Duration
1–4 weeks
AI Prototypes & Demos
MVPs, automations, and demos to test an idea's value before scaling — using tools like ChatGPT, OpenAI API, n8n, TypeScript, and AWS to prove what works with a tight scope.
Service at a glance
Audience
Product, innovation, operations, and technical leadership
Outcome
MVP or demo that proves value, limits, and effort before scale
Format
Prototype
Who it's for
- Product, innovation, and operations teams that need to test AI workflows before investing at scale.
- Technical leadership that needs evidence of value, limits, and effort.
- Business teams with an idea that may become a product, process, or automation.
What's included
- AI workflow prototypes
- Simple integrations with APIs and automations
- Demos for clients, leadership, and technical teams
- Quick tests before investing in scaling
- Documentation of what worked and what needs to change
How it works
- Understanding the idea and the test's success criteria.
- Building the prototype or demo with a tight scope.
- Testing with users, clients, or leadership.
- Documenting what worked and what needs to change.
What you get
- AI workflow prototype
- Simple integrations with APIs and automations
- Presentable demo for clients, leadership, and technical teams
- Documentation of value, limits, and effort before scale
Frequently asked questions
When does it make sense to build AI prototypes?
When the company still does not know whether an idea should become a product, process, or automation. A well-built prototype shows limits, risks, technical effort, and perceived value before a larger decision.
How long does a prototype take?
Between 1 and 4 weeks, depending on scope — the goal is to prove value, limits, and effort before a larger investment.
Contact
To talk about this service, write to oi@dorly.com.br.
Other services
AI Adoption Strategy
Assessment, use-case selection, and program design to move AI from slides into team routines — with change management, metrics, and a follow-up rhythm to course-correct.
Learning Paths & Workshops
Hands-on sessions for technical and non-technical audiences, with real work examples, guided exercises, and reusable materials — the goal is leaving the session using AI on concrete tasks.
Enablement Assets
Playbooks, guides, prompt templates, rubrics, and knowledge bases built from your company's real context, so teams keep using AI autonomously after the workshop.
Metrics & Continuous Improvement
Metrics for usage, confidence, quality, and time savings to know whether AI adoption is working — plus a follow-up rhythm to update content and course-correct.