Service lines, assigned to your roadmap.
Azendo delivers from Chiang Mai, Thailand. You choose the disciplines your roadmap is missing; we assign specialists at full capacity, put a service delivery manager on the account, and deliver inside your repositories, your tools and your sprint rhythm. If the discipline you need is not already on our team, we go and find the right person for your project.
Choose a discipline, or describe the outcome
Most partners start with one discipline and add a second within the first year. A backlog problem turns out to be a release problem, where QA outsourcing does more than another engineer would, or a platform that needed attention before the next enterprise deal. Capacity moves at the monthly cycle rather than through a new contract, so adding a second line to an existing agreement is a conversation, not a procurement round.
Every line below runs the same way. Specialists assigned to one roadmap, working inside your repositories and sprint rhythm, with a service delivery manager accountable for what ships and a committed monthly capacity written into the agreement. If the discipline you need is not listed, we source the specialist and build the line around them.
Software development and product engineering
Product and interface work that moves the roadmap
Backend, frontend and full-stack software engineers working features, integrations and platform debt inside your existing codebase.
iOS, Android and cross-platform software engineers owning release cycles, store submissions and the long tail of device support.
Product designers running flows, interface work and design system maintenance in the same sprint rhythm as your software engineers.
QA, cloud and platform engineering
The work that keeps releases boring
Test strategy, automated suites and regression coverage owned by a specialist instead of squeezed in between features.
Pipelines, infrastructure as code, observability and cost control for teams whose platform has outgrown side-of-desk attention.
Pipelines, warehouse modelling and data quality work so the reporting layer stops being a monthly argument.
AI engineering and data services
From experiment to production-ready work
LLM features built into your software properly: retrieval, evaluation, guardrails and the unglamorous plumbing around them.
Agentic workflows and internal automation that remove manual steps from operations, support and back office processes.
Deployment, monitoring and retraining infrastructure so models keep working after the notebook is closed.
Analysis, model development, fine-tuning and evaluation, tied to a decision someone in your business actually has to make.
A common shape: two software engineers, one QA engineer and part of a DevOps specialist's capacity, under one agreement and one service delivery manager.
Need a discipline we have not listed?
A niche framework, a specific ERP, Salesforce, game development, security engineering, technical writing — tell us the profile and we will search for the right specialist for your project, assess them through our own process, and build the discipline around them.
Expect a longer start than an established service line, no additional cost for the search, and an honest answer if we do not think we can deliver it well.
Tell us the profileThey become part of the Azendo team and are assigned to your project under the same agreement as every other discipline.
Start from the symptom, not the job title
Usually development capacity, sometimes QA — if a third of your engineering time goes into manual regression, adding developers only moves the bottleneck.
Software development →QA engineering and test automation, often paired with DevOps to get the suite running in the pipeline rather than on someone’s laptop.
QA and test automation →Cloud and DevOps capacity to get access control, logging and infrastructure evidence into a state a questionnaire can survive.
Cloud and DevOps →Data engineering first — pipelines and modelling — before any data science work has a foundation worth standing on.
Data engineering →AI engineering for the product surface, MLOps for everything that keeps it running and measurable once real users arrive.
AI engineering →Continuity rather than capacity. An assigned team that stays with one roadmap for years is a different arrangement from a pool of contractors, and the difference shows at month eight rather than month one.
Dedicated development team →Then start with the conversation, not the service line. Thirty minutes, and you get a written view of what we would deliver and what it takes.
Talk to us →
Common questions about our service lines
Can we combine several disciplines in one agreement?
Yes, and most partners do. One agreement covers the whole team regardless of how many disciplines it spans, with one monthly fee, one minimum capacity in hours and one service delivery manager across all of it.
What if you do not have the discipline we need?
We build it. You describe the profile, we search our network and the local market, assess the people we find against our own technical and communication standard, and you meet them before anything is committed. They join the Azendo team and are assigned to your project on the same terms as any other discipline. Expect a few extra weeks before delivery starts, at no additional cost.
Is there a minimum capacity?
Yes. Capacity is committed in full to one project, so agreements start at one discipline’s monthly capacity. We do not split attention across partners and we do not take part-time arrangements — delivery is only good when the team knows your product properly.
Can we change the team composition later?
Capacity and composition are reviewed monthly. Roadmaps move — a team that needed two engineers and a designer in the first year often needs QA and DevOps in the second. Changes go through your service delivery manager and take effect with the notice period in the agreement.