Blog
Short pieces on day rates, salary benchmarks and sourcing models, written for the person who has to sign the contract. We publish twice a week and include the parts that don't favour us.
Where AI integration budgets actually go, what moves the price, how each vendor category fails, and when renting engineers by the day is the wrong purchase.
Indicative senior day rates by market, why the same job title costs three times more in one country, and the costs that never appear on a supplier rate card.
Where data migration budgets overrun, the three ways to buy the work, what moves the price, and when renting senior data engineers is the wrong call.
Cost both options on the same lines. When a vendor product wins, when building with your own engineers wins, and the hybrid that costs more than either.
Engineering time is 70-85% of first-year AI development cost. How to size the labour line, what doubles an estimate, and what the system costs to run.
Directory rankings are paid placement. Rank IT staff augmentation companies on bench depth, substitution clauses, employment model and rate transparency instead.
Why fixed-scope outsourcing contracts break on AI and data projects, the cost lines the quote leaves out, and when handing the work outside still makes sense.
Where an IT consultant hourly rate goes: bench time, bid cost, management layers and risk cover, with directional € rates by supplier category in Europe.
What MLOps consulting services deliver, how the five provider categories fail, what senior MLOps engineers cost per day in Europe, and when not to buy any of it.
Five categories of AI software development company, what a senior engineer costs per day in each, how they fail, and four checks to run before signing.
Nearshore staff augmentation explained: contract terms, day rate ranges, time zone overlap maths, EU compliance and when the model is the wrong buy.
Fixed price loads 20% to 40% onto AI and data work to cover estimation risk. When that premium is worth paying, and when capped time and materials wins instead.
The five kinds of AI agent companies, what each actually sells, where each one breaks, and why most agent projects stall on data engineering rather than agents.
Managed services transfer delivery risk at a 20-40% price premium. Staff augmentation keeps control and speed. Which fits AI and data work, and when each fails.
The four sourcing models for AI engineering compared on cost, speed, accountability and exit risk, including the cases where staff augmentation is the wrong answer.
Day rate bands for senior AI, ML and data engineers across the UK, Germany, Poland and Romania, what drives the spread, and how to read a quote you have been given.
Why dividing an engineer's salary by working days understates the true cost by 30 to 50 percent, and the full calculation to run before comparing hiring against contracting.
The questions that separate vendors who ship production AI systems from vendors who demo them, plus the answers that should end a conversation early.
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