Data engineering and AI
Pipelines, lakehouses and reporting on Databricks and Python, so your numbers are right and your AI plans have something solid underneath.
Sometimes the most useful thing an engineer can do is look at what you have and tell you the truth about it. We review systems, suppliers and plans, then write it up in plain language for the people who make the decisions and sign the cheques.
Most of our consulting work starts with one of these. Often the client already suspects the answer and wants someone independent to confirm it.
Every piece of consulting work ends with a written document and a conversation. You get findings, reasons and a recommended order of work, not a slide deck of possibilities.
We look at how your systems are built, hosted and connected, and how the team works on them. You learn what is solid, what is fragile and what will get expensive if nothing changes.
A realistic plan for the next year or two, ranked by value and effort, that says what to build, what to buy, what to automate and what to stop doing altogether.
An honest comparison of writing your own software against using an existing product, including the running costs, the risks and the time each option really takes.
Help writing requirements, shortlisting suppliers, asking the right questions in demos and reading the contract terms that matter once the sales team has gone home.
An independent assessment of a company's technology for investors, acquirers and boards, covering code, security, infrastructure, costs and how much rests on a few key people.
We find the few places where AI would clearly save time or money in your business, check whether your data can support them, and advise on privacy and the EU AI Act before anything is built.
When a project has lost its way, we work out what is actually finished, what is missing and what it will take to deliver. Then we help you decide whether to continue, change course or stop.
Short, focused and fixed in price. Most reviews take a few weeks from the first conversation to the final report.
We start by writing down exactly what you need to decide. A clear question keeps the review short and the answer useful.
We read the code, the documents and the invoices, and we talk to the people who build, run and use the systems. Nothing replaces those conversations.
A report in plain language with findings, risks, costs and a recommended order of work, plus a technical appendix for engineers.
We walk you and your team through the report, answer the hard questions and help you plan the first steps, whoever ends up doing them.
An executive summary of two or three pages. A findings register with each issue rated for risk and effort. Architecture diagrams in the C4 model style so everyone sees the same picture. Architecture decision records for the main recommendations. Where delivery is in question, a baseline of the four DORA metrics: deployment frequency, lead time for changes, change failure rate and time to restore service.
Code and dependency analysis, cloud cost breakdowns, a security review informed by ethical hacking practice, and structured interviews with the people involved. We treat everything you share as confidential and happily sign your NDA first.
More on how we work across all projects is on our technology and standards page.
Anything else? Email info@avientiq.com and one of our engineers will reply.
That is the point of it. The main report is written for directors and owners, with the reasoning and the costs spelled out. The technical appendix is there for your developers or your next supplier, and you can skip it.
Yes. We take no commissions or referral fees from vendors, so a recommendation is only there because we think it suits you. If we would like to do some of the work that follows ourselves, we say so openly and you are free to use someone else.
We can. We look at the architecture, code quality, security, hosting costs, the team and how much depends on a few key people. The result is a written assessment of risks, likely costs to fix them and questions worth asking the founders, delivered on a timetable agreed before we start.
Reviews are priced as a fixed fee once we understand the size of the job. A focused review of one system is a small piece of work. A roadmap for the whole company takes longer. You will know the price before we start.
Pipelines, lakehouses and reporting on Databricks and Python, so your numbers are right and your AI plans have something solid underneath.
Azure and AWS setups that are secure, automated and sensibly priced. We also tidy up the ones that grew by accident.
Practical support for new tech leads, founders without a CTO and engineering teams that have lost their rhythm.
Send a few lines about your project or the problem in front of you. We'll come back with honest questions, a rough plan and a sense of cost. No sales pitch unless you ask for one.