"In a 2023 blog post, external, Palantir described the challenge of combining data from multiple government systems containing tens of thousands of visa applications and hundreds of thousands of accommodation offers."
This is the kind of thing GDS and other Civil Service departments build all the time, its a completely standard kind of challenge that a small team of Devs (+ supporting staff) from a departments DDAT department does day in and day out.
The output will be open source by default and use existing standards.
There's not really enough info to know if this is just a coin toss or something more. "Company tries to roll its own system and [saves / loses] money" is just a common story, one way or the other.
For context, the Homes for Ukraine refugee scheme cost 2-3 billion as of 2023. I can't seem to find an updated cost. This cost (from the article) was Palantir working for free for the first 6 months (could they have beat that, time wise?), then awarded 4.5m and 5.5m for two more 12 month terms, and now they're transitioning to something home-grown instead.
> The MHCLG [ Ministry of Housing, Communities and Local Government] said it initially needed a system which could be ready within days but, in seeking a "steadier service", later created an updated platform to meet the programme's longer-term needs and bring down costs.
I basically agree with the MHCLG's reasoning here. It's always worth at least experimenting to see if you can roll your own.
The MHCLG blog post that this article is reporting on is available here: https://mhclgdigital.blog.gov.uk/2026/04/09/from-emergency-t...
I would imagine with AI generated software this kind of replacing off the shelf software with internally created software will only increase.
Palantir needs to be banned in every EU country. The UK would be wise to do the same.
I would never trust an openly MAGA company.
Millions of pounds wasted by using Palantir tech in refugee system
(FTFY)
Palantir is very expensive. This is because:
1. they aim to deliver product company margins with a consulting-heavy model.
2. your software purchase funds a cadre of "free" FDEs and deployment strategists who customize your install, build a bunch of data pipes/transforms, and talk to people to figure out what all the data means.
This could be a good deal if your tech org is not very competent at integrating your data, or if you have a sudden, short-term need. In the longer term, it's probably cheaper and more effective to develop a competent tech team, modernize the source data systems, and roll your own integration -- but that also requires leaders with long-term vision who are resistant to external hype and pressure.