- Short answer: We help European organisations pilot and scale AI and automation that deliver measurable ROI — focusing on practical use cases, robust validation and production readiness.
Our AI & automation work is led by Product Owner / Senior Business Analyst professionals with experience in AI trading platforms and HR chatbots, combining product thinking, data awareness and hands-on delivery.
What we do
- Process automation: Identify tasks for automation, build flows and integrate with existing systems (e.g. CRM, ticketing, HR systems).
- AI chatbots & virtual agents: Design and deliver conversational assistants, support and internal processes.
- Document understanding: Extract structured data from invoices, contracts and forms with human validation loops to keep accuracy and compliance high.
- Predictive analytics & ML: Build lightweight models focused on measurable business KPIs (conversion, throughput, risk) and explainability instead of black-box experiments.
- AI product consulting: Support product teams building AI-centric platforms with backlog design, user journeys and experiment frameworks.
Whether you are starting with a single workflow or building a full AI-enabled product, we focus on value, feasibility and risk in that order.
How we deliver
- Discovery & value assessment: Identify quick wins and define success metrics. We look at processes, data readiness, constraints (compliance, security) and business priorities.
- Pilot & validate: Small-scale proof-of-concept with clear acceptance tests. We document assumptions, run experiments, and make it easy to compare AI vs non-AI baselines.
- Scale & embed: Move from prototype to production with monitoring, retraining plans and clear ownership. We align with your IT and security teams early to avoid later blockers.
This approach has been used for AI webapps, automation of HR activities and analytical backends, where the cost of failure is real and governance matters.
Example use cases
- AI trading support: Supporting a web-based trading platform by structuring product backlog, aligning AI features with user journeys, and setting up clear acceptance criteria for ML outputs.
- HR automation & chatbots: Designing an AI chatbot to automate HR FAQs, leave processes and basic employee requests, integrated with HR systems and escalation workflows.
- Back-office workflow automation: Mapping manual approval chains, implementing automated routing and notifications, and tracking cycle time improvements.
- Document routing & classification: Using AI models to pre-classify incoming requests or documents, keeping a human in the loop where risk is higher.
Each of these scenarios was handled with clear metrics (time saved, error rate reduction, user satisfaction) and defined guardrails.
AI Implementation Success Metrics
HR Chatbot for Large Enterprise: Developed and implemented an AI-powered HR chatbot, automating responses to 60% of common employee queries, leading to a 25% reduction in HR support tickets and improved employee satisfaction.
Trading Platform Automation: Integrated machine learning models into a trading platform to automate risk assessment and optimize trade execution, resulting in a 15% increase in trading efficiency and reduced operational risk.
Industries & environments
We are comfortable bringing AI & automation into environments where governance and traceability matter:
- EU and public-sector organisations that need to respect data protection and regulatory constraints.
- Certification & exam bodies that want automation without compromising exam integrity or customer trust.
- Corporate functions such as HR and operations that need practical tools, not AI hype.
- Product and startup teams building AI-first features and looking for a delivery-minded Product Owner / BA profile.
Risk & governance
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We design AI systems with clear guardrails: ethical reviews, data lineage, and human oversight — balancing speed and safety. We document where AI is used, who reviews outputs,
and which decisions must stay fully human-controlled.
For regulated or sensitive environments, we help you define acceptable use policies, logging and audit trails and fallback paths if models or APIs fail.
AI & automation FAQ
How long does a typical pilot take?
- Pilots are usually 4–8 weeks depending on data readiness and scope; they focus on proving measurable value quickly and de-risking a later scale-up.
Do you build custom models or use off-the-shelf?
- We choose the approach that fits the business case — often combining pre-trained models with light customisation and domain adaptation. Where possible, we start with off-the-shelf and move to custom only if needed.
Can you help us choose AI vendors and platforms?
- Yes. We support you with vendor and platform evaluation, focusing on integration complexity, total cost of ownership, governance features and your internal capabilities.
Do you also handle business analysis and project management?
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Yes. AI & automation initiatives benefit from strong business analysis and project management.
We can cover the full lifecycle instead of dropping a proof-of-concept and leaving.
In the call we clarify your use cases, data constraints and success metrics — then propose a realistic AI roadmap instead of a buzzword list.