Turn data into measurable business value.
We measure the opportunity first.
Then build what delivers the value.
Five data problems we get hired to fix
Data failures become more expensive when they are discovered too late.
We measure the cost and duration of failures before they are detected and resolved.
Data spread across systems creates duplicate infrastructure, manual work, and additional operating costs.
We measure the cost of running, moving, reconciling, and maintaining data across systems.
Conflicting reports create manual reconciliation, repeated analysis, and delayed decisions.
We measure reconciliation costs and the impact of decisions delayed by conflicting numbers.
Platform costs grow without a clear connection to the workloads and outcomes they support.
We measure which workloads, queries, storage, and services are driving cost.
AI models consume time and infrastructure without reaching production because the underlying data is not ready.
We measure the cost of stalled development and identify the data gaps that must be closed before production.
About us
Cadvel is a boutique data engineering consultancy based in Kraków, Poland. We help enterprises reduce costs, improve performance, and deliver measurable business value. Our expertise spans Snowflake, ClickHouse, Datadog, and modern data architectures.
We only fix what we can measure
We measure what your problem costs before we propose anything. If the savings will not cover the cost of fixing it, we say so and stop there.
Baseline
We establish where the problem starts, what it affects, and what it costs. You get the number and the method behind it.
We establish where the problem starts, what it affects, and what it costs. You get the number and the method behind it.
Root cause
We identify what is driving the problem: architecture, workload, cost, data quality, or process. Until the cause is clear, implementation is guesswork.
Proof
We measure the change on your data, in your environment. You keep the result and method; where implementation is in scope, the code stays in your repository.
Start with one defined problem and a measurable baseline
Start with a fixed-price assessment focused on one costly problem. Expand only if the findings justify it.
Diagnosis
We start with interviews and an architecture review, using production data only if the agreed scope requires it. You leave with a calculated cost and clear priorities.
Measurement pilot
One process or one source, with a working proof built in your cloud. You keep the result, method, and reusable code. Implementation beyond the pilot is agreed separately.
Senior expertise stays close to the work
We build each delivery team around the problem, required skills, architecture, and scope.
We start with one defined problem, not a broad transformation program.
We work with Snowflake, ClickHouse, and Datadog, and use other technologies where the workload requires them.
We work alongside your IT team, under NDA and with access agreed for each stage.
Every project leaves a number behind
Some clients remain unnamed. We publish the industry, the situation, the measured result, and the calculation method. We identify the company only with its consent.
Logistics & Transport
Sealand Liquids: ISO Tank Fleet Visibility and Utilization
Fleet utilization rose from 37% to 53% year on year and gross profit per tank-day by 21%, after tank status, lease costs and sales decisions were connected in one view.
Retail
Sales Data Reconciliation and Cloud Cost Assessment for an International Retail Group
$40,000 in potential monthly cloud savings identified in a six-week assessment, seven CRM systems reconciled with ERP and accounting, and key reports generated 40% faster.
Finance
Secure Data Sharing for an International Payments Technology Company
More than 4 TB shared across three core tables in one business day, with no duplicate storage and no separate data-transfer pipeline.
Manufacturing
Migrating a Manufacturing and Retail Data Warehouse from Oracle to ClickHouse
Query performance and out-of-memory failures resolved on 20 years of sales data, with stable ETL across datasets of more than 300 million rows.
How we work
You can stop after the first stage. We designed it that way.
The first stage gives you a decision, whether or not you continue with us.
Fixed-price assessment
We start with a fixed-price assessment focused on one costly problem. After that, you decide whether the findings justify further work.
Decision based on evidence
If the findings do not justify further work, we stop rather than recommend work the evidence does not support.
The knowledge stays with you
Code, documentation, and knowledge stay with your team. When the scope includes implementation, the code stays in your repository.
The cost of bad data rarely appears on the balance sheet
It appears elsewhere in the business:
Wasted hours.
Engineering time spent maintaining pipelines, reconciling reports, and fixing recurring failures.
Unexplained infrastructure costs.
Cloud resources and platform contracts that cannot be clearly connected to workloads, owners, or business outcomes.
Customer impact.
Delayed or incorrect information that slows resolution and damages customer retention.
Where data, operations, and regulation meet
Production data split between SAP, Oracle and operator systems, plus PPWR and ESG reporting requirements.
DORA on the data side, access control for people and autonomous agents, and the requirement for every number in a report to be fully reproducible.
Start with one costly problem.
We measure its cost and define the scope through a fixed-price assessment, then recommend what, if anything, to build.
We measure its cost and define the scope through a fixed-price assessment, then recommend what, if anything, to build.