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- Scalable data pipelines with Apache Spark, Kafka, and Airflow
- Data lakes and warehouses (Snowflake, Databricks, BigQuery)
- ETL/ELT processes for multi-source data integration
- Real-time streaming for immediate insights and actions
AI & Machine Learning Consultancy
End-to-end AI and ML solutions from data engineering to production deployment. We build custom models that solve real business problems and deliver measurable ROI.
Scalexa is an AI and machine learning consultancy for CTOs and founders whose platforms can't afford to get AI wrong. If you are being asked to put a large language model in front of customers, automate a process that touches money or regulated data, or turn a promising prototype into something your operations team can rely on, this page is for you.
What we do
The problem is rarely the model. It is the data feeding it, the evaluation that should catch its mistakes, the infrastructure that serves it at a sensible cost, and the people who will be paged when it misbehaves. Most AI projects stall in the gap between a convincing demo and a production system.
We cover the full path from idea to monitored production system. Most engagements combine two or three of these.
LLM applications and retrieval-augmented generation (RAG)
We build assistants, search and document workflows on top of commercial and open models, grounded in your own data with retrieval. We design the chunking, indexing and prompt layer so answers are traceable to sources, and we put guardrails around anything a customer sees.
MLOps and production deployment
We take models out of notebooks and into versioned, monitored services with experiment tracking, a model registry and repeatable pipelines. Every training run is reproducible, every deployment can be rolled back, and drift is caught by alerts rather than by customers.
Computer vision
We build detection, tracking and document-reading systems that run on real-world images and video, not curated samples. Our work includes aerial roof-damage detection for NavGen and object tracking and blurring for law-enforcement video.
AI automation of business processes
We automate high-volume, error-prone work such as invoice reconciliation, candidate data intake and customer sentiment monitoring. The goal is fewer manual hours with a clear audit trail, not a black box your team has to babysit.
Model evaluation and independent audit
Before you trust a model, someone should try to break it. We design evaluation sets, measure accuracy against the cases that matter to your business, and provide independent technical audits, as we did for QOVES's NLP ingredient-classification system.
AI strategy and roadmaps
For leadership teams deciding where AI should and shouldn't go, we produce a grounded roadmap: which use cases are worth building, what data is missing, what it will cost to run, and what to do first. It is written by engineers who will be accountable for delivering it.
Capabilities
- Advanced statistical analysis for pattern discovery
- Predictive modelling and forecasting
- Interactive dashboards with Tableau, Power BI, Looker
- A/B testing and experimentation frameworks
- Custom ML algorithms for complex business problems
- Recommendation systems for personalisation
- Time series analysis and anomaly detection
- Feature engineering and model optimisation
- Custom models with TensorFlow, PyTorch, scikit-learn
- Deep learning for image, speech, and text
- Reinforcement learning for optimisation problems
- MLOps: model deployment, monitoring, and retraining
- Text classification and sentiment analysis
- Language translation and summarisation
- Named entity recognition and extraction
- LLM integration and fine-tuning (GPT, Claude, Llama)
- Object detection and image classification
- Facial recognition and biometric systems
- OCR for document processing and automation
- Video analysis and real-time processing
- Intelligent chatbots and virtual assistants
- AI-powered decision support systems
- Predictive maintenance for industrial applications
- Automated content generation and analysis
- Scalable AI system design and architecture
- Edge AI for real-time, low-latency processing
- AI integration with existing IT infrastructure
- AI governance and responsible AI frameworks
- Custom visualisations with D3.js, Plotly
- Real-time dashboards for monitoring and KPIs
- Data storytelling for executive presentations
- Embedded analytics for your applications
- Python, PowerShell, Bash automation scripts
- Workflow automation with n8n, Zapier, Airflow
- Automated testing and CI/CD pipelines
- Bot development for repetitive tasks
How we work
1. Free 30-minute call
We ask about the AI use case, the available data, the stakes and the deadline, and tell you honestly whether we are the right fit.
2. Scoped proposal
Following the free 30-minute call, we outline the priorities, proposed work and delivery approach in a scoped proposal grounded in your data and systems.
3. Delivery
The scoped work moves into accountable delivery. You get weekly billing on actual hours, a weekly summary of what was done, and code in your own Git organisation from day one.
4. Handover or ongoing support
Every engagement ends with documentation, runbooks and a recorded walkthrough. If you want ongoing support, we move to AI operations with agreed quality and cost measures.
Engagement models
Defined AI outcome
A focused engagement with a clear end: readiness, evaluation, a production use case or a technical review.
Embedded AI delivery
We work in your repositories and delivery process and take ownership of a defined part of the AI roadmap. You can scale up, scale down or stop at any point, with no long notice periods.
AI operations
We monitor and improve the AI system week by week: quality, drift, cost, reliability and controlled model changes, with clear reporting and ownership.
A proof of concept typically takes 2–4 weeks and a production MVP with monitoring 8–12 weeks, depending heavily on how ready your data is.
Relevant work
Technologies
Deep expertise in leading technologies to deliver enterprise-grade solutions
Why Choose Scalexa?
25+ years
Decades of experience building systems at scale for Fortune 500 companies.
You own it
Code in your Git organisation and infrastructure in your cloud from day one.
Free call, then a proposal
A free 30-minute call, then a scoped proposal with a time and cost range. No obligation.