Orbit.
AI engineers who join your team.
Forward-deployed engineers who learn how you work and build the AI you've been meaning to build.
You keep ownership. We bring the capability.
From first call to embedded engineer. In weeks, not quarters.
What Orbit is
An engineer in your team.
Not a project on a slide.
Most AI projects fail on context, not capability. The model is rarely the problem—understanding your business, your systems and your constraints is. Orbit exists to close that gap: senior AI engineers who embed with your team, do the understanding work, and then build.
You do not hand over a specification and wait. You get an engineer who shows up in your standup, reads your code, asks hard questions, and builds working software with you.
Join your team
Orbit engineers embed in your repository, your tools, your standups and your review process. Not a portal, not a ticket queue, not a black box. They work like your team because, for the duration of the engagement, they are.
Learn how you work
Context comes before code. Your systems, your data, your constraints and your customers come first. An engineer who understands your business builds the right thing—not a generic demo.
Build what matters
The AI capability you have been meaning to build: the feature on your roadmap, the workflow your team dreads, the product idea you never had the capacity for. Scoped together, shipped together.
What we can build with you
The AI you meant
to build.
Every engagement is scoped to a real outcome. These are the shapes they usually take.
AI capability in your product
Add AI features to the product your customers already use: assistants, search, recommendations, document understanding, decision support—built to production standards inside your existing system.
Internal AI tools and automation
Automate the work your team does by hand: reporting, data preparation, customer operations, document-heavy workflows. Built with appropriate access and review controls.
A new AI product
Turn an AI idea into a working product. We help scope the smallest useful version, build it properly, and give your team the knowledge to keep going.
From first call to embedded
A short path.
A fast ramp.
We keep the start simple: understand the need, match the engineer, embed and learn, then build. You stay in control at every step.
- 01
Scoping call
A focused conversation about the role, your stack, your team and the outcome you need. Not a sales pitch—we come back with a clear picture of the fit and the work.
- 02
Engineer matching
We shortlist engineers from our bench with the right AI depth for your problem, share work samples and a written note on why each is a fit. You interview directly and decide.
- 03
Embed and learn
The engineer joins your team and learns how you work: systems, data, conventions and constraints. You see the understanding take shape before the build accelerates.
- 04
Build and ship
The engineer builds the AI capability with your team, in your process. Regular reviews, working software along the way, and decisions documented as they are made.
The human-agent partnership
Agents accelerate.
Your people decide.
Orbit engineers work alongside AI coding agents—the same way our own teams do. Agents handle bounded implementation work; people own the judgment. Responsibilities stay explicit at every stage.
Product & architecture
AgentsAI coding agents explore alternatives and prepare implementation options.
PeopleOrbit engineers and your people own trade-offs, system design and the final decisions.
Implementation
AgentsAgents scaffold features, write bounded changes and assist with refactoring.
PeopleOrbit engineers review diffs, integration behaviour, dependencies and maintainability.
Testing & debugging
AgentsAgents propose test cases, investigate failures and prepare fixes.
PeopleEngineers verify the tests are meaningful and check behaviour against requirements.
Release & operations
AgentsAgents help prepare documentation, deployment checks and change summaries.
PeoplePeople authorise releases and own incidents, access and production decisions.
Working with your team
It should feel like
your own hire.
The value of embedding is in the day-to-day: the context they absorb, the questions they ask, the reviews they pass through. We design the engagement so that works from week one.
Direct integration
Your Slack, your standups, your sprint planning, your code reviews. Communication happens in real time with your people, not through a middle layer.
Flexible scaling
Start with one engineer to prove the fit. Add a second, a specialist for a phase, or scale down when the work is done. No long lock-ins.
Backed by our bench
Every Orbit engineer is backed by our internal code review, architecture review and senior AI bench. When a piece of work needs a second opinion, it gets one.
Fit guarantee
If the fit is not right in the first two weeks, we replace the engineer at no cost. You are never stuck with the wrong person because of a contract.
Security and ownership
Inside your team.
Inside your boundaries.
An embedded engineer touches your code and your data, so the boundaries need to be explicit and enforceable—not goodwill.
Access controls that actually enforce access
Engineers receive only the access the work requires, scoped and reviewable. Permissions are agreed with you and removed when the engagement ends.
You own the code and the IP
Everything built during the engagement belongs to you. Repository access, IP ownership and confidentiality terms are explicit in the agreement—not assumed.
Data boundaries are agreed, not improvised
We agree what the engineer and their AI tooling may access, keep credentials outside code and prompts, and minimise sensitive data in development.
Specific requirements, not blanket claims
Deployment, audit logging, retention and regulatory needs are agreed during scoping and designed to with your stakeholders. We do not claim certifications we do not hold.
After the engagement
The knowledge
stays with you.
An Orbit engagement is designed to leave your team stronger, not dependent. Architecture notes, setup documentation, known limitations and a prioritised backlog are part of the work—and we walk your team through all of it.
Keep the context you built. Continue with your team, or extend the engagement to the next phase.
Before we start.
What exactly is Orbit?
Orbit is our forward-deployed AI engineering service. One or more AI engineers join your team for an engagement, learn how you work, and build the AI capability you have been planning. You keep ownership of the product, the roadmap and the code.
How is this different from hiring or outsourcing?
Hiring takes months and is hard to reverse; full outsourcing moves your context to the vendor. Orbit embeds senior AI engineers in your team and process, ramps in weeks, scales up or down, and keeps the knowledge on your side.
How quickly can an engineer start?
Typically within one to three weeks of the scoping call, depending on the specialization and your onboarding requirements. We confirm timing during scoping rather than promise a date upfront.
Do engineers work in our repo and tools?
Yes. They work in your repository, your CI, your infrastructure and your tools, under your review process. The point of embedding is that the work is visible and reviewable at every step.
Who owns the code?
You do. Work produced during the engagement belongs to you, with repository access, IP ownership and confidentiality terms made explicit in the agreement before we start.
Can you scale the engagement up or down?
Yes. Many engagements start with one engineer to prove the fit, then add engineers or specialists as the workload grows. Scaling down or ending the engagement has short notice periods.
What if the fit is not right?
If the fit is not right in the first two weeks, we replace the engineer at no cost. If expectations change later, we work with you to transition to a better match quickly.
How is pricing decided?
We scope the engagement—the outcome, the specialization and the expected duration—then agree the price and approach. Billing is monthly with no long lock-ins, and scope changes are discussed before they become extra work.
Let's build
What have you been
meaning to build?
Tell us about the AI capability you want, the team it would join and the outcome it should change. We'll help you judge the fit and agree a practical way to start.