Agentic AI Comparison:
Ceramic.ai vs Google Agentspace
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Introduction
This report provides a detailed comparison between Ceramic.ai, an enterprise-focused AI platform for accelerating model building and fine-tuning, and Google Agentspace, a Google Cloud platform for enterprise AI agents that automate workflows and synthesize data across business tools.
Overview
Ceramic.ai
Ceramic.ai, founded by Anna Patterson, enables enterprises to build custom AI models faster and more efficiently by streamlining data preparation, fine-tuning, and evaluation processes. It targets organizations needing tailored AI solutions without extensive in-house expertise.
Google Agentspace
Google Agentspace is an enterprise-grade AI platform that connects to company apps like Salesforce, Google Drive, and Jira to automate tasks, generate insights, and provide unified search across internal data sources. It leverages Gemini models for secure, scalable operations.
Metrics Comparison
autonomy
Ceramic.ai: 7
Ceramic.ai supports autonomous model fine-tuning and evaluation pipelines, reducing manual data engineering, but requires user oversight for enterprise model deployment.
Google Agentspace: 9
Agentspace excels in background automation of workflows, pulling data from multiple sources and executing tasks like report generation without human intervention.
Google Agentspace demonstrates higher autonomy for operational tasks, while Ceramic.ai focuses on semi-autonomous model development.
ease of use
Ceramic.ai: 6
Requires technical knowledge for model building and integration, though designed to simplify enterprise AI workflows compared to raw tools.
Google Agentspace: 8
Features no-complex-setup prebuilt connectors and conversational interfaces for quick enterprise deployment and daily use.
Agentspace prioritizes user-friendly access for non-technical teams; Ceramic.ai suits users with some AI expertise.
flexibility
Ceramic.ai: 9
High flexibility in customizing foundation models for specific enterprise needs, including data handling and fine-tuning variations.
Google Agentspace: 8
Offers broad integrations with third-party tools and agent interoperability, but optimized for predefined enterprise workflows rather than deep model customization.
Ceramic.ai edges out in model-level flexibility; Agentspace provides versatile tool connections.
cost
Ceramic.ai: 7
Enterprise pricing model likely usage-based for model training, potentially cost-efficient for targeted AI builds but lacks public details.
Google Agentspace: 6
Tied to Google Cloud Platform with setup costs, admin requirements, and scaling expenses for enterprise integrations.
Both are enterprise-oriented with opaque pricing; Ceramic.ai may offer better value for model-specific use cases.
popularity
Ceramic.ai: 5
Emerging startup with limited mentions and no widespread adoption data in current sources as of early 2026.
Google Agentspace: 9
Backed by Google Cloud with extensive documentation, demos, and integrations, indicating strong enterprise traction.
Google Agentspace significantly outpaces Ceramic.ai in visibility and market presence.
Conclusions
Google Agentspace leads overall for enterprises seeking immediate workflow automation and broad integrations (average score: 8.0), while Ceramic.ai shines for teams prioritizing custom model development (average score: 6.8). Selection depends on whether model building or agent-driven operations is the core need.