Mindflow

Mindflow got the opportunity to share its perspective in Amazon Web Services (AWS)'s latest report on AI adoption: "Unlocking Europe’s AI Potential". What makes that meaningful to us → it reinforces that the conversation is moving where it needs to: beyond experimentation, toward real deployment and measurable execution. This matters to us because it reflects what we've been saying since we started building Mindflow. The next phase of enterprise competitiveness won't be defined by whether you've tried AI. It will be defined by whether you can deploy it at scale, embed it into real operations, and move from experimentation to execution. Our CEO, Paul-Arthur Jonville put it plainly in his contribution: "What once took months can now take days or even hours. This acceleration not only enables users to refocus on activities that truly create value, but it also empowers them to accomplish what was previously impossible." That's not a vision statement. That's what we see happening on the ground with the security, IT, and operations teams building on Mindflow every day. The report: https://lnkd.in/eCTEHiP4 Highly recommend it if you work in enterprise AI or ops, or if you're thinking about where agentic automation fits in your stack. Sasha Rubel Juan Bannatyne Calderón Nicolas de Place Nicolas Pfeiffer Aurore Poirier France de Roquemaurel Sophie-Eléonore Veynachter Vincent Mercier Alia Ilyas Garance Lefèvre

How to build a culture of Automation at enterprise scale? Teams buy platforms, skip change management, and wonder why no one uses the workflows they built. They automate in silos, measure the wrong things, and treat automations as one-time projects instead of living systems. The enterprises winning at automation aren't the ones with the most tools. They're the ones where every analyst, engineer, and ops lead thinks, "Can we automate this?" before doing it manually. That shift doesn't happen overnight. But it compounds fast. Full breakdown on our blog: https://lnkd.in/dn2W8DwQ cc: Sagar Gaur

If your application management still depends on manual approvals and fragmented tooling, the issue is not the process. It’s integration depth. App connectivity, service tickets, API gateways, service mesh configs, data streams. They live in different systems. When integrations are shallow, automation stops at provisioning. You can request access or changes. You can’t execute them end-to-end. Application management scales only when policy enforcement, service configuration, API control, and data flow operations are fully executable via APIs. Full read and write coverage. Not tickets. Not manual handoffs. Tufin SecureApp · Ivanti Cherwell · Azure API Management · AWS App Mesh · Lenses.io

Your SecOps team shouldn't spend their day chasing alerts manually. Here are 5 AI··Agents built on Mindflow to supercharge threat detection and response: from CrowdStrike detection analysis and Sigma Rules enrichment to Google Drive suspicious activity monitoring, IoC extraction through external threat intel, and real-time event analysis against detection rules. Ready to build yours? 👇

European companies are building technologies that actually matter in production, as visible in the Amazon Web Services (AWS) Pioneers Project. One thing I kept coming back to when we were featured: the question of trust. Because the most common thing I hear from enterprise security and IT leaders isn't "can your AI do this?" It's "how do we know it won't do something it shouldn't?" That question deserves a real answer; well, you wouldn't let a new team member push to production without a review cycle. You wouldn't let any decision with real consequences go unchecked. The same logic applies to agents. AI that acts without oversight isn't a feature. In enterprise operations, it's a liability. What we believe in at Mindflow is supervised autonomy. The agent does the work. The human owns the outcome. That distinction matters enormously, for trust, for auditability, for the kinds of customers who are serious about deploying this at scale. Agentic AI without governance isn't enterprise-ready. It's just a demo. Learn More about the AWS Pioneers Project: https://lnkd.in/eQPvJDcY

GRC teams don’t need another dashboard. They need faster, consistent analysis. In this demo, Umberto MATTEI, Solution Designer at Mindflow, demonstrates how AI agents handle end-to-end contract compliance and gap analysis. Upload a contract → Compare it against multiple frameworks → Get a structured analysis with risks, scores, and remediation steps. The output is consistent, structured, and ready to act on. Watch the full use case on YouTube: https://lnkd.in/eg5vC5hU

Practices that separate production-grade AI agents from expensive prototypes. Read the full breakdown: https://lnkd.in/eeynhXZp

If your credential management still relies on manual reviews and periodic cleanups, the issue is not policy. It’s integration depth. Tokens, identities, user permissions, service accounts, access relationships. They live across multiple systems. When integrations are shallow, automation stops at visibility. You can audit access. You can’t enforce it in real time. Credential management scales only when provisioning, deprovisioning, token rotation, and access updates are fully executable via APIs. Full read and write coverage. Not audits. Not spreadsheets. Databricks Token Management · Imperva User Management · Microsoft Graph Identity · Acronis Account Management · Veza

Proud to be featured by Amazon Web Services (AWS) as part of the Pioneers Project. This is what we're building at Mindflow: AI agents that handle the repetitive, high-volume operational work so that security and IT teams can focus on what actually matters. When Amazon Web Services (AWS) set out to spotlight European innovation, we're glad Mindflow made the cut, not for the recognition, but for what it reflects about where enterprise automation is heading. The teams defending your infrastructure deserve better tools than 40 open tabs and a queue of alerts. That's the problem we exist to solve. We call it augmented intelligence. Not AI that replaces humans; AI that removes the busywork so humans can do what only they can do: create, protect, and innovate. Built on Amazon Web Services (AWS), powered by Amazon Bedrock Fabrice Delhoste Evan Bourgouin Paul-Arthur Jonville Sasha Rubel Juan Bannatyne Calderón Nicolas de Place Nicolas Pfeiffer Aurore Poirier France de Roquemaurel Sophie-Eléonore Veynachter Anna Vincent

Umberto MATTEI, Solution Designer at Mindflow, shows how AI··Agent swarms handle security alert investigations end-to-end. A lead incident responder agent orchestrates multiple specialized agents to: · Analyze alerts across systems · Enrich context with threat intelligence · Correlate findings · Generate a structured investigation report · Recommend next steps or create a ticket Each action is controlled, auditable, and tied to specific integrations. The result is a faster, more consistent way to investigate alerts without manual back-and-forth across tools. Watch the full use case on YouTube: https://lnkd.in/er4ne98z