CERN Expertise and
Real-World AI SolutionsWhat is Cledar?
Led by former CERN domain leaders, Cledar is a team of data scientists, technology experts, and software engineers united by a desire to achieve big things with big data. We design, build, and refine data-driven applications that will help you to make sense of – and thrive – in the world around you.
Ontology-driven AI
Cledar turns fragmented data into a single source of truth, laying the foundation for enterprise AI adoption
PRODUCTIVITY
BOOST
Cledar turns fragmented data into a single source of truth, laying the foundation for enterprise AI adoption
COST
OPTIMIZATION
Cledar turns fragmented data into a single source of truth, laying the foundation for enterprise AI adoption
ROI
MAXIMIZATION
Cledar turns fragmented data into a single source of truth, laying the foundation for enterprise AI adoption
PRODUCTIVITY
BOOST
Cledar turns fragmented data into a single source of truth, laying the foundation for enterprise AI adoption
COST
OPTIMIZATION
Cledar turns fragmented data into a single source of truth, laying the foundation for enterprise AI adoption
ROI
MAXIMIZATION
Cledar turns fragmented data into a single source of truth, laying the foundation for enterprise AI adoption
Platform features & benefits
Secure, Modular Infrastructure
Features:
Runs complex workloads across cloud, on-prem, and hybrid models.
Built-in governance, cost visibility and compliance
Benefit:
Scales seamlessly while ensuring compliance and trust
Unified Data Foundation
Features:
Integrates fragmented data sources into a unified semantic context
Provides a single, governed source of truth
Benefit:
Harmonizes enterprise data and eliminates silos
Ontology - Driven Intelligence
Features:
Runs complex workloads across cloud, on-prem, and hybrid models
Built-in governance, cost visibility and compliance
Benefit:
Scales seamlessly while ensuring compliance and trust
Data Preparation & Quality Engine
Features:
Integrates fragmented data sources into a unified semantic context
Provides a single, governed source of truth
Benefit:
Harmonizes enterprise data and eliminates silos
Adaptive AI Agents
Features:
Deploys configurable agents that reason across data
Executes end-to-end tasks autonomously
Benefit:
Automates workflows, reducing manual effort and delay
Conversational & Visual Analytics
Features:
Natural language querying and instant visualization
Full BI and SQL integration for technical teams
Benefit:
Democratizes analytics while preserving depth and control
Ontology Flywheel Advantage
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Next Steps
1-2 weeks
INITIAL SCOPE
Goal
Align on objectives, challenges, and problem scope
Action
Orientation call, sample use cases, data/policy questionnaire, and high-level value statement
2-8 weeks
PROOF OF CONCEPT (POC)
Goal
Prove value and validate assumptions on a use case
Action
Previously agreed upon POC alongside technical documentation of early results with insights and learnings
2-3 weeks
REQUIREMENT DEFINITION
Goal
Convert POC insights into production requirements
Action
Detailed requirement matrix, model options, governance and compliance design, and implementations roadmap
2-6 months
SCALE-UP (MVP)
Goal
Deploy the MVP, integrate systems, optimize workflows
Action
System configuration, integration with live sources, user onboarding, dashboards; governance and support framework initiation
+1 year
LONG-TERM CONTRACT
Goal
Transition from MVP to steady-state operations and continuous value delivery
Action
Production-grade platform, maintenance and support, roadmap, and quarterly governance cadence
Interested?
Leave us your email, and we do the rest.