Find the AI use case worth building
We turn an idea into one focused product or feature, test it on real data and find out quickly whether it is good enough to invest in.
Machine Learning Consulting, AI Solutions & Data Science
Don’t waste time doing things by hand. Let AI handle it quicker and better
Empower your company with AI and machine learning solutions
Our AI expertise was built through real client work and refined in production. We delivered AI systems for companies including SMS Group and Emirates Group, solving real operational problems. Today, we apply that production experience across four core areas — each built around a clear business problem and designed to work in real operations.
AI systems we build
AI agents & multi-agent systems
We build AI agents that work directly inside the software your teams already use.
They can read screens, enter data, move between systems and complete routine steps, even in legacy or closed software where APIs are unavailable or integration is too expensive.
This helps reduce manual work, speed up processing and automate workflows that previously had to be done manually. For more complex processes, we combine specialised agents for tasks such as retrieving information, validating data and preparing actions.
What you get: a controlled AI workflow that cuts manual work and onboarding time, speeds up operations and fits into the systems you already use.
Enterprise RAG & AI search
Let your teams ask questions across company documents and get clear answers with links to the source.
We connect AI to manuals, policies, contracts and knowledge bases so employees spend less time searching and can make decisions faster.
The system keeps information up to date, respects access rights and avoids unsupported answers when there is not enough evidence.
What you get: a searchable company knowledge base that speeds up access to information, reduces repetitive questions and fits into your existing tools through an interface or API.
Custom AI applications
Put custom AI into your product or internal platform to automate tasks, improve the user experience and add capabilities that were not possible before.
We build AI features such as smart assistants, intelligent search, personalised recommendations, content generation and tools that help users complete complex tasks.
We deliver the full application around the model, including the interface, business logic, integrations, permissions and validation needed for production use.
What you get: a production-ready AI capability built into your product, designed to automate key tasks, improve the user experience and create new product value.
Computer vision
Use computer vision to automate quality control and catch defects before they turn into waste, rework or customer complaints.
We have deployed computer vision systems directly on production lines, where they inspect products continuously, detect defects in real time and give production teams a consistent quality check at scale.
This helps manufacturers reduce manual inspection, identify problems earlier and improve product quality without slowing down production.
What you get: a production-ready vision system integrated into your line and built to improve quality, reduce waste and lower the cost of inspection.
AI Cost Optimisation
Cut the cost of running AI without cutting quality.
We analyse where your AI budget goes — which models handle which tasks, how much context they use and where requests can be simplified or reused.
We then optimise the workload through model routing, caching, shorter context and, where it makes sense, migration to open-weight models such as Llama or Mistral.
For suitable workloads, we assess whether OpenAI API costs can be reduced by 3–5× while maintaining agreed quality and response times.
What you get: a clear optimisation plan, tested alternatives and a lower-cost AI setup built around your actual workload.
Where AI works best
How we help startups
AI is easy to demo. Building a product around it is harder.
We help startups choose what is worth building, get it into production and scale it without assembling a full AI team too early.
Make it work in production
Agents, RAG, model infrastructure, integrations, evaluation and monitoring — we build the parts around the model that make AI reliable, usable and affordable at scale.
Build for scale and acquisition
We have helped startups scale and supported companies through acquisitions. That experience changes how we build AI — cleaner architecture, measurable model performance, controlled infrastructure costs and technology another team can actually take over.
How we take AI to production
Ways to work with us
Start with the smallest step that can prove the opportunity.
Instead of committing to a large AI programme upfront, validate the business case first — on your processes, your data and your constraints.
Test it first. Scale what works.
AI Audit & Discovery — 1–2 weeks
We identify where AI can create the most value, estimate potential ROI and define a practical architecture and roadmap.
Rapid MVP / PoC — 3–4 weeks
We build and test a working solution on real data so you can see the value before deciding whether to scale.
AI Support & Optimisation — ongoing
We keep the system reliable as models, data and business requirements change — monitoring quality, performance, failures and security.
Our AI development stack
We select the stack for your workload, deployment requirements and existing systems. The tools below support different parts of the solution.
LLM applications and retrieval
LangChain and LlamaIndex for connecting models, retrieval and application logic. Hosted model APIs or suitable Llama and Mistral models, selected through task-level evaluation.
Model serving and optimisation
vLLM for serving supported language models. ONNX and OpenVINO for suitable model deployment and inference optimisation tasks.
Machine learning and data preparation
PyTorch, TensorFlow, Keras and XGBoost for model development. NumPy and Pandas for data preparation and analysis; Dask for suitable larger-scale processing workloads.
Backend services and integrations
Python, FastAPI and Flask for AI application services. APIs, tool and function calling, and MCP for connecting agents to tools and data sources.
Pipelines and event processing
Airflow for scheduled data workflows. Kafka, RabbitMQ, SQS and NATS for messaging and event-driven integration; WebSockets for live application updates.
Experiment tracking and operations
MLflow for experiment tracking and model lifecycle tasks, alongside application-level evaluation, monitoring, versioning and cost tracking.
Our development toolkit
Actions speak louder than words
Learn how we turn concepts into working solutions through real industry projects.
Computer vision monitoring solution
AI-supported control for trace heating systems
AI-powered reservoir management system
Efficient prediction of emergencies at pump stations and water reservoirs
Real-time smoke detection system
Quick and dependable smoke identification in live video footage
Banking recommendation system
Precise recommendations based on in-depth analysis of user behavior
UI interpretation system
Comprehensive screenshot analysis with real-time recommendations
Why choose XPG Factor for AI engineering
What makes us different? Why does our AI expertise matter? And why are we the right team for your project?
Here are just a few reasons to say “yes”.
Proven in production
Our AI expertise comes from real client work. We have delivered AI systems for companies including SMS Group and Emirates Group, working with real data, existing software and business-critical processes.
Built around business value
We look for places where AI can remove manual work, speed up operations and lower the cost of a process. We test the result on real data first, so you can see what actually works before investing in a wider rollout.
Security and privacy by design
We can deploy within your AWS or Azure environment or private infrastructure, with access controls, encryption and clear data-retention rules. Сlient data is not used to train public models.
MLOps and LLMOps expertise
We do more than connect an AI API. We monitor answer quality, failures, response times and cost, and version models, prompts and evaluation tests so changes can be tested before they reach production.
Customer stories
Nothing inspires us more than the sincere appreciation of our customers. It’s a clear sign we’re doing things right.
Christoph Schweinzer
Project Manager, Liebherr-Werk Bischofshofen GmbH
We’d like to thank XPG Factor for their exceptional collaboration since 2020.
It’s worth noting that we approached the specialists to strengthen our development team while working on a corporate internal ERP addon, and from the initial stage to the final delivery XPG Factor’s team was professional, knowledgeable, and extremely helpful.
High quality technical specialists, software and QA engineers got their job done quickly and competently which led to a smooth project workflow.
XPG Factor is a reliable technology partner and we look forward to working with them in the future.
What factor shows that your business needs AI transformation? XPG Factor!
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