Managed AI Services and Talent
How the work gets staffed and kept running after launch. Seven engagement models, each with a written route to your team taking it over — because a supplier you cannot leave is a dependency, not a service.
Most AI failure happens after the build.
The system launches, the team disperses, and nobody owns what happens next. Models drift with no one watching, retraining happens when someone remembers, costs move without explanation, and eighteen months later an expensive capability is quietly performing worse than the spreadsheet it replaced. None of that is a modelling problem, and none of it is fixed by building something else.
So every engagement here is defined by numbers and by an exit. Service levels with consequences rather than best efforts. Named people rather than profiles. Knowledge transfer as a deliverable rather than a courtesy. And a written handover plan agreed at the start, while everyone is reasonable, rather than negotiated during a transition when nobody is.
What we build
Each is a standalone engagement with its own scope, price and output. Most clients use two or three in sequence.
AI Managed Services and Retainers
Ongoing operation against defined service levels, with a documented exit to your own team whenever you want it.
Read more →AI Staff Augmentation
Individual engineers embedded in your teams, to your standards, with knowledge transfer expected.
Read more →Dedicated AI Development Teams
A complete team with its own lead and your product ownership, plus a transition plan from day one.
Read more →Hire AI and ML Engineers
Role definition, technical assessment that predicts performance, and honest advice on what you can attract.
Read more →Model Maintenance and Retraining
Retraining on evidence, gated against the incumbent, with the honest call when retraining will not fix it.
Read more →24/7 AI Support and SLA
Real service levels with severity by business impact — and a straight answer when business hours would do.
Read more →AI Project Rescue and Recovery
An independent read on a stalled project: what is salvageable, what is not, and whether to continue at all.
Read more →How they fit together
You do not need all twelve. Most programmes follow one of these paths depending on where the uncertainty sits.
Keep systems running
Managed services and retainers against defined service levels, model maintenance and retraining triggered by evidence, and 24/7 support where the impact genuinely justifies it.
Add capacity to your teams
Staff augmentation for a missing skill in a team you already run, and dedicated AI teams where a whole workstream needs delivering.
Build your own capability
Hiring support — role definition, assessment that predicts performance, and the conditions that keep the person. Advisory and fixed-fee, not a placement commission.
Fix what has gone wrong
Independent project rescue, priced separately from any recovery so the conclusion is not for sale — including when the conclusion is to stop.
FAQ
Marked up with FAQPage schema so these answers can surface in search results and inside AI assistant responses.
Which engagement model do we need?
A defined outcome with a deadline should be bought as a project, where the delivery risk sits with us. An ongoing workstream with no capacity is a dedicated team. A team missing one skill is augmentation. Systems that need operating rather than building are managed services. A permanent capability means hiring, and we will help you do that.
Are we locked into a long relationship?
No, and the exit is written at the start rather than negotiated at the end: what is handed over, in what form, over what period, and what your team would need to run it. We would rather lose a renewal than hold a client through opacity, and we will recommend taking work in-house when that is the better value.
Can you support systems you did not build?
Yes, and it is a common case across managed services, retraining and support. Onboarding covers assessing and documenting what exists — frequently for the first time — and verifying that rollback works. Where something needs remediation before it can be operated safely, we price that separately and name it before any agreement starts.
Do you do body-shopping?
No. We propose named people rather than profiles, we do not substitute without your agreement, and we do not bill for one person while another does the work. Augmented engineers work in your process under your technical direction, and knowledge transfer is a checked deliverable rather than a courtesy.
What if our project is already failing?
Get an independent read before committing more budget. Project rescue is a two to four week assessment priced independently of any recovery work, precisely so that 'stop' remains an available conclusion — and a meaningful share of these assessments do conclude that.
Start with a conversation.
Thirty minutes, no charge, no deck. Tell us what you are trying to build with language models and we will tell you which of these engagements fits, or whether none of them do.