Bun 1.4 — the first stable release after Bun's runtime was rewritten from Zig to Rust — shipped on 20 August. A day later it was running across Scrydon's staging environment. The upgrade was uneventful; the first measurements were not. Across nine Bun runtime services, average CPU fell by 49.9% and average working-set memory by 60.4%, while traced traffic rose 27.1%.
Between 3 September and 29 October we are running five 45-minute sessions, each for a different person in the same building: the executive who has to decide, the engineer who has to run it, the security officer who has to sign it off, the leader who has to make it how the organisation works — and the data leader whose lakehouse it all has to stand on. Here is what each one covers, who it is for, and why we ordered them this way.
This summer, frontier AI labs disclosed that models under evaluation escaped their sandboxes and reached real third-party infrastructure. Scrydon was engineered on the assumption that this day would come. Here is what that means, concretely.
Palantir put the ontology — not the LLM — at the centre of enterprise AI, and that architectural bet is being proven right. But AI itself has now collapsed the cost of building an ontology. You no longer need an army of forward-deployed engineers, and you certainly don't need to hand your most sensitive data to a US vendor to get one.
Every organisation runs on processes. Customer onboarding. Invoice processing. Compliance checks. Sales hand-offs. Service escalations. These processes do not live neatly inside any single system. They exist partly in your CRM, partly in your ERP, partly in spreadsheets, and — most importantly — in the heads of the people who actually get things done.
Reflections from VivaTech 2026 in Paris, days after a US 'killswitch' cut Europe off from frontier AI models. Why going sovereign starts not with buying GPUs but with seeing your own data clearly — and how the Cognitive Enterprise makes that choice executable.
Following the European Commission's publication of its Cloud Sovereignty Framework Implementation Guidance, we've updated our free sovereignty assessment calculator to reflect the full 48-criterion scoring model used in the Commission's own EUR 180 million cloud procurement.
How Scrydon's Cognitive Enterprise implements McKinsey's AI assembly line for sovereign, regulated organisations.
MCP's rapid adoption has outpaced its security model. Here's why regulated enterprises need more than bolt-on fixes.
Key takeaways from NATO TIDE Sprint 44 in Istanbul — how AI, data fusion, agentic orchestration, and sovereign platforms are shaping the future of multi-domain operations.
Law & AI at UC Law SF: Governance, Power and the New Liability Map
Middle powers don’t have to choose between US and Chinese AI stacks. A controllable, auditable orchestration layer keeps your critical data, models, and workflows under your own laws.
Welcome to Scrydon. We're building the future of sovereign AI for Europe, providing choice and certainty in uncertain times.