AI-opslag

Je hebt een FinOps-platform geïmplementeerd. Je bronnen getagd. Voer wekelijkse kostenbeoordelingen uit. En 32% van je clouduitgaven wordt nog steeds verspild. Uit de State of the Cloud-enquête van Flexera in 2022 onder meer dan 750 bedrijven bleek dat dit het gemiddelde is. En het stijgt: 30% in 2021, 32% in 2022. Het probleem is niet de inspanning, maar wat je optimaliseert.

Uw juridische team vraagt om een bewijs van de oorsprong van de trainingsgegevens. Je haalt CloudTrail-logboeken op. De raadsman van de tegenpartij vraagt: „Kan AWS deze logboeken wijzigen?” Het antwoord is ja. De vraag is of dat belangrijk is, en in toenemende mate ook.

Uw reservekopietaak is met succes voltooid. Je auditor maakt het niet uit. 58% van de gegevensback-ups mislukt tijdens daadwerkelijke herstelpogingen. 40% van de cyberverzekeringsclaims die in 2024 werden ingediend, werd afgewezen. Niet omdat de aanvallen niet echt waren. Niet omdat de schade niet werd gedekt. Omdat bedrijven niet konden bewijzen dat hun back-ups echt werken.

Bedrijven in de EU zitten vast tussen het vertrouwen op Amerikaanse hyperscalers met blootstelling aan de CLOUD Act en de overstap naar volledig soevereine clouds die capaciteit opofferen en de kosten verhogen. De echte oplossing is het classificeren van gegevens en alleen het isoleren van de 20-30% waarvoor soevereiniteit vereist is. Een hybride model met door de klant bediende sleutels, nul uitgangen en S3-compatibele workflows biedt zowel soevereiniteit als innovatie tegen lagere kosten dan beide extreme

De meeste bedrijven hebben AI-automatiseringen of -agenten geïmplementeerd. Minder dan 10% heeft ze succesvol geschaald. De kloof zit niet in de capaciteit van agenten. Het is een opslaginfrastructuur die is gebouwd voor mensen.

Verplaats je gegevens naar Frankfurt. Nog steeds onderworpen aan de Amerikaanse wetgeving. Ga over naar OVHcloud. Nog steeds onderworpen aan de Franse wet. Het debat over gegevenssoevereiniteit heeft de verkeerde vraag gesteld. Iedereen maakt ruzie over waar data zich bevindt. De echte vraag is wie de voogdij heeft.

Al meer dan tien jaar draait de cloudarchitectuur om één aanname: data wordt overgezet naar computing. Enorme datapijplijnen hebben terabytes over clouds verspreid, van opslagemmers tot GPU-clusters en analyse-engines. Het model werkte wanneer de gegevens kleiner waren en de bandbreedte goedkoper was. Dat is niet meer het geval.

Learn to connect Claude AI to Akave Cloud using the Model Context Protocol (MCP). Create buckets, upload files, and generate pre-signed URLs with natural language.

375ai, a decentralized edge data intelligence network, has integrated a technical pilot with Akave, an enterprise-grade, S3-compatible object storage solution purpose built for edge and AI. Akave provides 375ai with the data integrity guarantees, low latency, high performance, and significant cost savings.

Artificial intelligence is moving from laboratories into society at an accelerating pace. Language models write code and screen resumes; recommender systems shape public discourse; autonomous vehicles navigate city streets. With these advances come risks of bias, accidents and abuse. Policymakers worldwide are scrambling to establish rules that ensure AI is trustworthy, transparent and accountable. In 2025 two regulatory frameworks stand out: the European Union’s AI Act, the first comprehensive law governing AI systems, and California’s Transparency in Frontier AI Act (SB 53), the first U.S. state law directly regulating developers of large foundation models.

Artificial intelligence has entered an era of industrial scale. Large models with hundreds of billions of parameters, trained across thousands of GPUs, are enabling breakthroughs in language, vision and science. Yet this success comes at a cost: electricity is now the limiting reagent for intelligence. Recent reporting has shown that AI data centres can consume as much power as a small city and that cooling these dense clusters of GPUs and TPUs is becoming a primary engineering challenge. When a single training run for a model like GPT‑3 consumes megawatt‑hours of electricity and high‑performance compute clusters require specialized cooling, it is clear that energy is no longer an afterthought, it is the bottleneck. Without reliable, affordable and low‑carbon power, compute sovereignty becomes impossible. This blog makes the case that energy sovereignty, control over the sources, resilience and sustainability of power, is now inseparable from compute sovereignty. We explore the technologies enabling this transition, from small modular reactors and fusion to microgrids, demand response and decentralized physical infrastructure networks (DePIN). We examine the geopolitical and environmental stakes of this transformation and offer actionable recommendations for policymakers and technologists.

As AI and data workloads grow, CIOs must rethink what “cloud strategy” really means. This guide outlines five critical questions every enterprise should ask before renewing a cloud contract, covering data control, cost transparency, verifiability, AI readiness, and multi-cloud flexibility.

By 2026, enterprise cloud strategy is shifting from monolithic stacks to composable infrastructure—modular, interoperable systems built on open standards. Instead of being locked into a single vendor, companies combine specialized tools like Snowflake for analytics, Apache Iceberg for open data formats, and Akave Cloud for verifiable storage.

As cloud infrastructure evolves, five major trends are reshaping how enterprises think about storage: sovereign edge deployments, verifiable audit logs, zero-trust security, AI-native orchestration, and sustainability by design. This blog explores how these shifts are redefining the role of storage—from passive capacity to active, programmable infrastructure—and highlights why future-ready platforms like Akave Cloud are well-positioned to lead in this new era.

Most enterprise data remains underutilized, trapped in silos, weighed down by egress fees, and unfit for real-time AI workflows. Akave Cloud is a programmable, verifiable object storage layer built to change that. With S3 compatibility, zero egress fees, and onchain auditability, it helps enterprises unlock proprietary data, support AI-scale performance, and monetize datasets via emerging data marketplaces like Baselight. From synthetic data storage to regulatory readiness, Akave Cloud provides the foundation for data ownership at scale, turning compliance cost centers into revenue-generating assets.

Akave O3 provides enterprises and institutions with GDPR-compliant cloud storage that combines S3 compatibility, immutable audit trails, encryption, and policy-based governance. Designed for regulated industries, O3 enables organizations to meet GDPR, HIPAA, SOC 2, and ISO 27001 requirements with verifiable provenance and zero egress fees. By embedding governance into the storage layer—covering access control, retention, classification, and auditability—Akave O3 helps data leaders transform compliance from a burden into a competitive advantage.

TL;DR Centralized AI cloud creates three predictable problems; exponential cost, vendor lock-in, and compliance risk. Akave Cloud × Heurist solves this by combining verifiable, S3-compatible storage with decentralized compute and ZK-native micropayments. The result: resilient, sovereign infrastructure that preserves provenance, reduces costs, and powers the agentic AI economy, where autonomous agents can store, share, and transact data with cryptographic guarantees.

The EU AI Act sets strict standards for transparency, provenance, and lawful data use across AI supply chains. Traditional storage falls short, relying on vendor-controlled logs that lack independent verification.