Rebuild a bottleneck
Replace or split the part of the system that slows every release, with a migration plan that keeps the product serving customers throughout.
Who we work with
Grow the product without breaking it.
Once a product works, the next challenge is different: more users, more data and a roadmap that outgrows the team that built it. We add senior delivery capacity and judgment.
Typical stageSeries A to Series C
Team size20 to 200 people
Common first projectPlatform or AI feature
EngagementDedicated team
Overview
The middle is the hard part.
A scale-up is rarely short of ideas. The hard part is choosing which ones the current team can carry, then delivering them without letting the existing product slip. Feature requests arrive faster than engineering capacity, and the systems that worked when the company was small start to show strain as usage grows.
We work alongside your team rather than around it. That means shared rituals, shared repositories and a clear split of ownership. Our engineers take whole features from design to production, document decisions and help your team carry the work after we leave. When AI is part of the answer, we test it against your real traffic before it ships.
Capacity without a long ramp
Senior engineers join an existing codebase, learn your conventions and work within your review process from the start.
Features owned end to end
We take a problem from design through build, testing and release, so nobody has to stitch the work together at the end.
A steady delivery rhythm
Short cycles, regular demos and visible progress keep the roadmap honest while the rest of the company keeps moving.
AI added with evidence
We run new models against your own examples and compare them with the current process before we change anything your customers see.
Lessons your team keeps
Documentation, tests and working sessions leave your engineers able to maintain and extend what we build together.
Decisions you can audit
Architecture notes and trade-off records explain why a system works the way it does, which matters as the team and the codebase change.
Use cases
Where scale-ups get stuck
These are the requests we hear most often from teams past their first growth stage.
Second product line
Build a new offering beside the existing product, reusing the parts that fit and separating the parts that would slow both down.
AI in a live workflow
Add assistance or automation to a process your team already runs, with pilot groups, measured quality and a way back if it underperforms.
Delivery reset
When releases keep slipping, we review the code, the process and the estimates, then work with your leads on a plan everyone can follow.
How we work
How we slot into your team.
Align
We start with your roadmap, architecture and delivery process, then agree which work we own and how decisions get made.
Plan
We break the first stream of work into small releases, name the dependencies and set the measures that tell us it is working.
Deliver
We build alongside your engineers in short cycles, with joint reviews and demos that keep stakeholders close to the work.
Hand over
We document what changed, train the people who will own it and stay available while the new routine settles.
FAQ
Common questions.
How do you work with our existing engineering team?
We join your rituals, repositories and review process, and we agree on ownership before work starts. The aim is one team, not two teams reporting to different people.
Can you take over a project another vendor started?
Often, yes. We begin with a short review of the code and documentation, then tell you what can be kept and what should be rewritten.
What happens to knowledge when you leave?
We document decisions, write tests and pair with your engineers throughout, so the system does not depend on any one outside person.
Do you only do AI work?
No. Much of our work is ordinary product engineering. AI is one part of the toolkit, used where it solves a real problem.
How do you measure success?
We agree on measures before the work starts, such as release frequency, defect rates or the quality of an AI workflow, and review them at each demo.
Next step
Start the conversation
Roadmap outpacing your team?
Send us the short version of what you are trying to deliver and where it hurts. We will come back with a straight assessment and a way to start.