Services
Discover the potential of your data with our tailored end-to-end solutions.
At AILO, we turn your data challenges into opportunities, offering technical solutions tailored to the specific needs of your business. From initial exploration to seamless implementation, our end-to-end approach ensures that every step adds value to your development.
The end-to-end approach in a nutshell:
1 Exploration & Ideation
For the curious businesses who are unsure where to start – we kickstart the process by exploring the possibilities of your data based on your individual needs.
We take the time to truly understand your business’ goals and challenges, while also investigating the trends and opportunities related to use of data and AI in your industry. Combining technical expertise with business understanding, we ideate solutions that are both technically sound and strategically focused.
In this process, we dive deep into your data to ensure the defined solutions are feasible and create sustainable value for your business.
2 Development
Once the desired solution is defined, we move on to its technical development, working iteratively and keeping you in the loop at every step.
Using our technical expertise, we design and build all necessary pipelines – from data collection and prototyping to model development and testing. We are flexible with the tools and technologies we use, ensuring that the solution is tailored to your specific requirements and existing systems. For us, the focus is on building a robust and secure architecture, that scales well with future growth.
Throughout this phase, we emphasise transparency and collaboration, providing regular updates and incorporating feedback to ensure the solution evolves in line with your needs.
3 Implementation & Maintenance
In the final phase, we ensure a smooth implementation of the solution, seamlessly integrating it into your workflow and preferred environment.
We stay with you beyond the finish line — this process includes monitoring and maintaining the solution to ensure it keeps running efficiently. Ongoing support is always part of our commitment.
If further development is needed or new inspiration arises, we remain engaged, working in iterative cycles of the end-to-end process to adapt or create new solutions as your business evolves.
Data Engineering
This is where we start – to have a solid foundation. We provide robust data engineering solutions to help you collect, clean, transform, and store data efficiently, ensuring it is reliable and optimised for analytics and machine learning applications.
Examples of data engineering applications:
- Simplify your data systems through data modelling for efficient database design and restructuring legacy systems.
- Streamline data collection and processing with an automated data pipeline.
- Centralize and organize business-critical data in a data warehouse
Use Case
Centralised Data Warehouse
Centralise your fragmented data stored, e.g. in spreadsheets, disconnected systems, or legacy databases, into a structured repository.
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What if all your data—sales, inventory, customer interactions, and financial records—were unified in one place?
Many businesses struggle with fragmented data stored in spreadsheets, disconnected systems, or legacy databases, leading to inconsistencies and slow decision-making. A centralized data warehouse consolidates all your data into a structured, high-performance repository.
How a solution like this could impact your business:
- Single Source: Eliminate data silos by integrating all business data into a centralized, structured warehouse.
- Improved Reporting: Enable real-time access to up-to-date data, reducing manual data preparation.
- Scalability & Performance: Handle increasing data volumes with optimized storage and query performance.
Through data centralisation we help you eliminate data silos, ensuring reliable access for analytics, reporting, and AI-driven insights.
Data Analysis
We transform raw data into actionable insights, helping you uncover patterns and trends to make informed decisions.
Examples of data analysis applications:
- Identify key customer segments for targeted campaigns.
- Uncover sales trends that lead to boosts in revenue.
- Optimise resource allocation, saving your business time and resources.
Use Case
Uncovering Hidden Revenue Opportunities
Transform raw data intro actionable information and insights, that can support logical problem solving, and help you make data-driven decisions.
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What if you could identify untapped revenue streams hidden in your existing data?
With advanced data analysis, you can uncover patterns and trends beyond human comprehension. Combine previously unrelated sources, identify new significant correlations, group data into similar segments, or identify anomalies or irregularities in operational processes – the list goes on.
How a solution like this could impact your business:
- Customer Insights: Analyse purchase behavior to identify high-value customers and develop targeted campaigns that drive repeat business.
- Product Optimisation: Spot underperforming products or services and reallocate resources to higher-demand offerings, improving revenue margins.
- Operational Efficiency: Pinpoint inefficiencies in resource allocation, enabling cost reductions and productivity gains.
With data analysis, your business can transform raw numbers into actionable strategies, paving the way for sustained growth and improved profitability.
Data Visualisation
We make complex data easy to understand through interactive dashboards and dynamic plots.
Examples of data visualisation applications:
- Real-time sales dashboards for quick decision-making.
- Interactive financial summaries to guide investments.
- ESG Performance tracking reports for accountability and reporting.
Use Case
Automated ESG Reporting
Meet the increasing reporting requirements across areas with intelligent technology that can automate workloads and ensure compliance with relevant standards.
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What if you could reduce the time required to create detailed ESG reports from weeks to hours?
Creating detailed ESG reports does not have to be a time-consuming operational burden. With a dashboard- and data visualisation solution, you can largely automate the process — pulling data directly into professional predefined reports that are ready for refinement or use.
How a solution like this could impact your business:
- Efficiency: Automate reporting workflows, cutting down preparation time dramatically.
- Compliance: Generate reports that adhere to EU’s CSRD and ESRS standards with clear, contextualised visualisations, key figures, and textual descriptions.
- Improved Storytelling: Present data through descriptive, actionable insights and dynamic plots embedded directly into dashboards.
A dashboard and data visualisation solution can save significant time and resources, enabling your team to focus on growing your core business rather than being overwhelmed by reporting tasks.
Machine Learning
Automate processes and boost efficiency – we design algorithms custom-built for your needs.
Examples of machine learning applications:
- Custom chatbots to handle customer queries.
- Anomaly detection systems to prevent fraud.
- Recommendation systems to boost product sales or improve customer experience.
Use Case
Identifying Valuable Customers with AI
Focus on the customers who matter most. Using your customer data, machine learning can predict which customers are most likely to bring long-term value to your business.
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What if you could focus your efforts on the customers who bring the most long-term value to your business?
By implementing a machine learning model to predict Customer Lifetime Value (CLV), your team can prioritise resources, deliver personalised experiences, and increase overall retention and revenue.
How a solution like this could impact your business:
- Insightful Predictions: Use AI to predict each customer’s lifetime value based on transaction history, engagement patterns, churn risk, or other relevant factors.
- Targeted Efforts: Identify high-value customers to deliver premium support and tailored offers, while nurturing at-risk customers with retention campaigns.
- Efficient Resource Allocation: Focus your team’s efforts on strategies that maximise ROI; reduce churn and increase revenue retention.
With machine learning applications such as CLV predictions, your business can strategically allocate resources, improve customer satisfaction, and build stronger, more profitable relationships with your client base.
Predictive Analytics
We use predictive models to forecast trends and outcomes, helping you to plan ahead with confidence.
Examples of predictive analytics applications:
- Forecast inventory needs to reduce stockouts.
- Predict customer churn for targeted retention strategies.
- Anticipate market shifts for strategic business planning.
Use Case
Automated Sales Prediction
Transform the way your team forecasts sales and manages inventory. By automating the process with predictive AI, you can save time and enhance accuracy.
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What if your team could spend significantly less time on forecasting and managing inventory, and more time driving strategy and delivering value?
With predictive AI, your team can automate routine processes that take up valuable time and resources. The models feed on your historical data to derive value and uncover subtle patterns that make predictions more accurate and decision-making faster. Instead of spending hours weekly manually forecasting, a predictive model can take over, streamlining the process and freeing up valuable time for your team to focus on nurturing client relationships and driving strategy.
How a solution like this could impact your business:
- Accuracy: Achieve AI-driven predictions that match or exceed manual estimates, improving decision-making and reducing human error.
- Efficiency: Automate the entire process, cutting the prediction workload to near zero, and giving your team more time to focus on core business tasks.
- Scalability: Seamlessly handle growing data volumes as your business expands, without adding to your team’s workload.
By implementing predictive analytics, your business can likely reduce overstocking, lower storage costs, and redirect employee time toward higher-value activities that directly contribute to growth.
Workshops
Empower your team with hands-on learning to demystify AI and apply it in everyday operations.
GenAI for the Workplace – Practical Skills for Your Team
Explore how Generative AI can transform workflows and improve productivity.
Available for ChatGPT and Copilot.
What you and your team will learn:
- A general understanding of artificial intelligence (AI)
- Real-world applications of AI in the workspace
- Practical skills with GenAI (prompt engineering)
- Critical thinking and ethical GenAI use
- GenAI for communication, streamlining tasks, productivity and development
- Hands-on experience with GenAI (only included in half-day and day workshop)
Choose the format that works for you:
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Day workshop (7h): Interactive, hands-on, and packed with practical with insights and use cases across numerous areas.
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Half-day workshop (3.5h): Focused, semi-interactive sessions with selected use cases.
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Talk (1.5–2h): A dynamic, demonstration-style introduction with homework to try later.
Ready to Discover Your Data’s Full Potential?
We would love to get a glimpse into your world. Book a free initial consultation and let’s start with a conversation about your situation or challenge, and how we can help your SME leverage data and integrate AI to realise your business goals – whether it is boosting efficiency, reducing costs, or driving sustainable development.