AI and software development for tech companies
We work with software companies that already know how to build: SaaS businesses adding AI to their product, scale-ups with more roadmap than engineers and IT service providers offering AI to their clients. We join your repositories, rituals and review process, and ship with coding agents under experienced review.
Industries in software and tech
The work, and where software fits.
Tech companies come to us for capacity and for specific experience: retrieval, evals and agent design for AI features, or engineers who can take on a product stream while the core team keeps the roadmap moving. They expect the work to meet their own engineering bar from the first pull request.
We work inside your GitHub, Linear or Jira and your CI, follow your conventions and hand over code your team is comfortable owning. Our engineers use coding agents for scaffolding, tests and migrations, and a person reviews every change before it merges.
How we improve software and tech.
AI features in the product
Search, assistants, document understanding and agent workflows built into your SaaS, with evals and cost controls from the first release.
Delivery capacity
A small team that takes on a product stream or an integration backlog, working in your codebase and your sprint cadence.
Agentic engineering
Engineers working with coding agents on tests, migrations and refactors, with review and CI gates on every change.
Evaluation and monitoring
Test sets, tracing and dashboards that show how model-powered features behave for real customers after each release.
White-label delivery
AI and software projects delivered under your brand for your clients, for MSPs, system integrators and consultancies.
Related work.
Further reading.
Agentic engineering: how to ship SaaS faster with coding agents
How senior engineers use coding agents to ship SaaS faster while keeping control of architecture, quality and security.
4 min read
LLM evals: how to test AI features before every release
A practical approach to LLM evals: build a test set from real cases, combine code checks with model grading, and block releases that regress.
5 min read
Build vs buy software: when custom development pays off
A practical way to decide between off-the-shelf software and custom development, covering total cost of ownership, integrations and risk.
5 min read
Common questions.
Yes, most of our work with tech companies runs that way. We join your repositories, standups and code review, follow your conventions and pair with your engineers so knowledge stays in your team.
You do, from the first commit. Work happens in your repositories under a contract that assigns IP to you, and we do not reuse your product code for other clients.
Agents take the repetitive parts, such as scaffolding, test generation and migrations, and an engineer reviews every change. Your CI, linting and test requirements apply to our pull requests exactly as they do to your own team's.
Yes. MSPs, system integrators and consultancies use us to deliver AI and software projects under their own name. Our partners page has the details.