AI-assisted product lifecycles, automated testing and review, and the guardrails around both, our team turns the standard SDLC process into an AI-driven fast track.
Before changing anything, we measure what you have: cycle time, review latency, test coverage, defect escape rate, and where engineers actually lose their hours. You get a clear read on which stages of your lifecycle AI can move, which it cannot, and what the realistic gain is.
Coding assistants and agents produce very different results depending on how they are set up. We configure the tooling around your codebase and your product context, conventions, house rules, and pair with your engineers until AI-DLC becomes your daily habit.
Faster code generation is worthless if review becomes the bottleneck. We put AI to work on the parts of quality that scale badly: test generation, coverage gaps, automated review passes, documentation, and release notes.
The guardrails that let leadership say yes: which tools are approved, what code and data may leave your perimeter, how AI-authored changes are reviewed and attributed, and how licensing risk is handled. Paired with dashboards that show whether adoption is actually moving delivery, not just tool seat counts.
2.5×
uplift in video processing speed
Autodesk Flow Studio. An AI-driven production platform that enables the creation of Hollywood-level VFX and studio content on an indie budget.
75%
less manual document review
Document intelligence and AI workflows that keep clinical trials inspection-ready across 65,000+ research sites in 90+ countries.
$630M+
in annual revenue powered
The direct-to-consumer platform behind the world's best-known medical apparel brand. Search, product, and checkout clearing orders in 85 markets, for 3.1M+ clinicians.
450K
concurrent streams during the Summer Olympics
Germany's answer to Netflix. Our team architected the platform that carried the Summer Olympics live to hundreds of thousands of concurrent viewers, without missing a frame.
Nortik has been a reliable partner, helping deliver both complete software development projects and providing individual high-quality engineering talent for our partners.
Nortik’s Impact
Complete software development projects delivered end to end, alongside individual senior engineers placed with Netfork's partner teams.
Everything engineering leaders usually ask before rolling AI out to a whole team. Not here? Ask us directly.
It's your software development lifecycle rebuilt around AI assistance. Planning, coding, review, testing, documentation, release. AI takes the parts it's genuinely good at, and your engineers keep judgement over the rest.
The important bit is that it's a change to how the team works, not a licence you buy. Which is why most of the engagement goes into process, enablement, and measurement rather than tooling.
Usually quite a lot. Most teams stop at autocomplete. Nobody configures repo context or conventions, nobody sets up agentic workflows, automated review, or test generation, so the gains stay small and wildly uneven from one engineer to the next.
We start by measuring where your time actually goes, then push AI into the stages holding the team back instead of the one that happened to be easiest to adopt.
By treating AI output like any other contribution. Typed, tested, reviewed, covered by CI, with automated review passes tuned for the failure patterns assistants tend to produce.
We also track defect escape rate and change failure rate right through the rollout, so if quality slips, it shows up in a dashboard rather than in production.
Only if you pick a setup that allows it. We map your obligations first, then choose deployment modes to match. Enterprise agreements with no training on your data, private endpoints, or self-hosted models where the requirements are strict.
The approved tool list and the data boundaries get written down, so engineers know what's allowed without having to go and ask someone.
The baseline assessment takes two to three weeks. Test coverage, review turnaround, and documentation usually improve inside the first month of rollout.
Cycle time is slower to move. Give that one a quarter, because it depends on habits and process rather than tools.
We work with them. The point is a team that ships more with the people it already has, and the whole rollout is designed so your engineers end up owning it.
You get the playbooks, the configuration, and the dashboards, and we leave internal champions who can keep it going once we're gone.
Discover more ways we can help you scope, build, and scale AI in your business.
