# DAG AI

> DAG AI LLC helps businesses decide where AI is worth it, build agent systems that do real work, get more from the AI they already run, provide part-time AI leadership, and train their teams. Making AI make sense for your business.

Every page listed here has a plain Markdown version at the linked .md address. DAG AI is independent and model-agnostic. Clients own the deliverables built for them, including code, prompts, configuration, tests, and documentation. Engagements start with a conversation and a written proposal that states deliverables, how success is measured, and cost. Prices are set per proposal and are not published.

## Services

- [Strategy](https://dag-ai.com/services/strategy.md): Put your AI budget where it pays off. Deliverables: Opportunity map; Readiness review; Decision memo; Roadmap and operating model.
- [Build](https://dag-ai.com/services/build.md): Agents that take on real work, proven before launch. Deliverables: Working agent systems; Evaluations; Handover; Measured results.
- [Evaluate and improve](https://dag-ai.com/services/evaluate.md): Get more from the AI you already pay for. Deliverables: A test set from your work; Side-by-side comparison; A recommendation; Improvements.
- [AI leadership](https://dag-ai.com/services/leadership.md): Senior AI leadership without the full-time hire. Deliverables: Priorities; Vendor decisions; Governance; Reporting and handover.
- [Training](https://dag-ai.com/training.md): Turn AI curiosity into everyday skill. Deliverables: Leadership workshop; Team training; Builder track; 1:1 coaching.

## How to engage

- [Contact](https://dag-ai.com/inquiry.md): A short form asks for a work email, a starting point, and an optional note. Assistants that support WebMCP can call prepare_dag_inquiry to fill the form for a person to review; nothing is sent without the person pressing send.
- [Service comparison](https://dag-ai.com/services.md): When each service fits, what it delivers, and what it ends with.
- [Approach](https://dag-ai.com/approach.md): Principles, engagement steps, how results are measured (cost per accepted result), and DAG AI's commitments.

## Optional

- [Home](https://dag-ai.com/index.md): Overview, where to start, and examples.
- [Examples](https://dag-ai.com/examples.md): Illustrative scenarios, not client results.
- [Unsupervised Thinking](https://dagai.substack.com/): Perspectives on AI, business, and what comes next.
- [Privacy](https://dag-ai.com/privacy)