Professional Services
Accelerate your adoption of LakeLogic.
Architecture reviews, implementation support, governance design and platform integration, delivered by the team that builds LakeLogic. We work on the stack you already run and get you to governed, AI-ready data faster.
Extend, modernise and govern what you already run for AI workloads.
Most organisations are not ready for AI.
The state of most data estates
Five patterns show up on almost every engagement, and buying another tool fixes none of them. They need architecture, governance and disciplined delivery.
Fragmented data ecosystems
Lakehouses, warehouses, lakes and vendor silos each have their own quality regime, lineage gaps and access model, and AI workloads pull from all of them.
Limited data trust
Producers and consumers have no durable contract, so schema drift, broken pipelines and silent quality regressions are routine.
Slow engineering delivery
Every new domain takes a quarter. Reviewers spend cycles on manual checks that should be enforced as code.
AI readiness gaps
Models train on poorly governed sources with unclear PII boundaries and no provenance, so the business cannot see where an output came from.
Legacy technical debt
Critical pipelines still run on SSIS, Informatica or Hadoop. The team is afraid to refactor them and cannot leave them alone.
Every way we get you live on LakeLogic.
Services
Whether you start from a greenfield lakehouse, a mature EDW or a fragmented mix, every engagement ends the same way: your estate governed by LakeLogic, contracts enforced, incidents triaged by Zeus, and your team self-sufficient.
Lakehouse Architecture & Modernisation
Reference architectures for Microsoft Fabric, Databricks and Azure-native lakehouse stacks, with LakeLogic contracts as the governance layer from the start.
Enterprise Data Warehouse Modernisation
Extend SQL Server, Oracle, Teradata and SSIS/Informatica estates with a governed lakehouse layer running LakeLogic, keeping what already works. Migrate workloads when contract-backed evidence shows they are ready.
AI Readiness Advisory
Find where your data is ready for AI and where it is not, then close the gaps with LakeLogic contracts, quality gates and lineage that make governance, freshness and PII boundaries concrete.
Data Governance & Data Contracts
Codify domain ownership, SLAs, and quality rules as executable contracts. Enforce at PR time and runtime. Replace ticket-driven governance with automation.
Data Observability & Reliability
Estate-wide health and incident triage that shorten the time to recover. Bad rows are quarantined before they reach gold, and one place answers "is everything OK right now?"
AI-Assisted Delivery Accelerators
LakeLogic, Zeus and contract-aware code generation shorten the work of ingestion, contract definition and remediation.
Start with a Lakehouse Readiness Assessment.
Complimentary · Selected organisations
A focused, hands-on assessment that gives you a concrete answer to “are we actually AI-ready, and what’s the shortest path?” Delivered by senior architects who run this work daily.
Request your assessmentArchitecture review
Current-state map of ingestion, storage, and serving across cloud + on-prem.
Governance assessment
Ownership, quality, lineage, and PII boundary scoring against AI-readiness rubric.
AI readiness evaluation
Concrete signals: provenance, freshness and contract coverage.
Target-state recommendations
Modernisation moves ranked by cost, risk, and time-to-AI-value.
Prioritised roadmap
Sequenced 90 / 180 / 365-day plan with measurable milestones.
Four phases. Outcome-anchored.
Delivery model
Each phase has a deliverable, an exit criterion and a hand-back point. There are no open-ended retainers.
- 01
Assess
An architecture, governance and AI readiness baseline, completed in days.
- 02
Design
Target-state lakehouse architecture, contract-first operating model, and migration sequencing.
- 03
Accelerate
Stand up the foundation with LakeLogic accelerators: contracts, quality gates, Zeus AI and observability.
- 04
Operationalise
Hand over to internal teams with playbooks, training, and an enforceable governance baseline.
We use what we recommend.
Why LakeLogic
We built the platform we use to deliver. The architecture patterns, governance models, and AI accelerators we recommend are the ones running our own product.
AI-native delivery
We use our own AI accelerators on every engagement. The same Zeus agent that diagnoses your incidents in production drove our delivery from week one.
Open architecture
No vendor lock-in. Apache 2.0 OSS at the core, ODCS-compliant contracts, runs on Polars, DuckDB, Spark, Fabric, Databricks, and EMR.
Governance-first
Contracts, lineage and PII boundaries are designed in from the start, so compliance for AI work is part of the default setup.
Built for modern AI data teams
Domain ownership, medallion architecture and contract-first delivery: we ship the operating model we built our own platform around.
Ideal engagements.
Where we add the most leverage
We focus on modernisation, governance and AI readiness, where LakeLogic helps most and a small senior team can get you to a governed platform quickly.
- Building modern lakehouse architectures on Microsoft Fabric, Databricks, or Azure
- Modernising SQL Server, Oracle, Teradata, or Informatica estates without ripping them out
- Preparing data foundations for AI adoption: RAG, agentic workflows and ML training
- Improving governance, lineage, and trust across federated domain teams
- Consolidating legacy on-prem data estates into a governed cloud platform
- Standing up a governed, contract-first data platform from scratch
Supported ecosystems
LakeLogic governs the platforms you already run.
We also work across hybrid and multi-cloud setups. LakeLogic runs on Polars, DuckDB, Spark or a supported warehouse, so we govern your estate where it already is.
Start here
Start with a readiness assessment.
A focused engagement with senior architects that ends with concrete findings, a prioritised roadmap and a clear path to an AI-ready foundation.