Unpredictable costs
Token-based pricing means your bill scales with usage, not value. A successful pilot can become an unbudgeted line item within a quarter.
Alt Horizon · AI consultancy
AI adoption that pays for itself. Without defaulting to the cloud.
Most AI projects fail at the economics and governance layer, not the demo layer. We model your options first, then recommend the one that survives cost, compliance, and operational reality.
Three reasons AI buying goes wrong
Before you pick a model, pick a constraint. The teams we see struggling have usually skipped this step.
Data sovereignty and compliance
If your data is regulated, sensitive, or commercially valuable, "send it to someone else's API" is a decision, not a default. Most teams make it by accident.
Tooling without a thesis
Copilots, agents, RAG, fine-tunes: the market sells answers before the questions are clear. We start with where value is actually created, then choose the tooling.
30–60%
of the real cost of running AI is operational overhead: support, monitoring, governance, re-training. The API line item is usually the smaller half.
How we think about AI adoption
Three principles hold across every engagement. Everything else is negotiable.
Evidence before enthusiasm
Real numbers before you commit. Volume estimates, total cost of ownership, and a ROI model. Not a demo.
We don't assume cloud
Cloud, self-hosted, hybrid, and platform-native are four different answers to four different questions. We model all of them.
If it doesn't pay for itself, it doesn't ship
We will tell you to wait, descope, or not adopt, and we have. Recommendations you can defend to a CFO.
Instrumented, not inferred
Cloud AI hands you a token bill. Self-hosted AI gives you kilowatts, emissions, and an audit trail per workflow. If sustainability reporting sits anywhere near your AI strategy, that difference matters more than it looks.
A repeatable process for measurable outcomes
Five phases, five concrete deliverables. Same method whether you're scoping a single use case or a portfolio.
Consultancy engagements
A typical engagement runs from a half-day Assessment through to live, measured deployment. Scope scales with ambition: one use case, a portfolio, or a full adoption programme.
Discovery & Assessment
Half-day workshop and short-form report. Current-state inventory, data-sensitivity review, and use-case longlist. Outcome: a grounded view of what to do next, before you spend on tooling.
Cost & ROI modelling
Detailed cost and ROI model on 3–5 shortlisted use cases. Cloud, self-hosted, and hybrid priced side-by-side with assumption ranges, not single-point forecasts.
Phased implementation
MVP, integration, governance, training, go-live. Milestone-based. Measured against the KPIs set in Assess. No implementation without a ROI case.
Horizon Portal
A self-hosted AI management platform for operations, governance, and security-conscious teams. One dashboard for agents, tickets, alerts, and change workflows, with policy and usage controls sitting underneath.
What it does
- Run AI-assisted operations without sending data to someone else's cloud.
- Manage Windows, Linux, macOS, and container fleets from one interface.
- Set usage and policy controls so adoption doesn't outrun governance.
- Monitor security posture (vulnerabilities, certificates, compliance) alongside AI workflows.
- Expose status and service views to customers where it helps them, not your competitors.
Who Horizon Portal isn't for
Teams who prefer cloud-first, SaaS-only deployment with no self-hosting appetite, or who don't yet have an AI use case with a justified ROI. Start with the discovery call instead.
UK-based. Global reach.
Typical engagements involve a CIO, CTO, or CFO accountable for AI spend, and a 6–18 month adoption roadmap.
Ready to make AI work for your business?
Thirty minutes, your use case, a straight answer. No slide deck.