Time and materials

Time and materials (T&M) bills you for the effort spent: a day rate or hourly rate per engineer, plus any direct costs such as cloud usage or model inference. There is usually an estimate, but the estimate is not a commitment. If the work takes longer, the invoice grows. If it finishes early, you pay less.

It works well when nobody can honestly define the outcome in advance: research spikes, ongoing product development with a changing roadmap, or embedding engineers into an existing team. Our dedicated pod model is a form of T&M with a monthly retainer, because a pod's backlog is set by your product team, not by us.

T&M is not the same as fixed price, fixed date, and it is not automatically cheaper. Without a clear backlog and weekly review, T&M engagements drift, and the buyer discovers the overrun only when the invoices arrive. We default to fixed-price programs for defined outcomes and use T&M only where the scope genuinely cannot be locked.

• CFO: costs are variable and open-ended, so you need a monthly budget ceiling and reporting to avoid surprises.
• CTO / Head of Engineering: T&M gives you control of priorities week to week, but you also own the outcome if the backlog is unclear.
• Product manager: a changing roadmap fits T&M better than a fixed scope, provided you review burn against progress every sprint.
• Founder / CEO: the model is easy to start and easy to stop, which suits early exploration before you commit to a larger build.

Time and materials exists because some work cannot be scoped honestly before it begins. Forcing a fixed price onto genuine research produces either padded quotes or disputes. T&M lets both sides start quickly and adjust as they learn. The trade-off is that the buyer carries the risk of overrun and must actively manage the engagement. We use it for pods and for exploratory work, and we recommend a fixed-price program for anything with a definable outcome, because a fixed scope forces the hard prioritisation conversations to happen before money is spent rather than after.

• A SaaS company retaining a two-engineer pod to extend an existing copilot feature set across quarterly roadmap changes.
• A FinTech running a research spike on open-weight models for bank-statement analysis before deciding on a production build.
• A logistics operator embedding an engineer into its in-house team for ongoing dispatch-platform improvements.
• A retailer paying by the hour for peak-season load testing and tuning where the effort depends on what the tests reveal.
• An education platform funding continuous content-generation tooling that evolves with each academic term.

ConceptA commercial model, not a skill. At Eazyware it appears as monthly dedicated-pod retainers and occasional research spikes; defined outcomes are delivered under fixed-price programs instead. Pods are described on the pricing page.

Eazyware service that covers it: Pricing. Starting prices are on the pricing page.