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 / Models & Architecture
Chain-of-Thought (CoT)
← All glossary termsReasoning style where the model spells out intermediate steps before answering.
Chain-of-thought (CoT) prompting encourages LLMs to produce step-by-step reasoning, which often improves accuracy on math, logic, and multi-hop questions. It is widely used in agent planning, tool selection, and auditability of AI outputs.
Want to see how this applies to your organisation?
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