Four practices. Three ways to work with us.
We work with businesses of various shapes and sizes across four key practice areas, including data architecture, BI, research and AI/ML. Mozaik services come in the form of strategic advisory (i.e. we advise, you execute), consulting (e.g. we execute) and team training and mentorship.
Advisory, consulting, training.
Three ways to engage, across any of our four practices.
Direction, before commitment.
Strategic guidance without us touching your stack. Stack and vendor selection, architecture review, research design critique, roadmap definition — the judgement calls that are expensive to get wrong and cheap to get right if you ask the right person first.
Typical shape: a focused engagement of days or weeks, often a review with a written recommendation.
Hands on the keyboard.
We build what we recommend. Migrations executed, platforms deployed, dashboards designed, studies fielded, agent workflows shipped. Delivery work, owned end to end, by the person who scoped it.
Typical shape: weeks to months, defined deliverables.
So you don't need us next time.
We offer technical training, coaching and mentorship for data teams and practitioners. Programs can be delivered live on-site or remotely, or you can license our existing courses available on platforms like Udemy and Coursera for on-demand learning.
Typical shape: workshops, structured programmes, or ongoing enablement alongside a build.
Build on foundations that hold.
Most data problems presented as analysis problems are architecture problems. Reports that disagree, pipelines that fail silently, a warehouse that was right for the company three years ago and quietly stopped being right since. Mozaik designs, deploys and repairs the infrastructure your analytics depend on — for scale, for safety, and for correctness you can actually defend in a meeting.
- Database deployment, setup and configuration
- Data warehouse migrations and replatforming
- Database hygiene, quality and integrity audits
- Data modelling and schema design
- Pipeline and ingestion architecture
- Access, governance and security review
- Platform and vendor selection advisory
Reporting people use without being asked to.
A BI tool nobody opens is an expensive filing cabinet. Mozaik builds, migrates and tunes business intelligence environments so the answers are findable, trustworthy, and consistent no matter who runs the query — then pushes them out to the people who need them. Increasingly that means self-service: asking a question in plain language rather than waiting three days for someone to write the SQL. This practice also covers the presentation layer — dashboards, executive reporting, and the data storytelling that makes a finding land instead of merely being available.
- BI platform implementation (Metabase, Looker, Tableau, Power BI)
- BI platform migrations and consolidation
- Dashboard design and development
- Semantic and metrics layer definition
- Self-service analytics enablement
- Text-to-SQL and conversational analytics
- Executive and stakeholder reporting frameworks
- Data storytelling and presentation design
Evidence your own data will never contain.
Your warehouse is a record of what your existing customers already did. It cannot tell you why they did it, what the people who didn't buy were thinking, what a feature is worth before you've built it, or how your brand is faring with an audience that has never touched your product. Those answers have to be collected, not queried. Mozaik has run this work for fifteen years, across customer, product and brand — quantitative and qualitative, in more than thirty markets.
- Segmentation and ICP development
- Voice-of-customer and persona research
- Market sizing and opportunity assessment
- Pricing research (van Westendorp, Gabor-Granger)
- Concept testing and product validation
- MaxDiff and conjoint for feature prioritisation
- Brand tracking and health diagnostics
- Competitive positioning analysis
- Crisis monitoring and reputation research
Make your data legible to machines.
Pointing an LLM at a warehouse and hoping is how organisations end up with confident, fluent, wrong answers. Models don't fail because they lack intelligence — they fail because nobody gave them the context to know what a table means, which metric is canonical, or what "active customer" is defined as this quarter. Mozaik builds that layer: the semantic definitions, the retrieval, the custom tooling and agent workflows that let AI operate against your data with results you can check.
- Semantic and context layers for LLMs
- Custom MCP server development
- Agent workflows for data and research teams
- RAG over internal and organisational data
- AI-assisted analysis pipelines
- Evaluation and accuracy testing for AI outputs
- AI tooling strategy and stack advisory