic process automation (RPA), business process management (BPM) and analytics.

Just as important is the people side of process change. We will document and streamline processes, communicate the upcoming changes, and apply a robust change management strategy.

With Centric as your guide, your people will embrace the change as a valuable improvement.

Machine learning consultants help you turn your data into action for:

Preventing Adverse Events

Many avoidable outcomes could be prevented if someone was watching. Adverse events may be rare, but when they occur, the human and financial impacts can be devastating.

AI can be your watcher. It has the power to continuously monitor data to find anomalies. Applications include watching for fraudulent activity, defects and quality issues, and safety risks.

Even better, using machine learning, AI has the power to learn which complex data patterns suggest an impending problem. This capability often makes AI/ML a better watcher than any human.

Improving Customer Experience

Creating an exceptional customer experience is foundational for every business. A customer’s experience is shaped by your responsiveness, personalization, watching out for the customer’s best interests and ease of interaction.

To complicate matters, there is always a trade-off between customer service and operating costs. These decisions are usually made with the best information available.

AI and ML can optimize your customer experience and operating profit at the same time. This could be as simple as making predictions about customer attrition so that you can take corrective action.

Reducing Manual Processing

Core operations often hold on to manual processes the longest due to specializations and years of expertise. It can seem that there’s no practical way to augment or replace manual processes due to their apparent complexity.

However, labor costs from these manual processes may be too high, preventing scaling of the business. With higher throughput often comes higher rates of errors or quality concerns.

Combining Machine Learning with Robotic Process Automation and AI can replace many time-consuming activities. Not only can AI and ML learn from aggregate years’ experience of your existing team, but it often can also make better decisions, faster.

Outpacing the Competition

Companies compete on customer experience, but also pricing and foreseeing market conditions. Those who can most rapidly adapt pricing, production and logistics will have an advantage.

Changing your response with spreadsheets and “instinct” leads to unreliable outcomes. The time required to accumulate the necessary information usually means that response times are too slow to make a difference in the marketplace.

AI and ML allow you to make informed changes based on massive data crunching and confidence intervals. AI can perform the ultimate what-if analysis by plugging in potential business responses and seeing how it is most likely to play out.

Moving Beyond Six-Sigma

Process improvement and re-engineering are traditionally performed by process analysts. They observe, take notes and plug data into spreadsheets to review performance.

Machine learning consultants deeply consider every piece of data to build AI tools that can optimize business processes. Instead of basic charts in Excel, AI can look across multiple dimensions at once for a clear understanding of factors that correlate to the best outcomes.

What if you could predict which customers were likely to go to your competitors? How would you respond to prevent it? AI and ML can give you this sort of hidden insight, presenting new ways to unlock value.

Trying and Failing

Setting up ML for AI can be tricky to get off the ground even in mature organizations. Many companies start by hiring high-priced data scientists who immediately begin sifting through data.

Yet, the concrete business value never seems to materialize. Eventually a wave of skepticism overwhelms the imagined sandcastle of possibilities. We understand the disappointment this creates.

It is important to recognize that AI is a powerful tool in the toolbelt, but does not itself make you more competitive, responsive, intelligent. AI and ML must be paired with a deep understanding of business process change, system integration and operationalization.

Machine Learning Supports Functions Across Industries

Our carefully crafted, value-based machine learning approach is designed to support key business functions and outcomes across various industries.

We specialize in a use-case based methodology that minimizes delivery risk, drives speed to value, and nurtures long-term strategic relations with our clients.

The goal is to minimize efforts associated with attaining desired maturity, bypassing organic growth curves, and delivering business value drops in weeks, rather than months and years.

Machine Learning Use Cases

Machine Learning in Finance

Transform your institution’s decision-making with intelligent automation:

Identify fraudulent transactions in real-time using advanced data mining techniques
Predict loan defaults to reduce risk through predictive analytics
Enable algorithmic trading that responds to market changes instantly
Drive operational efficiency while improving customer experience through personalized services and faster loan approvals

Machine Learning in Insurance

Revolutionize underwriting and claims processing with intelligent risk assessment:

Analyze vast datasets to price policies more accurately using data mining
Detect fraudulent claims in real-time with pattern recognition algorithms
Automate routine claims processing with computer vision to accelerate payouts
Enhance profitability through precise risk modeling while delivering faster, more transparent service that builds customer trust

Machine Learning in Healthcare

Accelerate patient outcomes and operational efficiency through data-driven insights:

Assist physicians with faster, more accurate diagnoses
Predict patient deterioration to prevent complications through continuous monitoring
Optimize staff scheduling to reduce costs with intelligent workforce planning
Improve care quality while streamlining operations and enhancing patient satisfaction

Machine Learning in Manufacturing

Optimize production and eliminate costly downtime with intelligent manufacturing systems:

Predict equipment failures before they occur using sensor data mining
Automatically adjust production parameters for quality control with computer vision inspection
Optimize supply chain logistics through predictive demand forecasting
Minimize unplanned downtime while maximizing equipment effectiveness and maintaining consistent product quality

Machine Learning in Customer Service

Deliver exceptional customer experiences while reducing operational overhead:

Power intelligent chatbots with natural language processing (NLP) to handle routine inquiries 24/7
Predict customer needs to enable proactive support
Analyze conversation patterns with NLP to identify service improvement opportunities
Transform customer interactions into competitive advantages while freeing your team to focus on complex, high-value relationships

Let’s Collaborate with Us!

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Edmonton, AB T6J 4T3, Canada

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Our Machine Learning FAQs

What types of machine learning problems do you typically solve for businesses?

We help businesses create business cases and roadmaps for artificial intelligence (AI) and machine learning (ML) that will identify opportunities that have a high potential for ROI. We can also help you develop a rapid pilot so you can quickly test an ML application. Lastly, we can help organizations improve existing processes and establish new ones for working with their new ML or AI applications.

How do you approach integrating machine learning solutions into existing business processes?

We start by leading your organization in a discovery process to identify current use cases. Before, during and after the technical implementation, we document current processes and evaluate how to streamline them based on how the machine learning solution will work with your team, as well as communicate the upcoming changes while establishing a robust change management strategy.

What kind of data is required to start a machine learning project with your consulting services?

You don’t necessarily need to have prior investment in data quality or reporting to get started on a machine learning project. We can work with you to build a custom AI or ML application using raw operational system data, so you don’t always need a data warehouse to get started, either. That said, our data consultants can work with you to address your data modernization, governance, strategy needs to fully support your evolving business.

Can you provide examples of successful machine learning implementations you have delivered?

In one example, we worked with a clinical terminology company to implement machine learning to help them quickly create and maintain medical description consistency. The organization is dedicated to helping healthcare professionals establish a shared language so that when, for example, a patient receives a prescription or recommendation, the doctor, nurse and pharmacist all have the same understanding of the prescription. To keep up with the millions of nuanced descriptions, the company turned to us to develop a natural language processing and ML solution. We helped them improve their experts’ capacity by developing a recommendation tool that allowed the client to map 62 percent of new descriptions to a recommendation list where the correct procedure was in the top ten list about three-quarters of the time.

What is your process for developing a business case and roadmap for machine learning projects?

We work with you to define and develop a roadmap for AI and ML based on projects that will have a high potential for ROI. We’ll also establish business cases based on our market research and Industry Vertical experts, so you know you have the financial analysis to create a strong claim for buy-in and funding.

How do you handle change management and training for employees adopting new AI/ML solutions?

We consider change management critical for implementing new processes into an organization. We’ll document and streamline new processes while communicating the upcoming changes to employees and developing a robust Change Management strategy.

How does BB Atlantic ensure the success of its AI projects?

Our team ensures the success of AI projects by following a structured project management process, engaging with cross-functional expertise throughout our firm, using proven methodologies and tools, and maintaining a close collaboration with the client throughout the project. We measure the performance of AI solutions against predefined KPIs to ensure they deliver the expected results and take an iterative, continuous improvement approach to the solutions we implement.

What kind of support does BB Atlantic provide after the implementation of an AI solution?

Our AI consulting team provides comprehensive support during and after AI development and implementation. This includes monitoring the performance of the solution, providing regular maintenance, updates and improvements, and offering training and support to your team. We also provide workforce strategy, adoption and change management services to ensure the long-term success of your organization’s AI journey.

What is the AI market size expected to be by 2030?

The AI market is huge and rapidly growing in revenue, tools, and services. By the end of 2024 we expect there to be 25,000 new AI tools and services and revenue to grow from $89 billion to $190 billion. By 2030 we’re expecting this market to be $1.5 to $2 trillion in size.

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