Stockholm-based climate tech scale-up Nordgreen needed to scale their carbon tracking platform from 100,000 to 2M enterprise users — fast. Hiring in Stockholm's competitive engineering market would take 9 months. Zyrova deployed 8 senior engineers within 2 weeks who delivered the platform architecture that made the scale possible.
Nordgreen Climate Technologies operates a carbon footprint tracking and offset platform for European enterprises — a market that exploded following the EU's Corporate Sustainability Reporting Directive (CSRD) mandate in 2024. After closing a Series B round in Q1 2024, they had capital, pipeline, and ambition. What they did not have was engineering capacity: their 12-person team could not scale the platform architecture fast enough to onboard enterprise clients at the pace sales was closing them.
Stockholm's engineering talent market was at full employment. Nordgreen's Head of Engineering estimated a 7–9 month timeline to hire the 8 additional senior engineers they needed through conventional recruitment. With enterprise clients waiting to onboard and a CSRD reporting deadline creating a hard market window, a 9-month hiring delay was commercially catastrophic. They needed engineers who were genuinely senior, could understand their TypeScript/Python codebase on day two, and could operate independently within their existing Agile process.
Zyrova treated this as a mission-critical engineering deployment, not a staffing transaction.
Nordgreen's Head of Engineering spent 6 hours defining exact profiles: TypeScript/Python full-stack, distributed systems experience, previous scale-up context. We surfaced 12 candidates in 72 hours — 8 were hired after first-round interviews.
Full codebase access, dev environment setup, Slack/Jira integration, and first PR submitted within 72 hours of contract start. Nordgreen's existing process onboarded engineers in 3 weeks.
The Zyrova team led the migration from a monolithic Django API to a microservices architecture on Kubernetes — enabling horizontal scaling that took the platform from 100K to 2M user capacity.
Two ML engineers built Nordgreen's AI carbon intensity forecasting model — predicting grid carbon intensity 48 hours forward to optimize when enterprise clients should run energy-intensive workloads.
Built automated CSRD-compliant reporting exports — transforming what was a 4-day manual process per enterprise client into a one-click export, enabling 10x client onboarding velocity.
Structured knowledge transfer programme ensuring all architectural decisions, documentation, and critical institutional knowledge remained with Nordgreen's permanent team throughout.
We needed people who could read our codebase on Monday and be in production on Wednesday. That is not a reasonable expectation of most augmentation providers. Every Zyrova engineer we hired hit it. Seven months later, three of them are now permanent Nordgreen employees — which is the highest compliment I can give.
Lars Eriksson Head of Engineering · Nordgreen Climate Technologies