Embedded
A Forward-Deployed AI Engineer,Working Inside Your Team
Embedded puts an AI engineer from our team inside yours, working between your engineers and RevOps to turn an AI roadmap into workflows that ship in your own stack. It runs as a monthly program scoped on a call, for teams that need hands-on build capacity and judgement more than another strategy deck.
Embedded at a glance
- Who runs it
- Our engineer, in your team
- Where it runs
- Your stack and repos
- What you own
- Everything we ship
- What it costs
- Talk to usScoped on a call
01Who it's for
Who Embedded Is For
Embedded fits teams with real AI ambitions, a stack too specific for a packaged service, and engineers who would rather build alongside someone than hand the work off.
Embedded is a good fit if
- You have an AI roadmap and need someone to build it, not another deck about it
- Your engineers and RevOps team need a bridge between what the business wants and what gets built
- Your stack is specific enough that a packaged service would not fit it
- You want your own team to learn to build and run AI workflows as the work happens
Another lane fits better if
You want the GTM work done for you on top of HubSpot
Look at ManagedYou want a defined AI build with a fixed fee and a handover
Look at OwnedYou need HubSpot and RevOps help more than AI engineering
Look at Advisory
02What you get
What Embedded Looks Like
Embedded is hands-on work inside your systems and your team's rhythm, measured by what ships rather than by meetings attended.
Hands-on build work
We build agents, integrations and workflows in your stack alongside your engineers, and ship them to production rather than a demo.
A bridge between teams
Our engineer works between engineering and RevOps, turning what the business needs into systems your engineers are comfortable maintaining.
An AI roadmap that ships
The roadmap is ranked by business value and kept short enough that every item on it has a build date, not just a slide.
Your team trained as it goes
Your people learn by building with our engineer, so the capability stays inside the company when the program ends.
Governance built in
Permissions, review steps and human approval on outbound actions are part of every build, not added after something goes wrong.
Claude set up properly
Where Claude is not yet in place, the program starts by implementing it with the workspace, permissions and governance your security team can sign off.
AI leadership
Need AI Leadership as Well as Build Capacity?
Our fractional Chief AI Officer page covers the strategy, governance and vendor decisions that sit alongside hands-on build work, and how the two fit together in one engagement.
03How it works
How Embedded Works
Embedded starts with a conversation about your roadmap and becomes a monthly program with a clear, short list of what ships next.
- 1
Scope call
A 30-minute call to understand your roadmap, your stack and your team, and to decide honestly whether Embedded is the right lane.
- 2
Roadmap
We agree a short, ranked roadmap and the first builds, so the program starts with work that pays for itself early.
- 3
Build in production
Our engineer builds inside your systems alongside your engineers and RevOps team, shipping to production rather than to a sandbox.
- 4
Hand over as you go
Every build is documented and owned by someone on your team from the start, so nothing depends on us to keep running.
04What it costs
What Embedded Costs
Embedded is a monthly program priced to the scope of your roadmap, so we talk it through on a call before we put a number in writing.
Every Embedded engagement includes
- A ranked AI roadmap agreed with your team
- Build work shipped to production in your stack
- Documentation and training as each build ships
- Human approval built into every workflow
Monthly program
Talk to us
Hands-on AI engineering inside your team, priced to your roadmap and agreed in writing before the program starts.
05Questions
Questions Buyers Ask About Embedded
What is a forward-deployed AI engineer?
An engineer who works inside your team and your systems rather than from an agency queue, building AI workflows in production and staying close enough to the business to know which ones matter. Our engineer works that way with your engineers and RevOps team, on your stack and your priorities.
How is Embedded different from a fractional Chief AI Officer?
A fractional Chief AI Officer owns AI strategy and governance at the leadership table, while Embedded is hands-on build work inside the team. Many companies need both, and the program can include roadmap and governance work, but Embedded is measured by what ships rather than by the strategy itself.
What does Embedded cost?
Embedded is a monthly program priced to the scope of your roadmap, which is why we talk it through on a short call before putting a number in writing. You get a written scope and a monthly price before anything starts.
Do we need engineers on our side?
It helps, because Embedded works best alongside an engineering or RevOps team that will own the systems over time. If you do not have engineers, Owned or Managed is usually the better fit, and we will say so on the first call.
Other Ways to Work With Us
Same team and the same Claude expertise, packaged for a different answer to who runs the system and who owns it.
Talk Through Your AI Roadmap on a 30-Minute Call
Bring the roadmap, or the problem you want a roadmap for, and we will tell you honestly whether Embedded is the right lane and what the first builds would be.