Artificial Intelligence Solutions in Amsterdam

Most teams experiment with AI; few run it in production. We build autonomous AI agents that handle multi-step, cross-system workflows like document processing, triage, and data updates—keeping human oversight where it matters.

• Workflow Orchestration. We map your workflows, pinpoint where an agent adds real value, and establish clear human-in-the-loop oversight.
• Document Intelligence Processing. We extract, validate, and route invoices, orders, contracts, and forms across email, ERP, CRM, and CRM systems.
• Multilingual customer support agents. We build agents that handle routine requests in Dutch, English, and German and hand off to your team with full context.
• Internal operations agents. We automate back-office tasks in finance, HR, procurement, and logistics, connected to the tools your teams already use.
• Agentic Governance. We evaluate intent, tool calls, and retrieval independently to trace root causes. Hard guardrails and human approval gates prevent unvetted execution.

We audit your AI stack, map risk profiles, and build technical compliance safeguards for the EU AI Act, working alongside your legal team without slowing down shipping velocity.

• AI Asset Profiling. We catalogue the AI systems you build or use and run a preliminary assessment of the risk categories they may fall into.
• Transparency Implementation. We implement the technical safeguards for AI interaction notices, content tagging, and output attribution within your products.
• Technical documentation support. We produce detailed model cards, data lineage tracking, and system architecture specifications for your compliance framework.
• Engineering governance controls. We bake governance into your CI/CD pipeline via policy gates, access controls, automated security scans, and test suites.
• Readiness roadmap. We build a prioritized plan that ties upcoming regulatory milestones to concrete engineering tasks.

We build secure, domain-specific AI assistants and search pipelines on your proprietary data, deployed on-prem, in a private cloud, or in EU-hosted infrastructure for absolute data sovereignty.

• Infrastructure Selection. We evaluate hosting architectures alongside open-source and commercial models to match your specific security, performance, and budget requirements.
• Enterprise Hybrid RAG. We optimize retrieval accuracy using hybrid search, query rewriting, reranking, and RBAC-enforced filtering. For complex setups, agentic RAG routes and verifies queries across multiple sources.
• Private System Integration. We deploy models in your chosen environment and integrate them with SSO, existing applications, and APIs.
• Enterprise Knowledge Curation. We clean, structure, and index your internal knowledge assets to ensure search accuracy and retrieval precision as your data expands.
• Inference Optimization. We implement intelligent prompt routing, model quantization, caching, and auto-scaling to keep cloud LLM inference costs predictable and lean at scale.

We engineer production AI models for real-time fraud prevention, risk scoring, and KYC automation—built for full explainability, audit trails, and regulatory compliance.

• Real-Time Transaction Monitoring. We build models that flag suspicious patterns in real time, with explanations analysts can act on.
• Onboarding Automation. We automate document checks, data extraction, and case preparation to speed up customer verification.
• AML case support. We build AI tools that prioritize alerts, summarize case histories, and reduce investigators’ manual workload.
• Predictive Model Explainability. We deploy predictive risk models complete with model explainability (SHAP/LIME), comprehensive audit logging, and human-in-the-loop review workflows.
• Financial document intelligence. We automate the processing of statements, reports, and regulatory filings.

We unblock stalled AI initiatives, resolve data pipeline issues, and transition viable POCs into hardened, fully monitored production systems with measurable ROI.

• AI portfolio review. We assess your current pilots and ideas by business impact, feasibility, and readiness, then recommend what to scale, fix, or stop.
• Data Pipeline Audit. We evaluate data quality, access, and pipelines, and fix the issues that block production use.
• Production MLOps Evaluation. We set up automated deployment pipelines, model registry, and evaluation benchmarks—testing latency, throughput, cost, and output accuracy before scaling.
• Performance Metrics Tracking. We define success metrics before scaling, then track them so AI investment is tied to real outcomes.
• Technical Enablement Handover. We provide documentation, training, and knowledge transfer so your team can run and evolve the solution independently.