A consulting team where the engineers also implement the work
Protogenies works on cloud platforms, DevOps, production AI and software systems. Our engineers stay involved from architecture through implementation and handover.
Advice is more useful when it survives implementation
Architecture decisions need to account for the real team, security requirements, operating workload, cost and the tooling that will remain after the engagement.
An architect who designs a landing zone may also write the Terraform modules. An AI engineer proposing an evaluation strategy also builds the harness that runs it. We keep architecture and delivery close together because the person making a decision should see what it takes to make that decision work in production.
Client repositories, cloud accounts, documentation and runbooks remain with the client. Our job is to leave behind a system the internal team understands and can continue operating after the engagement ends.
Engineering disciplines we staff
Team composition is agreed before work starts and should match the actual problem rather than a fixed consultancy template.
Cloud architects
Landing zones, network and identity design, multi-account governance and migration planning.
DevOps engineers
Pipelines, Kubernetes platforms, infrastructure as code and release engineering.
AI engineers
Retrieval systems, agent orchestration, evaluation harnesses and model operations.
Software engineers
Product and platform delivery across TypeScript, Python and .NET.
Solutions architects
Turning business constraints into technical roadmaps with documented trade-offs.
Technical consultants
Assessments, discovery and enablement for internal engineering teams.
Rules we use when a technical decision is contested
These principles guide implementation choices and make the trade-offs visible to the team that will own the result.
Reproducible by default
If it cannot be rebuilt from a repository, it is a liability. Infrastructure, pipelines and configuration are code.
Make the safe path the easy path
Guardrails work when the compliant option is also the fastest one. We design for adoption, not for mandate.
Measure before and after
Baseline what matters, change one thing, then check. We report the result even when it is unremarkable.
Design for the handover
Every engagement ends with your team able to operate what we built, with documentation to match.
Prefer deterministic solutions
Use a query, a rule or a workflow engine where one suffices; reserve models and complexity for problems that need them.
Say what we do not know
Unknowns are stated and investigated rather than papered over with confident language.
Three ways teams work with us
The right structure depends on whether the work is bounded, who owns the roadmap and how much continuity the programme needs.
Dedicated engineering team
A cross-functional squad working to your roadmap, embedded in your boards and review process.
Best for
Multi-quarter programmes such as a migration, platform build or product workstream where continuity matters more than a fixed scope.
Fixed-scope project
A defined outcome with agreed deliverables, acceptance criteria and a milestone plan.
Best for
Well-bounded work such as a landing zone, a CI/CD standardization effort, a migration wave or an AI evaluation harness.
Engineering extension
Individual specialists added to your existing team to cover a capability gap or delivery peak.
Best for
Teams that own the direction and need cloud, DevOps or AI depth alongside their own engineers.
Talk to the engineers who would do the work
Bring your current architecture, constraints and the problem you are trying to solve. We will tell you what we would change first, what it depends on, and where we would start.