Understand the context
Map the problem, existing systems, available data and the people who will use the solution.
Custom Enterprise AI Engineering
AI that understands
your systems. Not just your prompts.
Custom AI systems, backend engineering and integrations
for the way your business works.
01 / What we build
Engineering that fits.
Built around the systems you already rely on.
Enterprise AI Integration
Connect AI to your data, business systems and workflows, with the controls your environment needs.
Engineering Tools
Custom developer tools that work with repository context, related systems and existing engineering practices.
Custom AI Systems
Purpose-built agents, backend services and integrations shaped by your domain and operational requirements.
02 / Selected experience
Real context. Applied.
Anonymised examples from company projects.
CRM-integrated support AIProof of conceptConnecting support workflows with CRM data and internal knowledge.
The engineering challenge
Bring an AI assistant into an existing CRM environment, where customer context and internal knowledge are already part of the support team's work.
The approach
A proof of concept exploring context retrieval and AI assistance within the native support workflow.
Concept-stage work. This example does not imply a production deployment or measured business results.
Context-aware code reviewEngineering experienceCode review informed by changes, repository context and related systems.
The engineering challenge
A change can affect more than the lines in a diff. Useful review needs to account for the surrounding system and relationships across repositories.
The approach
AI-assisted review of individual commits and pull requests, connected to existing collaboration and development workflows.
Company project experience, presented without proprietary code or identifying details. Planned issue-tracker integration is not presented as a working capability.
Examples describe prior engineering experience, not products owned by PCCN.
03 / Working together
Start with the system.
Build what belongs.
Good integration starts with understanding your constraints. The model is one part of the solution.
Prove the approach
Define a bounded first step and agree how to evaluate it before committing to a wider build.
Engineer the integration
Build the backend, interfaces and controls needed to fit the solution into day-to-day work.
04 / Research & Lab
Curiosity, with
an engineering purpose.
Research is a long-term commitment behind the work. The focus is on how AI can use system context, reason over connected information and produce results that can be checked.
Context & retrievalSystem-aware reasoningEvaluation & validation
Research interests and exploratory work. Experimental ideas are kept distinct from delivered capabilities.
05 / About PCCN
Independent thinking.
Connected engineering.
PCCN is the engineering identity of PC Connect New Kft., based in Hungary and focused on working with UK and EU teams.
The work brings together backend development, enterprise integration and applied AI. The starting point is always a concrete problem in an existing system, with research informing the approach.
Based in Hungary · Working with UK & EU teams06 / Let's talk
What needs to
work together?
Tell us about your systems, the challenge and what a useful first step would look like.
No polished brief needed. A little context is enough.
Based in Hungary · Working with UK & EU teams