AI & Machine Learning Policy

Understanding how our rostering system uses AI

Overview

SKEDA uses agentic AI, providing it with optimisation algorithms tooling to solve complex scheduling problems. AI and LLMs are used only as a coordination function, automatically evaluating the quality of the solutions before they are shown to our users, in order to provide the best possible experience. All the raw data generated by the solving algoritms is shown to the user, so that the agent cannot inadvertedly limit their control over the solutions proposed.

Our Technology

Tabu Search

We use a sophisticated optimization algorithm called Tabu Search. This technique is very effective at solving complex scheduling problems where multiple constraints must be satisfied simultaneously.

Why Not Large Language Models (LLMs)?

Inefficiency

LLMs are not designed for mathematical optimization and would be computationally expensive for scheduling problems.

Lack of Precision

LLMs generate text, not mathematical solutions, making them unsuitable for precise scheduling optimization.

Constraint Handling

LLMs cannot systematically handle complex constraint systems required for legal compliance.

Our Approach

Purpose-Built

Our algorithm is specifically designed for scheduling optimization problems.

Computationally Efficient

Optimized for speed and resource usage, making it practical for real-world applications.

Constraint-Aware

Systematically handles complex compliance requirements and staff preferences.

Important Limitations

No Guarantee of Optimality

While our algorithm finds good solutions, it does not guarantee finding the absolute best schedule. This is a fundamental limitation of heuristic optimization approaches. However, our solutions are consistently high-quality and meet all specified constraints.

Transparency & Control

We believe in transparency about our AI systems. You can review the constraints and preferences that influence our scheduling decisions, and our system provides explanations for why specific assignments were made. This helps build trust and allows for human oversight and adjustment when necessary.

Questions?

If you have questions about our AI and machine learning approach, please don't hesitate to contact us.

SKEDA

AI enhanced scheduling for your team.

Privacy Policy

We are committed to protecting your privacy and keeping your data secure.

Data Collection: We only store user IDs and emails from your authentication providers (Google, Microsoft).

No Personal Data: We do not collect, store, or process any other personal information.

Data Usage: Your data is used solely for authentication and service delivery.

AI & Machine Learning Policy

Our rostering system uses agentic AI as a coordinator, but provides the agent with custom tooling to find solutions mathematically rather than by prompting an LLM

Technology: We use Tabu Search, a costraint solving technique specifically designed for optimization problems.

Efficiency: Our approach is computationally efficient and purpose-built for scheduling.

Limitations: While our algorithm finds good solutions that satisfy your constraints, it does not guarantee finding optimal solutions. This is a property of Tabu search which allows efficient exploration of the problem space in a short amount of time.

Contact Us

Have a question or need a demo? Drop us a line anytime.

Email: info@sked.app
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