Solution · AI & Machine Learning
Retrieval pipelines, agents, evaluations - production-grade ML
Production-grade applied ML - retrieval pipelines, agents, evaluation harnesses, monitoring. Less hype, more shipping.
What we deliver
Production-grade ML
Retrieval pipelines
Indexing, chunking, hybrid retrieval — tuned for your actual corpus, not a demo dataset.
LLM agents
Tool-using agents with guardrails. We design for the failure modes you have not hit yet.
Evaluation harnesses
Offline + online evals, regression sets, prompt-versioning. So you can ship changes confidently.
Monitoring & MLOps
Token spend, latency, hallucination rates. Dashboards your on-call can actually action.
Fine-tuning
When fine-tuning makes sense and when it does not. We will tell you which one yours is.
Inference infra
Self-hosted vs hosted, batching, caching, autoscaling. The cost-conscious decisions.
How we work
A process that ships and lasts
01 · DISCOVER
Discover
Stakeholder interviews, technical audit, success criteria.
02 · DESIGN
Design
Architecture, UX flows, prototyping — co-designed with you.
03 · BUILD
Build
Two-week sprints, demoable increments, embedded delivery.
04 · LAUNCH
Launch
Migration plans, performance baselines, knowledge transfer.
05 · SCALE
Scale
Ongoing partnership: feature velocity, reliability, observability.
Technologies
The stack we lean on
Frontend
Interfaces that stay fast under real traffic.
- TypeScript
Backend
Services that hold up when load spikes.
- Node.js
Related case studies
Builds in this discipline
Retail Companies
E-commerce Platform
3.7% conversion · Migrated a multi-vertical e-commerce operation across 50+ stores — fashion, sports, health & beauty, and tactical retail — from legacy Magento monolith to composable Adobe Commerce architecture with Hyvä storefront. Conversion lifted, page-load 3× faster, 99.98% uptime through peak-season flash sales. ERP, POS, and PIM fully integrated. Native iOS & Android shipped in parallel.
GraphQL · PHP · Alpine.js · Tailwind +5
News Portals
News Portal Platform
By introducing a custom CMS, modern SSR frontend, and shared mobile architecture, we enabled faster portal launches, reliable real-time publishing, and improved operational efficiency across 14+ digital platforms serving millions of readers monthly.
PHP · Python · Vue.js · Tailwind +2
Frequently asked
What clients usually ask first
How long does a typical engagement take?+
For mid-market clients, six to twelve months end-to-end is typical — including discovery, architecture, build, and cutover. We optimise for time-to-meaningful-launch rather than feature parity on day one.
Do you work as an embedded team or end-to-end build partner?+
Both. Most engagements start as a focused build and evolve into an embedded partnership. Some are explicitly capacity augmentation from day one. We are explicit about which mode an engagement is in.
Which technologies do you recommend, and when?+
Honestly, it depends. We will never recommend a stack we would struggle to operate ourselves, and we will tell you when the boring choice is better than the trendy one.
How do you protect SEO and conversion during cutover?+
Mapping 301 redirects, structured-data parity, performance baselines, phased traffic ramps, and a documented rollback. The first launch we ever did taught us all of this the hard way.
What does engagement cost typically look like?+
Engagements typically run between €100k and €500k for the initial build, with ongoing partnership work charged monthly. We will give you a scoped estimate after a one-hour technical conversation.
Get started
Ready to talk AI?
A 60-minute call with our engineering lead, no obligation. The form below pre-fills the Interest dropdown.