Lasse Hyldahl Jensen

I joined Avido as its Founding Engineer and third co-founder and took the product from a vibe-coded Next.js MVP to something banks run in production. I own it end to end, from the Next.js frontend and Python and Node.js backends down to the infrastructure on Azure Kubernetes, with Pulumi for infrastructure as code, Flux for GitOps, GitHub Actions for CI, and the Grafana LGTM stack for logs, metrics and traces. As a founder I have been on-call for all of it.

The product helps banks and financial firms test, monitor and evaluate the AI they put in front of customers, and I built most of it, from the data pipelines that turn a customer’s raw data into test sets to the conversational AI Core in Python and FastAPI. Keeping it dependable under real load meant work on rate limiting, retries and caching, with retrieval over Postgres and pgvector.

To get through one bank’s procurement we ran the same container images inside their own private cloud, whether we host the platform or they do. Security is held to the standard banks expect, with passwordless Azure Workload Identity and zero-trust networking between services, and our SOC 2 penetration test came back with zero findings. Avido is used by companies like Skatteguiden, Sydbank, Kamina, and ABN AMRO.

I built backend microservices in Go, with gRPC for internal service-to-service communication and GraphQL and REST APIs for the internal frontend and the customer mobile and web apps.

As an intern I built an anti-corruption layer in front of one of Lunar’s partner integrations. API calls had been forwarded straight to the partner, which added latency and left little control over response times; the layer fixed that and let us move to event sourcing across the affected microservices. Those endpoints were hit every time one of Lunar’s million users opened the app, and we shipped changes to them continuously, sometimes several times a day.

Full-time, I took over Lunar’s card management system. It dated back to the 2019 banking licence and the rushed 2020 launch, so it carried real technical debt. I reworked the architecture that was holding back scalability and built an integration with Nets, Lunar’s card issuer, to keep the two systems in sync and reconcile any discrepancies automatically. I was on-call for the system and handled the production incidents that came with running it at that scale.

In early 2024, two colleagues and I started Lunar’s AI Colony, a small team set up to find out how far generative AI could go across the bank’s products and internal work.

We launched a customer-facing assistant and built a full support system on top. It connects to Intercom through its REST API and answers customers in seconds, where a reply used to take up to three days. It resolves 85% of Lunar’s support cases today, and together with the assistant it handles over 40,000 customer interactions a month, all on Go microservices with retrieval over PostgreSQL and pgvector.

I also built Lunar’s internal GenAI platform, so other teams could reach LLMs through our APIs and build their own RAG pipelines without standing up the plumbing themselves.

For my Bachelor’s project, I collaborated with IBM Denmark and Smukfest to develop the backend for Smukfest’s new mobile app. The backend was designed for scalability and maintainability, and it integrates various Content Management Systems (CMS) while enabling push notifications to all devices via Expo.

The app successfully launched for Smukfest 2023, supporting over 50,000 attendees, and was built to keep running even when parts of the backend failed.