# How we work: engagement models & approach

> Architecture Sprint, Build Squad or Embedded Experts. A measure-first approach: discover, design, build, scale and hand over.

Source: https://aibyos.com/how-we-work

How we work

# Start small. Prove value. _Scale_.

Three ways to engage, one measure-first approach, and no long lock-ins.

01 · Engagement models

## Three ways to engage.

2–3 weeks

### Architecture Sprint

A fixed-scope assessment of your idea or existing system.

-   Stakeholder & data workshops
-   Target architecture & risks
-   Prioritised roadmap with estimates

Fixed price

6–12 weeks

### Build Squad

A small senior team that takes one use case to production.

-   Architect + AI engineers
-   Weekly demos, eval dashboards
-   Hand-over, docs & runbooks

Milestone-based

Ongoing

### Embedded Experts

AI engineers or a fractional architect inside your team.

-   Flexible capacity
-   Works in your tools & rituals
-   Scale up or down monthly

Time & materials

Need something in between, or a different setup? Engagements are tailored to you. [Tell us what you need →](https://aibyos.com/contact)

02 · Starting point

## Find your starting point in 3 clicks.

Not sure which engagement fits? Answer three short questions and we'll suggest where to begin.

03 · Approach

## Measure first. Build second. Scale last.

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Step 01 · Discover

-   Stakeholder interviews & process walk-through
-   Data and systems audit
-   Success metrics and first eval set
-   Risk and compliance screening

#### Vendor-neutral

No reseller deals. We recommend what fits: open models, hosted APIs, or no AI at all.

#### Senior by default

The people you meet in the first call are the people doing the work.

#### You own everything

Code, prompts, models, evals and docs live in your repositories from day one.

04 · FAQ

## Common questions.

We don't have an AI strategy yet. Is it too early?

No, that's the best time. An Architecture Sprint helps you avoid expensive dead ends and pick the use cases worth building first.

Can you work with our existing cloud and security policies?

Yes. We design within your constraints, AWS, Azure or GCP, private networking, data residency in the EU, and your identity and access model.

Will our data be used to train third-party models?

Not unless you decide so. We default to setups where your data stays in your tenant and provider data-retention is disabled.

Do you only work with large enterprises?

No. We work with startups, scale-ups and enterprises. Engagements are sized to the problem, not the logo.

Do you work with both hosted APIs and open-source models?

Yes. We are vendor-neutral: Anthropic, OpenAI, Google, Mistral and AWS/Azure/GCP model services, as well as open models (Llama, Qwen, Mistral, Gemma) self-hosted in your cloud. We choose based on your evals, data constraints and cost.

Can you build an MCP server for our product or internal systems?

Yes. We design agent-friendly tools, implement remote MCP servers with OAuth and scopes, and add a registry and gateway if you run many of them.

Which data platform or cloud should we choose?

It depends on your existing cloud, team skills and workloads, see the comparison on our [Platforms & Cloud](https://aibyos.com/platforms) page. We are vendor-neutral and often run a short proof-of-concept on your real workloads before recommending one.

Can you migrate our AI workloads to another cloud provider?

Yes, for example Azure OpenAI to AWS Bedrock, Vertex AI to Azure, or APIs to self-hosted models. We add an abstraction layer, evaluate old and new side by side and cut over in phases with rollback.

How do contracts and billing work?

Fixed price for sprints, milestone-based for build projects, and monthly time & materials for embedded experts. B2B contracts across the EU and beyond.