---
title: "AI Delivery Sprint: One Workflow to Production"
canonical: https://wavect.io/services/ai-delivery-sprint/
language: en
description: "A scoped AI delivery sprint for one business workflow. Wavect agrees readiness, acceptance, price and timing before building and handing over the result."
image: "https://wavect.io/img/general/bak/open_graph_preview.jpg"
---

AI Delivery Sprint

# One useful AI workflow, built through to a production handover.

Choose a recurring task with a clear owner and a measurable outcome. We turn it into a bounded implementation: one workflow, agreed integrations and a working production handover. The start date, price and delivery window follow the readiness assessment.

THE ENGAGEMENT

## A small scope with an operational finish line.

1. **Confirm readiness** Inputs, access, responsible owners and an achievable first release.
2. **Agree the commitment** Workflow boundary, acceptance evidence, price and delivery window.
3. **Build and hand over** Working integration, evaluation, operator training and next decisions.

DIRECT ANSWER

An AI Delivery Sprint is a defined implementation engagement for one ready-to-build AI workflow. It includes technical scoping, development, evaluation, integration and handover against written acceptance criteria.

Best for

- Teams with one identified workflow and an owner ready to make decisions
- Companies needing a bounded first AI implementation before expanding

Consider another approach

- An open-ended programme covering many departments
- A feasibility question that needs research before a delivery commitment

## Select a workflow with an available owner

A sprint needs a task that can be observed and accepted: triage incoming requests, prepare a draft for approval or extract records from a defined document family. We check access, sample inputs, integration constraints and who answers questions during delivery. Company-wide adoption and identifying many use cases belong with [AI Enablement](/services/ai-enablement/).

## Write down the first release before quoting it

The scope names supported inputs, actions, users and exceptions. It also states what still requires a person. We agree the success measure and an acceptance set before finalizing price and timing. Uncertain integrations or poor data can require a separate discovery step; the sprint begins when those dependencies are sufficiently understood.

## Review working behavior throughout the build

Implementation proceeds in reviewable increments. Your owner sees the workflow act on approved examples, including failures and handoffs, while there is still time to correct the direction. Authentication, data access, evaluation and operational logs belong in the release scope. A change to the agreed outcome is assessed openly for its effect on work and timing.

## Illustrative acceptance: draft a response, require approval

An example first release classifies an incoming request, retrieves an approved policy and prepares a draft. A staff member approves sending; ambiguous requests stay in review. Acceptance checks the supported request types, grounding, correct queue assignment and the fact that no message is sent without approval. This defines the delivery boundary without promising a particular productivity gain.

## Finish with an owner who can operate it

The handover includes code, configuration, evaluation cases, operating instructions and an agreed walkthrough. We demonstrate retries, a safe stop and how to handle exceptions. Ongoing changes or monitoring are separate decisions after acceptance. Broader product development remains with [AI Agents & Products](/services/artificial-intelligence/), while an engineer embedded for continuing delivery has a separate [engagement model](/services/embedded-ai-engineer/).

## Questions before you start

### Is the sprint always a fixed number of weeks?

No. We agree the delivery window after checking scope, access and dependencies. A short label is not a substitute for a credible implementation plan.

### Is the price fixed?

A fixed price can be agreed for the accepted scope. Discovery, third-party usage charges and later changes are identified separately in the proposal rather than assumed to be included.

### Do we receive a prototype or a production workflow?

The intended deliverable is the agreed production workflow and handover. If feasibility or access only supports a prototype, that is contracted explicitly instead of being presented as production delivery.

### What if AI adds little value to the task?

We recommend a simpler rule, integration or workflow change where it meets the outcome. The readiness assessment can also conclude that the proposed sprint should not proceed.

## Continue with the right scope

- [Choose and prepare AI use cases](/services/ai-enablement/)
- [Commission a broader AI product](/services/artificial-intelligence/)
- [Embed an engineer for ongoing delivery](/services/embedded-ai-engineer/)

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