Turn your vision into an actionable roadmap
Build and scale solutions from idea to impact
Embed Faktion’s AI experts into your team
Augment expertise and workflows with agents
Drive smarter decisions and business growth
Streamline manufacturing and maintenance
Build armies of domain experts, 24/7 available.
Measure real progress & achieve production quality.
Make Knowledge your competitive Advantage.
Ensure reliable and scalable AI model deployment through robust data quality and MLOps strategies by Faktion.
Combining ML and generative AI to automate classification and accelerate sourcing
GIS International:
Agents aren't the starting point of enterprise AI maturity. They're the result of a trusted, governed knowledge foundation. Here's the architecture and phased rollout that gets you there.
Why enterprise AI breaks without a RAG-first foundation. Build trustworthy retrieval, governance, and traceability before scaling agents and workflows.
Discover the key trends from AI Engineer Paris 2025—where AI engineering shifts from model training to reasoning, evaluation, and operational excellence.
AI Engineer Paris 2025:
Learn how to transform raw IoT telemetry into actionable insights with our ML pipeline for industrial machinery usage detection. Unlock hidden patterns today.
IOT data to insights:
Discover the common failure modes of RAG in enterprises and learn practical fixes to move beyond prototypes into production-ready AI systems.
Transforming 3M+ IoT sensor files into a query-ready dataset with a serverless Azure pipeline delivering sub-second insights at low cost.
Agentic knowledge Management Assistants help organisations systematically capture, structure, and access knowledge, transforming it from an operational bottleneck into a strategic competitive advantage.
Knowledge Management Assistant:
Competitive advantage in AI comes from expert engineering that turns your data and processes into scalable AI systems—not just choosing the right LLM.
Process Modelling can replace manual trials, enabling precise, data-driven input optimisation.
Episode 2: Four methods for building RAG ground truth datasets, from manual to synthetic.
RAG Output Validation - Part 2:
Episode 1: Lays the foundation for scalable, reliable RAG output validation.
RAG Output Validation - Part 1:
How AI reshapes the process industry through real-world impact and scalable solutions.
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