How We Engage

From first call to
live in production.

Enterprise buyers need to know how an engagement actually runs before they can build an internal business case. Here is the real structure — timelines, deliverables, and team composition.

The Path

Four stages, from discovery to ongoing operation.

01
1–2 weeks

Discovery Sprint

We map your current workflows, data architecture, and regulatory constraints. You get a clear ROI priority matrix — not a generic capabilities deck.

📦 AI Readiness Report + Priority Matrix
02
8–14 weeks

Pilot

We build one production-grade AI workflow end-to-end — fully governed, audit-ready, integrated with your live systems via MCP. Not a sandboxed demo.

📦 Live AI System + Audit Trail + KPI Dashboard
03
3–9 months

Scale

With proof established, we extend the architecture to additional workflows and departments, consolidating governance across all live systems.

📦 Multi-Workflow AI Platform + Governance Framework
04
Ongoing

Operate

Continuous monitoring, retraining, and optimisation — either handed to your internal team with documentation, or retained as an ongoing HYVE engagement.

📦 SLA-backed AI Operations + Quarterly Reviews

Engagement Models

Choose the structure that fits how you buy.

Fixed-Scope Project

Best for a single, well-defined workflow

Clear deliverables, fixed price, fixed timeline — ideal for a first AI pilot or a defined compliance deadline.

Embedded Team

Best for ongoing, evolving AI programmes

HYVE engineers work inside your team and sprint cadence — ideal for multi-department transformation with shifting priorities.

Outcome-Based Retainer

Best for measurable KPI ownership

We agree target metrics upfront (cost saved, time reduced, accuracy gained) and remain accountable to them post-launch.

Not sure which model fits your organisation?

Tell us your constraints — budget cycle, procurement process, internal team size — and we'll recommend a structure.