Agentic platform for enterprise AI
Stop Shadow AI before it becomes a board problem. One governed platform for all your AI — agents, models, costs, and data.
Governed corporate software generation
AI-SDLC end to end: signable Golden Specs, granular AI-BOM traceability, and auditable delivery for teams already generating code with AI.
The face of your brand
Lifelike 3D avatars powered by conversational AI. Create memorable brand experiences with hyper-personalized interactions.
From resistance to excellence
Transform a defensive infrastructure into an active Experience Center. Intelligent automation, persistent context, and real empowerment for your human agents.
Governed intelligence layer
Connect documents, systems and data into one governed layer — source-grounded answers, citations, audit trail. Not a search box: reasoning on what your organisation knows.
Managed cloud security
Wiz partner: managed service on Wiz Cloud Platform — detection, response, and compliance without license sprawl.
Consulting that implements solutions
Strategic consulting plus Mesh-backed build: implant an intelligent nervous system—integrated data, orchestrated workflows, and solutions that stay in production.
Governed software lifecycle with agents
Master specs, mandatory sign-offs, five phases (framing → delivery), risk-tiered reviews, and one LLM gateway — so AI scales without losing auditability.
Official EU sources & your delivery path
Orientation to regulation, official sources, and a practical path from policy to implementation.
Choose with criteria
RAG vs fine-tuning, build vs buy agents, open-source vs proprietary LLMs, AI Act roles: neutral comparisons with a short answer.
Terms that matter
Definitions and links across Mesh, products, and insights — one vocabulary for your teams.
/ AI glossary / Responsibility
Distortion in data or model that produces unfair or inaccurate results.
Bias in AI refers to systematic errors or distortions in training data or model behavior that lead to unfair, discriminatory, or inaccurate outcomes. Responsible AI practices include bias detection and mitigation.
Want to see how this applies to your organisation?
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