Build a reliable, AI-ready data environment that delivers accurate insights at scale.
Structured foundations for data, analytics, and AI - designed and implemented exclusively by senior experts. No shortcuts, no guesswork, no vendor hype.
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We map your risks, metrics, and AI readiness before we touch anything.
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First insights and tangible results within the first week.
Focus
The foundations behind reliable analytics and AI.
Confidence
Transparent, measurable accuracy - no hidden logic, no guesswork.
Engagement
Hands-on, no outsourcing, no juniors
"You would not build a house starting from the roof. Yet most companies try to build AI on top of foundations that were never designed to support it. We give you the base to build fast, accurately, and without compromise."
Radek Duha, Head of Data, QuantumSpring
Start with the fastest path to measurable impact
Focused engagements accelerate delivery, align metrics, and unlock AI-ready insights.
Conversational Analytics
Because your senior analysts are trapped in manual SQL and dashboard firefighting.
Deploy reliable AI answers and NL2SQL with governance and evaluation built in.
Semantic Layer
Because business metric definitions drift across teams, creating KPI debates and inconsistent reporting.
Unify business definitions so teams and AI use the same trusted metrics.
AI Data Readiness Audit
Because you need a clear view of data quality, governance, and AI risk before investing.
We help you uncover issues and prepare for AI-enabled data work across your company.
Real results: conversational analytics at scale
A real-world, anonymized case study showing how AI-ready foundations unlocked instant answers, reduced costs, and improved decision velocity across the business.
How we build AI data foundations you can trust
Most AI initiatives fail because the data foundation was never designed for AI.
Start with meaning, not tools
Metrics, semantics, and context come first.
AI rarely fails because of models. It fails because metrics are unclear, definitions drift, and business meaning lives only in people's heads.
- Tools never first.
- Semantic layer never first.
- Business understanding first.
Design for humans and AI
If humans do not understand the data, AI will not either.
We design models, metrics, and relationships so they are understandable to analysts first, and usable by AI second.
- Clarity first.
- Semantic layer only when needed.
- Shared meaning over tech.
Guardrails over cleverness
Reliable answers beat smart demos.
We prioritize data quality, tests, and AI guardrails before advanced automation. Trust is built through consistency, not novelty.
- No fragile demos.
- Quality before automation.
- Accuracy over novelty.
Incremental, not theoretical
No big-bang rewrites. No academic architectures.
We improve what already exists. Step by step, with visible value early, and no rewrites unless they are unavoidable.
- Pragmatic improvements over slides.
- Early value, reduced risk.
- Rewrites only when necessary.
Enable teams, do not replace them
AI should reduce dependency, not create a new one.
Our goal is not to build systems that only we can maintain. We leave behind systems and teams that can run independently.
- Handover built in, not bolted on.
- Documentation and training included.
- Your team stays in control.
Fewer incidents. Faster decisions. Trustworthy AI.
The concrete wins teams see when the foundation is fixed: faster delivery, consistent metrics, safer AI, and less firefighting.
Faster time-to-insight
Faster delivery with cleaner architecture and a unified semantic layer.
100% accurate AI answers
Reliable answers backed by stronger metadata, governance, and evaluation guardrails.
Lean SQL and lower costs
Fewer redundant queries from optimized models and clearer definitions.
One source of truth
Reliable, company-wide reporting with aligned metrics and governance.
Analysts on strategy
Teams move from firefighting to experimentation and higher-value work.
AI-ready foundation
Stable groundwork for agents, NL2SQL, and automation without surprises.
Fewer incidents
Proactive monitoring and guardrails keep pipelines stable and AI outputs reliable.
Next step
Speak directly with Radek Duha
A short expert call to evaluate your data environment, identify the biggest risks, and see if AI & Data Foundations is the right move.
Clear guidance. Senior expertise. No sales talk.
FAQ
Answers before we start
Do we need a mature data team before working with you?+
No. Many clients come because the environment is fragmented or understaffed. We design foundations your existing team can build on immediately.
How long does an AI & Data Foundations project take?+
It depends on your situation, needs, and scope. In every case, we aim to deliver early wins within days and a working MVP within two weeks.
What do we need to prepare before starting?+
We typically need access to your DWH and dbt account. We will align on everything during our calls and document the intended use for each access request. We only request access to accounts we actually need for the agreed scope and tasks.
Will this replace our current tools or dashboards?+
No. We fix the foundation beneath them. Your existing dashboards, analysts, and AI initiatives benefit immediately from clearer architecture and definitions.
What if our data is messy or undocumented?+
That is normal. The process is built for missing documentation, inconsistent metrics, and historical shortcuts. We turn chaos into clarity.
