AI & Generative AI Solutions
From AI agents to copilots and intelligent automation – we help you put the latest AI to work safely, securely and with measurable ROI.
Practical AI
AI that delivers real business value
AI has moved from experiments to everyday business tools. We help you identify the use cases with the highest return, build them on proven platforms, connect them securely to your data and systems, and run them responsibly in production – with clear metrics from day one.
- Use-case discovery and AI readiness assessment
- Rapid proofs of concept in weeks, not months
- Production-grade engineering, security and monitoring
- Responsible-AI governance built in
What we build
Our AI capabilities
Current, proven techniques – applied to your processes and data.
Agentic AI
AI agents & agentic workflows
Autonomous and human-in-the-loop agents that plan, use tools and complete multi-step tasks – from ticket triage to report generation – with approvals and audit trails.
Knowledge
RAG & enterprise search
Retrieval-augmented generation over your documents, wikis and databases, using vector search and hybrid ranking, so answers are grounded in your own data with citations.
Integration
MCP & tool integrations
Model Context Protocol (MCP) servers and secure APIs that connect AI assistants to your CRM, ERP, ticketing and data platforms with the right permissions.
Copilots
AI assistants & copilots
Chat and voice assistants for customers and employees, embedded in your website, apps, Microsoft Teams or Slack.
Automation
Intelligent document processing
Extract, classify and validate data from invoices, contracts, forms and emails using multimodal AI – feeding clean data straight into your workflows.
Engineering
AI-assisted software engineering
We use and help your teams adopt AI coding assistants such as Claude Code and GitHub Copilot for faster delivery, test generation and legacy-code modernization.
Models
Fine-tuning & custom models
When off-the-shelf models are not enough: fine-tuning, small language models and classic machine learning for prediction, forecasting and anomaly detection.
Operations
LLMOps & evaluation
Automated evaluations, guardrails, prompt and model versioning, cost and latency monitoring – so AI quality is measured, not guessed.
Trust
Responsible AI & AI security
Data privacy, access control, protection against prompt injection and data leakage, and governance aligned with frameworks such as the NIST AI RMF and the EU AI Act.
Platforms we work with
Model-agnostic by design
We choose the right model for each job – balancing quality, cost, latency and data-residency needs.
- OpenAI GPT models
- Anthropic Claude
- Google Gemini
- Azure OpenAI
- Amazon Bedrock
- Google Vertex AI
- Meta Llama
- Mistral
- LangChain & LangGraph
- LlamaIndex
- Model Context Protocol (MCP)
- pgvector
- Pinecone
- Azure AI Search
- Hugging Face
- Python
- PyTorch
How we deliver AI
From idea to production in four steps
01
Discover
Identify high-value use cases, assess data readiness and define success metrics.
02
Prototype
A working proof of concept on your data in weeks, evaluated against real examples.
03
Productionize
Secure integration, guardrails, monitoring and user training for a reliable rollout.
04
Improve
Continuous evaluation and optimization of quality, cost and adoption.
Where could AI make the biggest difference for you?
Book a free discovery call and we will help you find out.