Dataiku vs Sakana AI

Discover Dataiku Agent Management: every agent on the record

Dataiku announced the launch of Dataiku Agent Management, a new product feature for managing AI agents, along with the announcement of the AI Success Frontrunner award winners.

12,000 Attend Ai4 2026 to Discuss AI's Invisibility

The article reports on the Ai4 2026 conference in Las Vegas, which saw record attendance of over 12,000, up from 8,000 the previous year. Dataiku's keynote highlighted that 96% of enterprise leaders believe employees are using unsanctioned generative AI tools, and 80% of CIOs see their jobs at risk without measurable AI ROI. Pat Gelsinger argued that AI economics must improve dramatically, while Geoffrey Hinton, Fei-Fei Li, and Andrew Ng jointly endorsed AI regulation. The conference emphasized the need for AI governance, budget ownership, and cross-functional staffing. Speakers from Cisco, Nvidia, Uber, PayPal, and other companies discussed the shift from assistants to autonomous agents and the importance of accountable AI deployment.

• Ai4 2026 attendance exceeded 12,000, up from 8,000 the previous year.
• Dataiku's survey found 96% of enterprise leaders believe employees use unsanctioned generative AI tools.
• 80% of CIOs say their job is at risk without measurable AI ROI.

Governed RAG: Data, Context & Lineage for Enterprise AI

The article describes risks introduced by Retrieval-Augmented Generation (RAG) when enterprise data is exposed to vector search pipelines and proposes a three-part Governed RAG architecture: (1) ingestion with cryptographic embedding lineage and metadata, (2) query-time contextual Attribute-Based Access Control (ABAC) embedded into vector search queries, and (3) outbound payload sanitization (PII/PHI masking, indirect injection removal, and context length minimization). It argues that enterprises must enforce retrieval-time access controls, maintain graph-based data lineage, and implement real-time index freshness/eviction to prevent privilege escalation, prompt-injection attacks, stale-context hallucinations, and to meet compliance requirements.

• Retrieval-Augmented Generation (RAG) pairs LLMs with vector databases and knowledge graphs to ground agents in proprietary corporate knowledge.
• Vector stores typically do not preserve fine-grained document-level ACLs or cryptographic data lineage by default, creating over-permissioned retrieval risks.
• The proposed Governed RAG pipeline has three security boundaries: ingestion with cryptographic embedding lineage, query-time contextual ABAC inside the vector search, and outbound payload sanitization.

Sakana AI、「日本スタートアップ大賞2026」で総務大臣賞（情報通信分野）を受賞

Sakana AI has published multiple new announcements since the last check, including receiving the Minister of Internal Affairs and Communications Award at the Japan Startup Awards 2026, welcoming AI pioneer Jürgen Schmidhuber, introducing its Frontier Intelligence Group, updating its Sakana Chat and Marlin products, and announcing a comprehensive business partnership with SCSK and Sumitomo Corporation.

Introducing Sakana AI's Frontier Intelligence Group (FIG)

Sakana AI announces the launch of its Frontier Intelligence Group (FIG), a new initiative focused on advancing frontier AI research and applications.

Sakana AI、ＳＣＳＫ、住友商事の3社、AI活用による日本の産業変革と社会課題解決に向け包括業務提携 ～日本発の技術力・完遂力を核に、AIの社会実装を加速～

Sakana AI、SCSK、住友商事の3社が包括業務提携を発表。日本発の技術力と完遂力を核に、AIの社会実装を加速する。