# AI Product Development — Alector Lab Engineering Specification

Canonical URL: https://alectorlab.com/services/ai-product-development
Raw Markdown: https://alectorlab.com/services/ai-product-development/raw
Last Updated: 2026-09-10
Provider: Alector Lab – Enabling Technologies Ltd (https://alectorlab.com)
Contact: alectorlab@gmail.com

## Summary
From a focused AI feature to a complete product, we connect models, data, infrastructure, interfaces and evaluation.

## Engineering Overview
An AI product engagement connects a user problem to a working application—not just a model endpoint. We scope the interface, data flow, integrations and operational ownership together so the first release can be evaluated as a complete workflow.

### Illustrative Scope
For a support product, a first release could draft replies from approved knowledge, show the supporting passages and ask an operator to approve the response. The initial scope would exclude autonomous refunds or account changes. Those actions need separate permissions, tests and acceptance criteria.

## Target Audience
- Product teams moving beyond a prototype
- Companies adding AI to an existing platform
- Founders building an AI-native product

## Supported Workflows
- Product discovery and feasibility
- AI-native web and mobile applications
- Model and data integration
- Production rollout and managed improvement

## Required Inputs
- Target workflow and users
- Representative data
- Existing product and API context
- Security and deployment constraints

## Engineering Deliverables & Outputs
- Validated product scope
- Production application and integrations
- Evaluation and observability suite
- Handover and operating documentation

## Delivery Stages
1. Discover
2. Validate with representative data
3. Engineer the complete system
4. Deploy in stages
5. Operate and improve

## Acceptance Criteria
Agree task completion criteria, an error taxonomy and a representative test set. Handover includes application code, deployment instructions and ownership of monitoring. Infrastructure charges, model usage and ongoing support are scoped explicitly rather than assumed included.

## Operating Boundaries
- **Integrations:** Identify the existing identity provider, application APIs and data owners. Agree versioned interfaces and failure responses before integrating the model into the product.
- **Deployment:** Choose a hosted, private-cloud or on-premise boundary around data and operational requirements. Include model usage, infrastructure and support ownership in scope.
- **Human Review & Governance:** Define what users can verify, correct or escalate. Gate releases on task quality, access-control tests and recovery behaviour rather than a successful demo.

## Operating Limitations & Safety Boundaries
- Model capability does not replace product discovery
- Acceptance criteria require representative evaluation data
- Timelines depend on integration and governance scope

## Common Technical Question
**Q: Can we start with an existing prototype?**
A: Yes. Start with a technical review of the prototype, user feedback and data dependencies. Keep useful components; identify missing security, evaluation and operational work before agreeing what can be reused.