KyperX AI / Services
AI consulting and engineering services, matched to the problem.
Start with the question you actually have.
Four ways to engage, and nine technical capabilities behind them. Most engagements combine several.
Offer 01
AI assessment and roadmap
- What you receive
- Workflow review, data and integration constraints, prioritised opportunities, and a scoped pilot recommendation.
- First engagement
- Assessment
Capabilities
What gets applied inside an engagement.
Four ways to buy; nine technical capabilities behind them. Select an offer to see which it draws on — most engagements combine several.
01AI assessment & roadmap
Structured review of where AI is practical in a given workflow, and what it would take to get there.
02AI & workflow automation
Automating repetitive process steps, with exceptions routed to a person rather than passed through.
03AI agents
Multi-step tasks using tools and data, with the level of autonomy and human checkpoints suited to the application.
04Custom AI systems & applications
Applications built around your own information, workflows and interfaces rather than a generic product.
05Private & on-premise AI
Deployment inside environments you control, for cases where information cannot leave.
06Integrations
Connecting AI to the tools, data sources and review steps your team already uses.
07Computer vision
Detection, classification, measurement and monitoring from visual information.
08Machine learning
Prediction and classification where the data and the application genuinely support it.
09AI infrastructure
Specifying, designing and deploying the compute, storage and access architecture an AI system runs on — in your environment, on dedicated capacity, or on hardware you own.
Capability detail
Every capability, including what it does not cover.
Select any capability above to see its anatomy. The fourth column is the one worth reading.
What you supply
What we do
What you receive
What it does not cover
AI assessment & roadmap
You supply: Access to the workflow, the people who run it, and sample documents
We do: Structured review of steps, data, constraints and integration points
You receive: Prioritised opportunities, a scoped pilot recommendation, a constraints register
Not covered: Does not include building anything. It ends with a recommendation you can decline
AI & workflow automation
You supply: One defined workflow, sample data, an owner who can approve acceptance criteria
We do: Integration into existing tools, exception routing, acceptance testing
You receive: A working automation, a documented exception path, handover
Not covered: Not organisation-wide process redesign. One workflow at a time
AI agents
You supply: The task, the tools and data it must reach, and the decisions a person must keep
We do: Agent architecture with defined autonomy and explicit human checkpoints
You receive: An agent operating within stated bounds, with an audit trail
Not covered: No autonomous action outside the agreed scope, by design
Custom AI systems & applications
You supply: Your information, the interfaces it must fit, and the people who will use it
We do: Application design, data connections, evaluation against agreed criteria
You receive: A system built around your workflow, documented for your team
Not covered: Not a product licence, and not ongoing feature development unless separately agreed
Private & on-premise AI
You supply: The control requirement, the target environment, the network position
We do: Deployment architecture inside your boundary, with access controls agreed
You receive: A running deployment you control
Not covered: Private hosting changes who can reach the system. It does not by itself make a model more accurate
Integrations
You supply: The systems involved, their APIs or export paths, and permission to connect
We do: Bounded interfaces with failure made visible rather than silent
You receive: A connected flow with acceptance checks at each handoff
Not covered: We do not take ownership or operation of your source systems
Computer vision
You supply: Representative images, labels or a labelling route, and an accuracy target
We do: Model selection or training, evaluated on held-out samples from your data
You receive: A vision component with measured performance on your own samples
Not covered: Performance is measured on your samples. It is not a general guarantee
Machine learning
You supply: Historical data with the outcome recorded, and enough of it
We do: Feature and model selection, evaluated against a stated baseline
You receive: A model with stated performance and its limits written down
Not covered: If the data does not support the problem, we say so and stop. That is a valid outcome
AI infrastructure
You supply: Workload profile, control requirements, and site or power constraints
We do: Architecture, sizing, sourcing through providers, integration and commissioning
You receive: A deployment specification and a working environment
Not covered: Specification, design and integration. Not facility construction
Division of labour
What you supply, and what we do.
An engagement has obligations on both sides. Knowing yours is what makes a budget possible.
Deployment
Where your system runs is a design decision.
Privacy, control and latency push one way; elasticity and breadth push the other. Ownership is a separate question again, and the one most often blurred.
Not sure which applies?
Describe the work and we will tell you which engagement fits, or whether none does.