Experienced practitioners stay involved
The people who shape the recommendation remain involved in the code, reviews, and handover. You know who is accountable for the work.
Your Java and Spring systems already carry critical business logic. We design, build, and operate AI agents with Spring AI and Embabel, using typed actions, evaluations, observability, and explicit operational safeguards.
Choose the challenge that matters most right now.
Build testable, observable agents that integrate with your JVM estate and are ready for your operations team.
Find the real constraints in two weeks, then modernise incrementally where the evidence supports it—without a big-bang rewrite.
Turn good practices into everyday habits through embedded coaching and hands-on training grounded in your codebase.
Agentic AI engineering is our focus. Architecture reviews, modernisation, coaching, and custom delivery provide the foundations and engineering capability needed to run consequential systems in production. Experienced practitioners remain involved from discovery through delivery and handover.
We take your AI pilot towards production. Agents with Spring AI and Embabel, grounded in your data, with goal-oriented planning, evaluation harnesses, guardrails, cost control, and observability integrated with your operating model.
Fixed-scope discovery and first production agent.
An independent, senior read on your system in two weeks. Where the material risk sits, what to fix first, what to leave alone – delivered as a written report and a prioritised roadmap your team can act on immediately.
Fixed scope, fixed price, two-week turnaround.
Get your delivery speed back without a big-bang rewrite. Incremental migration of legacy Java systems to a well-bounded modular monolith with Spring Modulith, planned to preserve a releasable path and minimise disruption to feature work.
Fixed-scope discovery first, then delivery in increments.
Embedded technical coaching for sustained changes in day-to-day practice. Pairing, code review, testing discipline, and AI-assisted workflows are applied in your codebase and on current tickets.
Typically one to two days per week, three months minimum.
When you need the system built, not just advised on. We design and ship Java and Spring applications, including agentic workflows where justified, with explicit operational responsibilities and handover.
Scoped per engagement – fixed-price discovery first, then delivery in increments.
Wondering if you are ready for AI agents? Take our free AI readiness checklist – 35 questions across use cases, data, architecture, skills, governance, security, and cost. No sign-up.
Anonymised outcomes from recent engagements. Results depend on each organisation’s starting point, constraints, and participation.
Deployment cadence moved from quarterly release trains to daily production deploys, with automated quality gates replacing the manual sign-off ritual.
Delivery throughput increased after an embedded coaching engagement covering testing discipline, pairing, and AI-assisted development workflows.
An LLM proof of concept that could not be tested or explained became an agent using goal-oriented planning, with evaluation harnesses, guardrails, and production observability.
Hands-on courses for Java and Spring teams, taught by practitioners who use this stack in delivery and public teaching, including Devoxx and Spring I/O. On-site in Zürich, at your office anywhere in Europe, or fully remote – in English or German. See the full training curriculum.
In-house, up to 12 participants. Content tailored to your codebase.
Build intelligent applications and reliable agents: LLM integration, RAG pipelines, MCP, function calling, and agent workflows that select actions from goals and conditions.
Build a practical foundation in the Spring Framework: IoC container, dependency injection, AOP, data access, and Spring MVC. Includes Spring Certified Professional exam preparation.
Design maintainable modular monoliths: verify boundaries with architecture tests, decouple with domain events, and generate living architecture documentation.
Secure your Spring applications with authentication, authorisation, OAuth2, JWT, and method-level security.
Tune startup time, reduce memory footprint, and assess GraalVM native images against your production requirements.
Architecture, testing, refactoring, code review, or AI-assisted development – designed around your product, your stack, and your real code.
Practical collaboration, modern engineering, and outcomes your team can sustain without us.
The people who shape the recommendation remain involved in the code, reviews, and handover. You know who is accountable for the work.
Goal-oriented planning makes the selected actions and conditions inspectable. LLM-backed steps remain non-deterministic, so we evaluate, validate, observe, and constrain them.
Tests, observability, and maintainable code shorten feedback loops and make failures easier to diagnose.
We pair, review, and coach throughout, then reduce our involvement as your team takes ownership of the result.
If your problem is not one we should solve, we will tell you and, where we can, recommend a more suitable direction or specialist.
Book 30 minutes. Tell us what you are building, the decision in front of you, and what is getting in the way. You will speak with a practitioner who would remain involved if we proceed.
Prefer email? We reply personally within one business day – and if we are not the right fit, we will say so.