{"product_id":"predeep","title":"Predeep","description":"\u003cstyle\u003e\n.guidaio-v3 { --gv3-bg:#f6f5fb;--gv3-surface:#fff;--gv3-surface-soft:#fbfaff;--gv3-ink:#14132b;--gv3-ink-2:#2b2a4a;--gv3-muted:#6c6a8a;--gv3-line:#ecebf5;--gv3-line-2:#e0deef;--gv3-brand:#5b3df5;--gv3-brand-2:#7c63ff;--gv3-brand-soft:#efeaff;--gv3-brand-ink:#2c1d8a;--gv3-ok:#0f8a5a;--gv3-ok-soft:#e6f7ee;--gv3-warn:#b16800;--gv3-warn-soft:#fff3dc;--gv3-bad:#b3261e;--gv3-bad-soft:#fde7e6;--gv3-radius-lg:22px;--gv3-radius:16px;--gv3-radius-sm:10px;--gv3-shadow-sm:0 1px 2px rgba(20,19,43,.04);--gv3-shadow:0 12px 30px rgba(53,38,124,.07);\n  background:radial-gradient(1200px 600px at 80% -10%,rgba(124,99,255,.18),transparent 60%),radial-gradient(900px 500px at -10% 5%,rgba(91,61,245,.12),transparent 60%),var(--gv3-bg);\n  color:var(--gv3-ink);font-family:Inter,system-ui,-apple-system,\"Segoe UI\",Roboto,sans-serif;font-size:16px;line-height:1.6;-webkit-font-smoothing:antialiased;\n  max-width:1240px;margin:0 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summary{cursor:pointer;list-style:none;font-weight:700;color:var(--gv3-ink);display:flex;justify-content:space-between;align-items:center;gap:10px;font-size:15px}\n.guidaio-v3 .faq summary::-webkit-details-marker{display:none}\n.guidaio-v3 .faq summary svg{color:var(--gv3-brand)}\n.guidaio-v3 .faq .ans{color:var(--gv3-muted);margin-top:10px;font-size:14px}\n.guidaio-v3 section.block.conclusion{background:radial-gradient(700px 320px at 0% 0%,rgba(124,99,255,.18),transparent 60%),linear-gradient(135deg,#1c163a 0%,#2c1d8a 100%);color:#fff;border-color:#2c1d8a}\n.guidaio-v3 section.block.conclusion .head h2{color:#fff}\n.guidaio-v3 section.block.conclusion .lead,.guidaio-v3 section.block.conclusion .rich p{color:rgba(255,255,255,.88)}\n.guidaio-v3 section.block.conclusion .rich strong,.guidaio-v3 section.block.conclusion .rich b{color:#fff}\n.guidaio-v3 section.block.conclusion .eyebrow{background:rgba(255,255,255,.14);color:#fff}\n.guidaio-v3 section.block.conclusion .btn-secondary{background:rgba(255,255,255,.14);color:#fff;border-color:rgba(255,255,255,.25)}\n@media (max-width:1080px){.guidaio-v3 .hero-grid,.guidaio-v3 .trust-grid,.guidaio-v3 .company-grid,.guidaio-v3 .setup-grid,.guidaio-v3 .availability{grid-template-columns:1fr}.guidaio-v3 .grid-3,.guidaio-v3 .res-grid,.guidaio-v3 .plan-grid{grid-template-columns:repeat(2,minmax(0,1fr))}}\n@media (max-width:700px){.guidaio-v3{padding:12px 8px 48px}.guidaio-v3 .hero{padding:20px}.guidaio-v3 section.block{padding:20px}.guidaio-v3 .grid-2,.guidaio-v3 .grid-3,.guidaio-v3 .res-grid,.guidaio-v3 .plan-grid,.guidaio-v3 .bestnot,.guidaio-v3 .availability{grid-template-columns:1fr}.guidaio-v3 h1.title{font-size:28px}}\n\u003c\/style\u003e\n\u003cdiv class=\"guidaio-v3\" itemscope itemtype=\"https:\/\/schema.org\/SoftwareApplication\"\u003e\n\u003cmeta itemprop=\"name\" content=\"Predeep: AI Predictive Maintenance for Industrial Plants\"\u003e\n\u003cmeta itemprop=\"description\" content=\"Predeep predicts machine failures before they happen and plans every intervention. Cloud platform connecting existing IoT sensors and databases. Quote only.\"\u003e\n\u003cdiv class=\"hero\"\u003e\u003cdiv class=\"hero-grid\"\u003e\n\u003cdiv\u003e\n\u003cdiv class=\"hero-head\"\u003e\n\u003cdiv class=\"logo-tile\"\u003e\u003cimg src=\"https:\/\/www.aimonitoring.net\/wp-content\/uploads\/2024\/08\/Logo-aimonitoring.svg\" alt=\"Predeep logo\" itemprop=\"image\" loading=\"lazy\"\u003e\u003c\/div\u003e\n\u003cdiv class=\"name-block\"\u003e\n\u003cspan class=\"eyebrow\"\u003e\u003csvg viewbox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\" width=\"14\" height=\"14\"\u003e\u003cpath d=\"m12 3-1.9 5.8a2 2 0 0 1-1.3 1.3L3 12l5.8 1.9a2 2 0 0 1 1.3 1.3L12 21l1.9-5.8a2 2 0 0 1 1.3-1.3L21 12l-5.8-1.9a2 2 0 0 1-1.3-1.3Z\"\u003e\u003c\/path\u003e\u003c\/svg\u003e Manufacturing · Operations Supply\u003c\/span\u003e\u003ch1 class=\"title\" itemprop=\"name\"\u003ePredeep\u003c\/h1\u003e\n\u003cp class=\"lede justify\" itemprop=\"description\"\u003e\u003cb\u003ePredeep\u003c\/b\u003e is a cloud maintenance management platform from Italian vendor AIM. It combines scheduled maintenance with machine-learning failure prediction, connecting to existing Industry 4.0 machines, IoT sensors and databases to cut unplanned downtime.\u003c\/p\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003cdiv class=\"badge-row\"\u003e\n\u003cspan class=\"badge ok\"\u003e\u003csvg viewbox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\" width=\"14\" height=\"14\"\u003e\u003ccircle cx=\"12\" cy=\"12\" r=\"10\"\u003e\u003c\/circle\u003e\u003cpath d=\"m9 12 2 2 4-4\"\u003e\u003c\/path\u003e\u003c\/svg\u003e Active\u003c\/span\u003e\u003cspan class=\"badge\"\u003e\u003csvg viewbox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\" width=\"14\" height=\"14\"\u003e\u003cpolyline points=\"22 7 13.5 15.5 8.5 10.5 2 17\"\u003e\u003c\/polyline\u003e\u003cpolyline points=\"16 7 22 7 22 13\"\u003e\u003c\/polyline\u003e\u003c\/svg\u003e Contact Sales\u003c\/span\u003e\u003cspan class=\"badge\"\u003e\u003csvg viewbox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\" width=\"14\" height=\"14\"\u003e\u003cpath d=\"M6.3 20.3a2.4 2.4 0 0 0 3.4 0L12 18l-6-6-2.3 2.3a2.4 2.4 0 0 0 0 3.4Z\"\u003e\u003c\/path\u003e\u003cpath d=\"m2 22 3-3\"\u003e\u003c\/path\u003e\u003cpath d=\"M7.5 13.5 10 11\"\u003e\u003c\/path\u003e\u003cpath d=\"M10.5 16.5 13 14\"\u003e\u003c\/path\u003e\u003cpath d=\"m18 3-4 4h6l-4 4\"\u003e\u003c\/path\u003e\u003c\/svg\u003e No public API\u003c\/span\u003e\u003cspan class=\"badge brand\"\u003e\u003csvg viewbox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\" width=\"14\" height=\"14\"\u003e\u003ccircle cx=\"12\" cy=\"12\" r=\"10\"\u003e\u003c\/circle\u003e\u003cpath d=\"m9 12 2 2 4-4\"\u003e\u003c\/path\u003e\u003c\/svg\u003e Verified by Guidaio\u003c\/span\u003e\n\u003c\/div\u003e\n\u003cdiv class=\"tbd-row\"\u003e\n\u003cdiv\u003e\n\u003cdiv class=\"label\"\u003eCategories\u003c\/div\u003e\n\u003cdiv class=\"chip-row\"\u003e\n\u003ca class=\"chip cat\" href=\"\/collections\/manufacturing\"\u003eManufacturing\u003c\/a\u003e\u003ca class=\"chip cat\" href=\"\/collections\/operations-supply\"\u003eOperations Supply\u003c\/a\u003e\u003ca class=\"chip cat\" href=\"\/collections\/observability-monitoring\"\u003eObservability Monitoring\u003c\/a\u003e\u003ca class=\"chip cat\" href=\"\/collections\/smart-scheduling\"\u003eSmart Scheduling\u003c\/a\u003e\u003ca class=\"chip cat\" href=\"\/collections\/data-integration\"\u003eData Integration\u003c\/a\u003e\u003ca class=\"chip cat\" href=\"\/collections\/data-visualization\"\u003eData Visualization\u003c\/a\u003e\u003ca class=\"chip cat\" href=\"\/collections\/report-generation\"\u003eReport Generation\u003c\/a\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003cdiv\u003e\n\u003cdiv class=\"label\"\u003eTarget domains\u003c\/div\u003e\n\u003cdiv class=\"chip-row\"\u003e\n\u003ca class=\"chip dom\" href=\"\/collections\/mechanical-manufacturing\"\u003eMechanical Manufacturing\u003c\/a\u003e\u003ca class=\"chip dom\" href=\"\/collections\/energy-utilities\"\u003eEnergy Utilities\u003c\/a\u003e\u003ca class=\"chip dom\" href=\"\/collections\/automotive-mobility\"\u003eAutomotive Mobility\u003c\/a\u003e\u003ca class=\"chip dom\" href=\"\/collections\/operations-administration\"\u003eOperations Administration\u003c\/a\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003cdiv class=\"cta-row\"\u003e\u003ca class=\"btn btn-primary\" href=\"https:\/\/www.aimonitoring.net\/\" target=\"_blank\" rel=\"noopener\"\u003e\u003csvg viewbox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\" width=\"16\" height=\"16\"\u003e\u003cpath d=\"M15 3h6v6\"\u003e\u003c\/path\u003e\u003cpath d=\"M10 14 21 3\"\u003e\u003c\/path\u003e\u003cpath d=\"M18 13v6a2 2 0 0 1-2 2H5a2 2 0 0 1-2-2V8a2 2 0 0 1 2-2h6\"\u003e\u003c\/path\u003e\u003c\/svg\u003e Discover the tool\u003c\/a\u003e\u003c\/div\u003e\n\u003c\/div\u003e\n\u003caside class=\"snapshot\"\u003e\u003ch3\u003eSnapshot\u003c\/h3\u003e\n\u003cdl\u003e\n\u003cdiv class=\"row\"\u003e\n\u003cdt\u003ePricing model\u003c\/dt\u003e\n\u003cdd\u003eContact Sales\u003c\/dd\u003e\n\u003c\/div\u003e\n\u003cdiv class=\"row\"\u003e\n\u003cdt\u003eAPI available\u003c\/dt\u003e\n\u003cdd\u003eNo\u003c\/dd\u003e\n\u003c\/div\u003e\n\u003cdiv class=\"row\"\u003e\n\u003cdt\u003eDeployment\u003c\/dt\u003e\n\u003cdd\u003eWeb app\u003c\/dd\u003e\n\u003c\/div\u003e\n\u003cdiv class=\"row\"\u003e\n\u003cdt\u003eTool status\u003c\/dt\u003e\n\u003cdd\u003eActive\u003c\/dd\u003e\n\u003c\/div\u003e\n\u003cdiv class=\"row\"\u003e\n\u003cdt\u003eCountry of origin\u003c\/dt\u003e\n\u003cdd\u003e🇮🇹 Italy\u003c\/dd\u003e\n\u003c\/div\u003e\n\u003c\/dl\u003e\u003c\/aside\u003e\n\u003c\/div\u003e\u003c\/div\u003e\n\u003cnav class=\"toc\" aria-label=\"Page sections\"\u003e\u003ca href=\"#what\"\u003eWhat is it\u003c\/a\u003e\u003ca href=\"#bestnot\"\u003eWhen to use Predeep \/ When not to\u003c\/a\u003e\u003ca href=\"#how\"\u003eHow to use\u003c\/a\u003e\u003ca href=\"#proscons\"\u003ePros \u0026amp; Cons\u003c\/a\u003e\u003ca href=\"#pricing\"\u003ePricing\u003c\/a\u003e\u003ca href=\"#trust\"\u003eTrust \u0026amp; Privacy\u003c\/a\u003e\u003ca href=\"#watch\"\u003eWatch-outs\u003c\/a\u003e\u003ca href=\"#setup\"\u003eSetup \u0026amp; Integrations\u003c\/a\u003e\u003ca href=\"#company\"\u003eCompany\u003c\/a\u003e\u003ca href=\"#resources\"\u003eResources\u003c\/a\u003e\u003ca href=\"#faq\"\u003eFAQ\u003c\/a\u003e\u003ca href=\"#conclusion\"\u003eConclusion\u003c\/a\u003e\u003c\/nav\u003e\n\u003csection class=\"block\" id=\"what\"\u003e\u003cdiv class=\"head\"\u003e\n\u003cspan class=\"eyebrow\"\u003eOverview\u003c\/span\u003e\u003ch2\u003eWhat is Predeep?\u003c\/h2\u003e\n\u003c\/div\u003e\n\u003cdiv class=\"grid-2\"\u003e\n\u003cdiv class=\"rich justify\"\u003e\n\u003cp\u003e\u003cb\u003ePredeep\u003c\/b\u003e is the maintenance management platform of Artificial Intelligence Monitoring s.r.l. (AIM), a Naples company registered on 2 October 2020 and listed the same day in Italy's special register of innovative startups. Its pitch is blunt: eliminate the downtime companies suffer through intelligent, simple, scheduled maintenance.\u003c\/p\u003e\n\u003cp\u003eWhat distinguishes the product is that it joins two things the market usually sells separately. On one side it is a maintenance management system — work orders, planning, calendar, history, reporting. On the other it is a predictive layer: machine-learning algorithms compute a Health Indicator and estimate the risk that a given failure will affect a given component, so an intervention can be scheduled before a breakdown rather than after one. Both the homepage and the company page describe it as cloud-based software.\u003c\/p\u003e\n\u003cp\u003eSeven capabilities are named. Predictive maintenance with the Health Indicator and its risk algorithms. Maintenance management and planning, from raising an intervention through to reporting, with a calendar view. Machine fleet exploration, which organises assets into a clear hierarchy attached to the production line, the department and the plant. Modular intervention management, which breaks a main job into sub-tasks to expose the critical phases. Complete reporting on key indicators and costs. Intervention history per machine. And automatic alerts when failure risk rises.\u003c\/p\u003e\n\u003cp\u003eThe platform is designed to sit on top of what a plant already has: it interfaces with Industry 4.0 machines, IoT sensors and databases, collecting, storing and organising the data the installations already produce. Press coverage cited by the vendor describes the approach as hardware independent, connecting to sensors already in place.\u003c\/p\u003e\n\u003cp\u003eThe site publishes three figures, presented as a real-world average across its customers: 45% less downtime, 30% lower maintenance costs and 15% better energy efficiency. Four sectors are addressed individually — manufacturing, machinery production, utilities and automotive — and two user profiles are named: production managers, who get the real-time dashboard, and maintenance staff and technical partners, who get the calendar and the reports. Development is co-financed by the European Regional Development Fund through the Campania 2021-2027 programme, under the project \u003ci\u003ePREDEEP — Predictive Maintenance\u003c\/i\u003e.\u003c\/p\u003e\n\u003c\/div\u003e\n\u003cdiv\u003e\n\u003ch3 style=\"font-size:14px;margin-bottom:12px;color:var(--gv3-brand-ink);text-transform:uppercase;letter-spacing:.08em\"\u003eWhat it does\u003c\/h3\u003e\n\u003cul class=\"brand-list\"\u003e\n\u003cli\u003ePredict the risk that a specific failure will hit a specific component, before it happens\u003c\/li\u003e\n\u003cli\u003ePlan and track the whole maintenance process, from raising a work order to the closing report\u003c\/li\u003e\n\u003cli\u003eWatch the real-time health of every machine on an interactive dashboard\u003c\/li\u003e\n\u003cli\u003eReceive automatic alerts when the risk of failure becomes high\u003c\/li\u003e\n\u003cli\u003eOrganise the machine fleet into a hierarchy tied to production line, department and plant\u003c\/li\u003e\n\u003cli\u003eBreak a major intervention into sub-tasks to isolate the critical phases\u003c\/li\u003e\n\u003cli\u003eProduce reports on key indicators, costs and intervention performance\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\u003c\/section\u003e\n\u003csection class=\"block soft\" id=\"bestnot\"\u003e\u003cdiv class=\"head\"\u003e\n\u003cspan class=\"eyebrow\"\u003eAudience\u003c\/span\u003e\u003ch2\u003eWhen to use Predeep \/ When not to\u003c\/h2\u003e\n\u003cp class=\"lead\"\u003eA quick filter to help you decide if Predeep is the right fit.\u003c\/p\u003e\n\u003c\/div\u003e\n\u003cdiv class=\"bestnot\"\u003e\n\u003cdiv class=\"card for\"\u003e\n\u003ch3\u003e\n\u003csvg viewbox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\" width=\"16\" height=\"16\"\u003e\u003cpath d=\"M7 10v12\"\u003e\u003c\/path\u003e\u003cpath d=\"M15 5.88 14 10h5.83a2 2 0 0 1 1.92 2.56l-2.33 8A2 2 0 0 1 17.5 22H4a2 2 0 0 1-2-2v-8a2 2 0 0 1 2-2h2.76a2 2 0 0 0 1.79-1.11L12 2a3.13 3.13 0 0 1 3 3.88Z\"\u003e\u003c\/path\u003e\u003c\/svg\u003e When to use Predeep\u003c\/h3\u003e\n\u003cul class=\"brand-list\"\u003e\n\u003cli\u003eProduction managers on industrial sites where an unplanned machine stoppage is expensive, and who want a real-time health view of every asset\u003c\/li\u003e\n\u003cli\u003eMaintenance planners and technicians who currently juggle a spreadsheet, a paper calendar and a separate diagnostics tool\u003c\/li\u003e\n\u003cli\u003eMachinery manufacturers who want one shared reference point for their technicians and a structured after-sales service\u003c\/li\u003e\n\u003cli\u003eUtilities running critical water or energy infrastructure, where even a short interruption has a service and financial cost\u003c\/li\u003e\n\u003cli\u003ePlants already fitted with sensors that want to exploit the data they collect without replacing their instrumentation\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003c\/div\u003e\n\u003cdiv class=\"card not\"\u003e\n\u003ch3\u003e\n\u003csvg viewbox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\" width=\"16\" height=\"16\"\u003e\u003cpath d=\"M17 14V2\"\u003e\u003c\/path\u003e\u003cpath d=\"M9 18.12 10 14H4.17a2 2 0 0 1-1.92-2.56l2.33-8A2 2 0 0 1 6.5 2H20a2 2 0 0 1 2 2v8a2 2 0 0 1-2 2h-2.76a2 2 0 0 0-1.79 1.11L12 22a3.13 3.13 0 0 1-3-3.88Z\"\u003e\u003c\/path\u003e\u003c\/svg\u003e When not to use Predeep\u003c\/h3\u003e\n\u003cul class=\"brand-list\"\u003e\n\u003cli\u003eBuyers who want to compare prices before talking to anyone: nothing is published and the only entry point is a demo request\u003c\/li\u003e\n\u003cli\u003eTeams looking for a free plan or a self-service trial, neither of which the vendor announces\u003c\/li\u003e\n\u003cli\u003eOrganisations that need to be productive in days: the platform lands in about two weeks, but full predictive coverage takes three to six months\u003c\/li\u003e\n\u003cli\u003eNon-Italian-speaking teams, since the website, the documentation and the sales process are Italian only\u003c\/li\u003e\n\u003cli\u003eEngineering teams that need a public API, an SDK or a mobile app to embed maintenance data elsewhere: none exists\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\u003c\/section\u003e\n\u003csection class=\"block soft\" id=\"how\"\u003e\u003cdiv class=\"head\"\u003e\n\u003cspan class=\"eyebrow\"\u003eGet started\u003c\/span\u003e\u003ch2\u003eHow to use Predeep\u003c\/h2\u003e\n\u003cp class=\"lead\"\u003eA typical end-to-end flow, from setup to results.\u003c\/p\u003e\n\u003c\/div\u003e\n\u003col class=\"steps\"\u003e\n\u003cli\u003eRequest a demo through the contact form: there is no self-service sign-up\u003c\/li\u003e\n\u003cli\u003eAttend the live demo session the vendor schedules with its team\u003c\/li\u003e\n\u003cli\u003eStep 1, kickoff: a workshop on your maintenance processes, technology stack, stakeholders and objectives\u003c\/li\u003e\n\u003cli\u003eStep 2, data acquisition: a workshop to connect the platform to your existing data, or to present the acquisition system to install if the data is not sufficient\u003c\/li\u003e\n\u003cli\u003eStep 3, model training: the algorithms are trained on your company's own data\u003c\/li\u003e\n\u003cli\u003eStep 4, platform delivery: a first fully configured version arrives in roughly two weeks\u003c\/li\u003e\n\u003cli\u003eStep 5, predictive model integration: full predictive coverage is completed over three to six months\u003c\/li\u003e\n\u003cli\u003eDay to day, monitor asset health on the dashboard and act on the automatic alerts\u003c\/li\u003e\n\u003cli\u003ePlan, reschedule and close interventions in the maintenance calendar, splitting big jobs into sub-tasks\u003c\/li\u003e\n\u003cli\u003ePull reports on indicators, costs and intervention performance to steer the next cycle\u003c\/li\u003e\n\u003c\/ol\u003e\u003c\/section\u003e\n\u003csection class=\"block\" id=\"proscons\"\u003e\u003cdiv class=\"head\"\u003e\n\u003cspan class=\"eyebrow\"\u003eQuick read\u003c\/span\u003e\u003ch2\u003ePros \u0026amp; Cons\u003c\/h2\u003e\n\u003c\/div\u003e\n\u003cdiv class=\"grid-2\"\u003e\n\u003cdiv class=\"pc pros\"\u003e\n\u003ch3\u003e\n\u003csvg viewbox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\" width=\"14\" height=\"14\"\u003e\u003ccircle cx=\"12\" cy=\"12\" r=\"10\"\u003e\u003c\/circle\u003e\u003cpath d=\"m9 12 2 2 4-4\"\u003e\u003c\/path\u003e\u003c\/svg\u003e Pros\u003c\/h3\u003e\n\u003cul\u003e\n\u003cli\u003e\n\u003csvg viewbox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\" width=\"14\" height=\"14\"\u003e\u003cpolyline points=\"20 6 9 17 4 12\"\u003e\u003c\/polyline\u003e\u003c\/svg\u003e \u003cspan\u003ePlanning and prediction live in one tool, where the market usually sells the CMMS and the predictive layer separately\u003c\/span\u003e\n\u003c\/li\u003e\n\u003cli\u003e\n\u003csvg viewbox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\" width=\"14\" height=\"14\"\u003e\u003cpolyline points=\"20 6 9 17 4 12\"\u003e\u003c\/polyline\u003e\u003c\/svg\u003e \u003cspan\u003eConnects to existing sensors, Industry 4.0 machines and databases rather than imposing proprietary hardware\u003c\/span\u003e\n\u003c\/li\u003e\n\u003cli\u003e\n\u003csvg viewbox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\" width=\"14\" height=\"14\"\u003e\u003cpolyline points=\"20 6 9 17 4 12\"\u003e\u003c\/polyline\u003e\u003c\/svg\u003e \u003cspan\u003eGenuinely modular: the predictive module can be switched on alone and plugged into a maintenance system already in place\u003c\/span\u003e\n\u003c\/li\u003e\n\u003cli\u003e\n\u003csvg viewbox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\" width=\"14\" height=\"14\"\u003e\u003cpolyline points=\"20 6 9 17 4 12\"\u003e\u003c\/polyline\u003e\u003c\/svg\u003e \u003cspan\u003eThe rollout is written down and dated, with a first configured version delivered in about two weeks\u003c\/span\u003e\n\u003c\/li\u003e\n\u003cli\u003e\n\u003csvg viewbox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\" width=\"14\" height=\"14\"\u003e\u003cpolyline points=\"20 6 9 17 4 12\"\u003e\u003c\/polyline\u003e\u003c\/svg\u003e \u003cspan\u003ePer-customer isolated environments, encrypted data and encrypted communications, with extra security layers on request\u003c\/span\u003e\n\u003c\/li\u003e\n\u003cli\u003e\n\u003csvg viewbox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\" width=\"14\" height=\"14\"\u003e\u003cpolyline points=\"20 6 9 17 4 12\"\u003e\u003c\/polyline\u003e\u003c\/svg\u003e \u003cspan\u003eOn-premise deployment is possible, which is unusual for a small cloud vendor\u003c\/span\u003e\n\u003c\/li\u003e\n\u003cli\u003e\n\u003csvg viewbox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\" width=\"14\" height=\"14\"\u003e\u003cpolyline points=\"20 6 9 17 4 12\"\u003e\u003c\/polyline\u003e\u003c\/svg\u003e \u003cspan\u003eDevelopment backed by a named, verifiable European regional grant, which gives the roadmap some public accountability\u003c\/span\u003e\n\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003c\/div\u003e\n\u003cdiv class=\"pc cons\"\u003e\n\u003ch3\u003e\n\u003csvg viewbox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\" width=\"16\" height=\"16\"\u003e\u003ccircle cx=\"12\" cy=\"12\" r=\"10\"\u003e\u003c\/circle\u003e\u003cline x1=\"4.93\" y1=\"4.93\" x2=\"19.07\" y2=\"19.07\"\u003e\u003c\/line\u003e\u003c\/svg\u003e Cons\u003c\/h3\u003e\n\u003cul\u003e\n\u003cli\u003e\n\u003csvg viewbox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\" width=\"14\" height=\"14\"\u003e\u003cline x1=\"18\" y1=\"6\" x2=\"6\" y2=\"18\"\u003e\u003c\/line\u003e\u003cline x1=\"6\" y1=\"6\" x2=\"18\" y2=\"18\"\u003e\u003c\/line\u003e\u003c\/svg\u003e \u003cspan\u003eNo published price of any kind: you cannot size the investment without going through a salesperson\u003c\/span\u003e\n\u003c\/li\u003e\n\u003cli\u003e\n\u003csvg viewbox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\" width=\"14\" height=\"14\"\u003e\u003cline x1=\"18\" y1=\"6\" x2=\"6\" y2=\"18\"\u003e\u003c\/line\u003e\u003cline x1=\"6\" y1=\"6\" x2=\"18\" y2=\"18\"\u003e\u003c\/line\u003e\u003c\/svg\u003e \u003cspan\u003eNeither a free plan nor a free trial is announced\u003c\/span\u003e\n\u003c\/li\u003e\n\u003cli\u003e\n\u003csvg viewbox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\" width=\"14\" height=\"14\"\u003e\u003cline x1=\"18\" y1=\"6\" x2=\"6\" y2=\"18\"\u003e\u003c\/line\u003e\u003cline x1=\"6\" y1=\"6\" x2=\"18\" y2=\"18\"\u003e\u003c\/line\u003e\u003c\/svg\u003e \u003cspan\u003eNo terms and conditions, no legal notice and no data processing agreement are published, so no contractual commitment can be checked in advance\u003c\/span\u003e\n\u003c\/li\u003e\n\u003cli\u003e\n\u003csvg viewbox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\" width=\"14\" height=\"14\"\u003e\u003cline x1=\"18\" y1=\"6\" x2=\"6\" y2=\"18\"\u003e\u003c\/line\u003e\u003cline x1=\"6\" y1=\"6\" x2=\"18\" y2=\"18\"\u003e\u003c\/line\u003e\u003c\/svg\u003e \u003cspan\u003eThe only legal document online is a privacy policy that covers the marketing site, not the platform or its machine data\u003c\/span\u003e\n\u003c\/li\u003e\n\u003cli\u003e\n\u003csvg viewbox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\" width=\"14\" height=\"14\"\u003e\u003cline x1=\"18\" y1=\"6\" x2=\"6\" y2=\"18\"\u003e\u003c\/line\u003e\u003cline x1=\"6\" y1=\"6\" x2=\"18\" y2=\"18\"\u003e\u003c\/line\u003e\u003c\/svg\u003e \u003cspan\u003eNo list of subprocessors is published, and no hosting location for customer data is disclosed anywhere\u003c\/span\u003e\n\u003c\/li\u003e\n\u003cli\u003e\n\u003csvg viewbox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\" width=\"14\" height=\"14\"\u003e\u003cline x1=\"18\" y1=\"6\" x2=\"6\" y2=\"18\"\u003e\u003c\/line\u003e\u003cline x1=\"6\" y1=\"6\" x2=\"18\" y2=\"18\"\u003e\u003c\/line\u003e\u003c\/svg\u003e \u003cspan\u003eNo security certification is claimed — neither ISO 27001 nor SOC 2 — and the headline performance figures are self-declared averages with no named customer behind them\u003c\/span\u003e\n\u003c\/li\u003e\n\u003cli\u003e\n\u003csvg viewbox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\" width=\"14\" height=\"14\"\u003e\u003cline x1=\"18\" y1=\"6\" x2=\"6\" y2=\"18\"\u003e\u003c\/line\u003e\u003cline x1=\"6\" y1=\"6\" x2=\"18\" y2=\"18\"\u003e\u003c\/line\u003e\u003c\/svg\u003e \u003cspan\u003eItalian only, with no public API, no documentation and no mobile app, from a very small and young vendor\u003c\/span\u003e\n\u003c\/li\u003e\n\u003c\/ul\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\u003c\/section\u003e\n\u003csection class=\"block soft\" id=\"pricing\"\u003e\u003cdiv class=\"head\"\u003e\n\u003cspan class=\"eyebrow\"\u003ePricing\u003c\/span\u003e\u003ch2\u003ePricing \u0026amp; Plans\u003c\/h2\u003e\n\u003c\/div\u003e\n\u003cp class=\"rich justify\" style=\"color:var(--gv3-ink-2);margin:0 0 18px;max-width:80ch\"\u003eNo price is published. Across the whole eight-page site there is no pricing page, no plan table and no figure of any kind, and the vendor announces neither a permanent free plan nor a free trial. Predeep is sold through contact: the only call to action is a demo request, and the offer is presented as tailored to each sector and each customer, which is consistent with the absence of a public rate card. Prospective buyers should also budget for the rollout itself, which involves workshops, possibly the installation of a data acquisition system, and a three to six month integration period.\u003c\/p\u003e\n\u003cdiv class=\"pricing-extras\"\u003e\u003cdiv class=\"affiliate-note\"\u003ePrices and plans listed above may evolve. Always check the official pricing page before subscribing.\u003c\/div\u003e\u003c\/div\u003e\u003c\/section\u003e\n\u003csection class=\"block\" id=\"trust\"\u003e\u003cdiv class=\"head\"\u003e\n\u003cspan class=\"eyebrow\"\u003eTrust \u0026amp; Privacy\u003c\/span\u003e\u003ch2\u003eData, GDPR \u0026amp; hosting\u003c\/h2\u003e\n\u003cp class=\"lead\"\u003eA consolidated view of how Predeep handles your data.\u003c\/p\u003e\n\u003c\/div\u003e\n\u003cdiv class=\"trust-grid\"\u003e\n\u003cdiv class=\"col\"\u003e\n\u003cdiv class=\"trust-card\"\u003e\n\u003ch3\u003eGDPR overview\u003c\/h3\u003e\n\u003cp class=\"justify\" style=\"color:var(--gv3-ink-2);margin:0\"\u003eThe vendor is an Italian company and therefore established inside the EU, so no Article 27 representative is required and none is designated. Privacy and cookie policies are hosted on iubenda and linked from the footer of every page. The privacy policy lists the usual GDPR rights — access, rectification, erasure, restriction, objection, portability, withdrawal of consent and complaint to the supervisory authority — and names the controller with a certified email address. No data protection officer is appointed. The list of processors is available on request rather than published. Processing locations are declared for the website's third-party services only: the United States for the Google services, Ireland for LinkedIn.\n\nTwo limits matter. The site never claims to be GDPR compliant in so many words, and the policy covers the marketing site rather than the platform, so any GDPR fact stated here is revocable for Predeep itself.\u003c\/p\u003e\n\u003c\/div\u003e\n\u003cdiv class=\"trust-card\"\u003e\n\u003ch3\u003eWho owns the data?\u003c\/h3\u003e\n\u003cp class=\"justify\" style=\"color:var(--gv3-ink-2);margin:0 0 12px\"\u003eThe vendor publishes no terms and conditions, no service contract and no data processing agreement, so there is no public clause stating who owns the data a customer feeds into the platform. The only legal document online is a privacy policy hosted on iubenda, and it explicitly covers \u003ci\u003ethis Application\u003c\/i\u003e — the aimonitoring.net marketing site, not the Predeep platform. It names Artificial Intelligence Monitoring, Via Traccia a Poggioreale 541, Naples, as data controller, reachable at a certified Italian mailbox. On the product side the site says only that each customer gets a dedicated environment, fully separated from every other and open exclusively to the users the company itself designates. Ownership of machine data should be settled in writing before signing.\u003c\/p\u003e\n\u003ch3\u003eReuse rights\u003c\/h3\u003e\n\u003cp class=\"justify\" style=\"color:var(--gv3-ink-2);margin:0\"\u003eThere is no contract to read, so nothing describes what a customer may do with the data or the outputs the platform produces. What the vendor does describe is its own use: at step three of the rollout the algorithms are trained on the company's data, for that company. No pooled or cross-customer use of machine data is ever claimed, and no shared model is mentioned. The privacy policy documents only the marketing site — contact form, mailing list, Google Analytics 4, Google Tag Manager, several Google Ads services and a LinkedIn widget. The two opt-outs it offers are advertising and analytics opt-outs, not a way to keep machine data out of model training, which the vendor never addresses.\u003c\/p\u003e\n\u003c\/div\u003e\n\u003cdiv class=\"trust-card\"\u003e\n\u003ch3\u003eData retention \u0026amp; training\u003c\/h3\u003e\n\u003cdiv class=\"kv\"\u003e\n\u003cdiv class=\"k\"\u003eRetention summary\u003c\/div\u003e\n\u003cdiv class=\"v justify\"\u003eNo retention period is published anywhere, in days, months or years. The privacy policy uses the standard iubenda wording: unless stated otherwise, personal data is processed and kept for as long as the purpose it was collected for requires, and may be kept longer because of legal obligations or on the basis of the user's consent. Where processing rests on consent, the user can withdraw it at any time and the data is kept until that withdrawal.\n\nTwo limits should be kept in mind. This rule covers the marketing website only. Nothing at all is published about how long the machine data of Predeep customers is retained, whether it is anonymised, or what happens to it and to the trained models when a contract ends, because no contractual document is public.\u003c\/div\u003e\n\u003c\/div\u003e\n\u003cdiv class=\"kv\"\u003e\n\u003cdiv class=\"k\"\u003eGDPR contact\u003c\/div\u003e\n\u003cdiv class=\"v\"\u003e\u003ca href=\"mailto:aimonitoringsrl@pec.it\"\u003eaimonitoringsrl@pec.it\u003c\/a\u003e\u003c\/div\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003cdiv class=\"col\"\u003e\u003cdiv class=\"trust-card\"\u003e\n\u003ch3\u003eHosting summary\u003c\/h3\u003e\n\u003cp class=\"justify\" style=\"color:var(--gv3-ink-2);margin:0 0 14px\"\u003eThe vendor publishes nothing about where the data of Predeep customers is hosted. There is no security page, no trust centre, no subprocessor list and no hosting jurisdiction statement anywhere on the site.\n\nThe only processing locations that appear in the privacy policy belong to the marketing website's third-party services: the United States for Google Analytics 4, Google Tag Manager, Google Ads and Google Fonts, and Ireland for the LinkedIn widget. These say nothing about the platform itself and should not be read as the product's hosting. The policy otherwise uses a generic formula, stating that data is processed at the controller's operating premises and anywhere else the parties involved are located.\n\nThe only hosting-related commitment the vendor does make concerns isolation rather than geography: each customer is given a dedicated environment, fully separated from the others and accessible only to the users the company designates, with encrypted data and encrypted communications. Jurisdiction, data centre location and subprocessors all have to be asked for directly.\u003c\/p\u003e\n\u003c\/div\u003e\u003c\/div\u003e\n\u003c\/div\u003e\u003c\/section\u003e\n\u003csection class=\"block watch\" id=\"watch\"\u003e\u003cdiv class=\"head\"\u003e\n\u003cspan class=\"eyebrow\"\u003eWatch-outs\u003c\/span\u003e\u003ch2\u003eThings to keep in mind\u003c\/h2\u003e\n\u003cp class=\"lead\"\u003eRisks and trade-offs to weigh before adopting Predeep.\u003c\/p\u003e\n\u003c\/div\u003e\n\u003cul class=\"brand-list\" style=\"grid-template-columns:repeat(2,1fr);display:grid;gap:12px 24px\"\u003e\n\u003cli\u003eThe product name and the vendor name differ: Predeep is the platform, AIMonitoring or AIM is the company. That is normal, but it makes the tool easy to search for under the wrong name\u003c\/li\u003e\n\u003cli\u003eWith no contract, no terms and no data processing agreement published, everything that matters legally has to be negotiated privately, and a buyer without procurement support may end up accepting whatever is offered\u003c\/li\u003e\n\u003cli\u003eNothing is published about where customer machine data is hosted or who processes it, which is a real gap for a plant whose production data is commercially sensitive\u003c\/li\u003e\n\u003cli\u003eThe 45%, 30% and 15% improvement figures are the vendor's own averages, with no named customer, no period and no published study: treat them as a claim, not a benchmark\u003c\/li\u003e\n\u003cli\u003eThe site's endorsements come from journalists and one contact at a utility, not from contractual customer references, and several are displayed with empty star ratings\u003c\/li\u003e\n\u003cli\u003ePredictive models are only as good as the data behind them, and they reach full performance after three months: acting on early alerts as if they were certainties, or letting the dashboard replace an experienced technician's judgement, is the practical risk\u003c\/li\u003e\n\u003cli\u003eThe vendor is small and young, with a single employee in the last published accounts, so continuity of service and long-term support deserve an explicit contractual answer\u003c\/li\u003e\n\u003c\/ul\u003e\u003c\/section\u003e\n\u003csection class=\"block\" id=\"setup\"\u003e\u003cdiv class=\"head\"\u003e\n\u003cspan class=\"eyebrow\"\u003eSetup\u003c\/span\u003e\u003ch2\u003eSetup \u0026amp; Integrations\u003c\/h2\u003e\n\u003c\/div\u003e\n\u003cdiv class=\"setup-grid\"\u003e\u003cdiv class=\"setup-card\"\u003e\n\u003ch3 style=\"font-size:15px;margin-bottom:10px\"\u003eTechnical difficulty\u003c\/h3\u003e\n\u003cp class=\"justify\" style=\"color:var(--gv3-ink-2);margin:0 0 14px\"\u003eModerate, and vendor-led rather than self-service. The rollout runs in five stages: two workshops, one on your maintenance processes and technology stack and one to connect your data, then model training on your own data, delivery of a first configured platform in about two weeks, and full integration of the predictive models over three to six months. The prerequisite is data rather than skill: Industry 4.0 machines, IoT sensors or databases already in place, with an acquisition system installed if what exists is not enough. No historical data is needed, and no developer work is required.\u003c\/p\u003e\n\u003ch3 style=\"font-size:15px;margin:14px 0 10px\"\u003eDeployment\u003c\/h3\u003e\n\u003cdiv class=\"flag-row\"\u003e\u003cspan class=\"flag\"\u003eWeb app\u003c\/span\u003e\u003c\/div\u003e\n\u003c\/div\u003e\u003c\/div\u003e\u003c\/section\u003e\n\u003csection class=\"block soft\" id=\"company\"\u003e\u003cdiv class=\"head\"\u003e\n\u003cspan class=\"eyebrow\"\u003eCompany\u003c\/span\u003e\u003ch2\u003eBehind Predeep\u003c\/h2\u003e\n\u003c\/div\u003e\n\u003cdiv class=\"company-grid\"\u003e\n\u003cdiv class=\"company-card\"\u003e\n\u003cdiv class=\"kv\"\u003e\n\u003cdiv class=\"k\"\u003eCompany name\u003c\/div\u003e\n\u003cdiv class=\"v\"\u003e\u003cb\u003eArtificial Intelligence Monitoring s.r.l.\u003c\/b\u003e\u003c\/div\u003e\n\u003c\/div\u003e\n\u003cdiv class=\"kv\"\u003e\n\u003cdiv class=\"k\"\u003eFounded\u003c\/div\u003e\n\u003cdiv class=\"v\"\u003e02\/10\/2020\u003c\/div\u003e\n\u003c\/div\u003e\n\u003cdiv class=\"kv\"\u003e\n\u003cdiv class=\"k\"\u003eCountry of origin\u003c\/div\u003e\n\u003cdiv class=\"v\"\u003e🇮🇹 Italy\u003c\/div\u003e\n\u003c\/div\u003e\n\u003cdiv class=\"kv\"\u003e\n\u003cdiv class=\"k\"\u003eHeadquarters\u003c\/div\u003e\n\u003cdiv class=\"v\"\u003eVia Traccia a Poggioreale, 541, 80143 Napoli, Italia\u003c\/div\u003e\n\u003c\/div\u003e\n\u003cdiv class=\"kv\"\u003e\n\u003cdiv class=\"k\"\u003eUBO\u003c\/div\u003e\n\u003cdiv class=\"v\"\u003eINFORMATION_NOT_FOUND\u003c\/div\u003e\n\u003c\/div\u003e\n\u003cdiv class=\"kv\"\u003e\n\u003cdiv class=\"k\"\u003eUBO country\u003c\/div\u003e\n\u003cdiv class=\"v\"\u003eINFORMATION_NOT_FOUND\u003c\/div\u003e\n\u003c\/div\u003e\n\u003cdiv class=\"kv\"\u003e\n\u003cdiv class=\"k\"\u003eDomain registrar country\u003c\/div\u003e\n\u003cdiv class=\"v\"\u003e🇨🇦 Canada\u003c\/div\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\u003cdiv style=\"display:grid;gap:14px\"\u003e\u003cdiv class=\"company-card\"\u003e\n\u003ch3 style=\"font-size:15px;margin-bottom:10px\"\u003eSocial\u003c\/h3\u003e\n\u003cdiv class=\"social-row\"\u003e\u003ca class=\"social\" href=\"https:\/\/www.linkedin.com\/company\/aimonitoring\/\" target=\"_blank\" rel=\"noopener\" aria-label=\"LinkedIn\"\u003e\u003csvg viewbox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\" width=\"18\" height=\"18\"\u003e\u003cpath d=\"M16 8a6 6 0 0 1 6 6v7h-4v-7a2 2 0 0 0-4 0v7h-4v-7a6 6 0 0 1 6-6z\"\u003e\u003c\/path\u003e\u003crect x=\"2\" y=\"9\" width=\"4\" height=\"12\"\u003e\u003c\/rect\u003e\u003ccircle cx=\"4\" cy=\"4\" r=\"2\"\u003e\u003c\/circle\u003e\u003c\/svg\u003e\u003c\/a\u003e\u003c\/div\u003e\n\u003c\/div\u003e\u003c\/div\u003e\n\u003c\/div\u003e\u003c\/section\u003e\n\u003csection class=\"block\" id=\"resources\"\u003e\u003cdiv class=\"head\"\u003e\n\u003cspan class=\"eyebrow\"\u003eOfficial links\u003c\/span\u003e\u003ch2\u003eResources\u003c\/h2\u003e\n\u003cp class=\"lead\"\u003eAll the official URLs gathered for verification and reference.\u003c\/p\u003e\n\u003c\/div\u003e\n\u003cdiv class=\"res-grid\"\u003e\n\u003ca class=\"res\" href=\"https:\/\/www.aimonitoring.net\/\" target=\"_blank\" rel=\"noopener\"\u003e\u003csvg viewbox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\" width=\"14\" height=\"14\"\u003e\u003ccircle cx=\"12\" cy=\"12\" r=\"10\"\u003e\u003c\/circle\u003e\u003cpath d=\"M12 2a14.5 14.5 0 0 0 0 20 14.5 14.5 0 0 0 0-20\"\u003e\u003c\/path\u003e\u003cpath d=\"M2 12h20\"\u003e\u003c\/path\u003e\u003c\/svg\u003e\u003cdiv class=\"res-text\"\u003e\n\u003cdiv\u003eHomepage\u003c\/div\u003e\n\u003cdiv class=\"url\"\u003ewww.aimonitoring.net\u003c\/div\u003e\n\u003c\/div\u003e\u003c\/a\u003e\u003ca class=\"res\" href=\"https:\/\/www.aimonitoring.net\/azienda-e-persone\/\" target=\"_blank\" rel=\"noopener\"\u003e\u003csvg viewbox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\" width=\"14\" height=\"14\"\u003e\u003ccircle cx=\"12\" cy=\"12\" r=\"10\"\u003e\u003c\/circle\u003e\u003cline x1=\"12\" y1=\"16\" x2=\"12\" y2=\"12\"\u003e\u003c\/line\u003e\u003cline x1=\"12\" y1=\"8\" x2=\"12.01\" y2=\"8\"\u003e\u003c\/line\u003e\u003c\/svg\u003e\u003cdiv class=\"res-text\"\u003e\n\u003cdiv\u003eAbout\u003c\/div\u003e\n\u003cdiv class=\"url\"\u003ewww.aimonitoring.net\/azienda-e-persone\u003c\/div\u003e\n\u003c\/div\u003e\u003c\/a\u003e\u003ca class=\"res\" href=\"https:\/\/www.aimonitoring.net\/contatti\/\" target=\"_blank\" rel=\"noopener\"\u003e\u003csvg viewbox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\" width=\"14\" height=\"14\"\u003e\u003crect x=\"2\" y=\"4\" width=\"20\" height=\"16\" rx=\"2\"\u003e\u003c\/rect\u003e\u003cpath d=\"m22 7-10 5L2 7\"\u003e\u003c\/path\u003e\u003c\/svg\u003e\u003cdiv class=\"res-text\"\u003e\n\u003cdiv\u003eContact\u003c\/div\u003e\n\u003cdiv class=\"url\"\u003ewww.aimonitoring.net\/contatti\u003c\/div\u003e\n\u003c\/div\u003e\u003c\/a\u003e\u003ca class=\"res\" href=\"https:\/\/www.iubenda.com\/privacy-policy\/78284685\" target=\"_blank\" rel=\"noopener\"\u003e\u003csvg viewbox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\" width=\"14\" height=\"14\"\u003e\u003cpath d=\"M12 22s8-4 8-10V5l-8-3-8 3v7c0 6 8 10 8 10z\"\u003e\u003c\/path\u003e\u003c\/svg\u003e\u003cdiv class=\"res-text\"\u003e\n\u003cdiv\u003ePrivacy policy\u003c\/div\u003e\n\u003cdiv class=\"url\"\u003ewww.iubenda.com\/privacy-policy\/78284685\u003c\/div\u003e\n\u003c\/div\u003e\u003c\/a\u003e\n\u003c\/div\u003e\u003c\/section\u003e\n\u003csection class=\"block\" id=\"faq\"\u003e\u003cdiv class=\"head\"\u003e\n\u003cspan class=\"eyebrow\"\u003eFAQ\u003c\/span\u003e\u003ch2\u003eFrequently asked questions\u003c\/h2\u003e\n\u003c\/div\u003e\n\u003cdiv class=\"faq\"\u003e\n\u003cdetails\u003e\u003csummary\u003eDo I need historical data to get started? \u003csvg viewbox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\" width=\"14\" height=\"14\"\u003e\u003cline x1=\"12\" y1=\"5\" x2=\"12\" y2=\"19\"\u003e\u003c\/line\u003e\u003cline x1=\"5\" y1=\"12\" x2=\"19\" y2=\"12\"\u003e\u003c\/line\u003e\u003c\/svg\u003e\u003c\/summary\u003e\u003cdiv class=\"ans justify\"\u003eNo. According to the vendor's FAQ, Predeep gives customers insight into the operating state of their machines from the very first moment. Performance improves over time and reaches its maximum after about three months of operation.\u003c\/div\u003e\u003c\/details\u003e\u003cdetails\u003e\u003csummary\u003eCan Predeep be installed on-premise? \u003csvg viewbox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\" width=\"14\" height=\"14\"\u003e\u003cline x1=\"12\" y1=\"5\" x2=\"12\" y2=\"19\"\u003e\u003c\/line\u003e\u003cline x1=\"5\" y1=\"12\" x2=\"19\" y2=\"12\"\u003e\u003c\/line\u003e\u003c\/svg\u003e\u003c\/summary\u003e\u003cdiv class=\"ans justify\"\u003eYes. The vendor states that on-premise deployment is possible and asks prospects to book an appointment so the best arrangement can be assessed together. It is not the standard delivery model, which is cloud-based.\u003c\/div\u003e\u003c\/details\u003e\u003cdetails\u003e\u003csummary\u003eWe already have an ERP. Does Predeep integrate with it? \u003csvg viewbox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\" width=\"14\" height=\"14\"\u003e\u003cline x1=\"12\" y1=\"5\" x2=\"12\" y2=\"19\"\u003e\u003c\/line\u003e\u003cline x1=\"5\" y1=\"12\" x2=\"19\" y2=\"12\"\u003e\u003c\/line\u003e\u003c\/svg\u003e\u003c\/summary\u003e\u003cdiv class=\"ans justify\"\u003eThe vendor's stated aim is to make the most of resources already in the company, physical ones such as sensors and digital ones such as software and data. No named ERP integration is published, so the scope should be confirmed during the demo.\u003c\/div\u003e\u003c\/details\u003e\u003cdetails\u003e\u003csummary\u003eWe already run a maintenance system and only want the predictive part. Is that possible? \u003csvg viewbox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\" width=\"14\" height=\"14\"\u003e\u003cline x1=\"12\" y1=\"5\" x2=\"12\" y2=\"19\"\u003e\u003c\/line\u003e\u003cline x1=\"5\" y1=\"12\" x2=\"19\" y2=\"12\"\u003e\u003c\/line\u003e\u003c\/svg\u003e\u003c\/summary\u003e\u003cdiv class=\"ans justify\"\u003eYes. The vendor says you can activate only the platform's predictive module, or discuss integrating it with your current maintenance software.\u003c\/div\u003e\u003c\/details\u003e\u003cdetails\u003e\u003csummary\u003eHow is my data protected? \u003csvg viewbox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\" width=\"14\" height=\"14\"\u003e\u003cline x1=\"12\" y1=\"5\" x2=\"12\" y2=\"19\"\u003e\u003c\/line\u003e\u003cline x1=\"5\" y1=\"12\" x2=\"19\" y2=\"12\"\u003e\u003c\/line\u003e\u003c\/svg\u003e\u003c\/summary\u003e\u003cdiv class=\"ans justify\"\u003eThe vendor states that all data is encrypted and reachable only through specific authentication, that communications are encrypted, and that each customer gets a dedicated environment fully separated from the others and open only to the users the company designates. Additional security layers are available on request.\u003c\/div\u003e\u003c\/details\u003e\u003cdetails\u003e\u003csummary\u003eHow much does Predeep cost? \u003csvg viewbox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\" width=\"14\" height=\"14\"\u003e\u003cline x1=\"12\" y1=\"5\" x2=\"12\" y2=\"19\"\u003e\u003c\/line\u003e\u003cline x1=\"5\" y1=\"12\" x2=\"19\" y2=\"12\"\u003e\u003c\/line\u003e\u003c\/svg\u003e\u003c\/summary\u003e\u003cdiv class=\"ans justify\"\u003eThe vendor publishes no price, no plan and no free trial. The offer is described as tailored to each sector and customer, and the only entry point is a demo request through the contact form.\u003c\/div\u003e\u003c\/details\u003e\u003cdetails\u003e\u003csummary\u003eIs there a mobile app or a public API? \u003csvg viewbox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\" width=\"14\" height=\"14\"\u003e\u003cline x1=\"12\" y1=\"5\" x2=\"12\" y2=\"19\"\u003e\u003c\/line\u003e\u003cline x1=\"5\" y1=\"12\" x2=\"19\" y2=\"12\"\u003e\u003c\/line\u003e\u003c\/svg\u003e\u003c\/summary\u003e\u003cdiv class=\"ans justify\"\u003eNeither could be found. No iOS or Android application exists under the Predeep or AIMonitoring name, and no API documentation, developer subdomain or OpenAPI file is published.\u003c\/div\u003e\u003c\/details\u003e\u003cdetails\u003e\u003csummary\u003eWho is behind Predeep? \u003csvg viewbox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\" width=\"14\" height=\"14\"\u003e\u003cline x1=\"12\" y1=\"5\" x2=\"12\" y2=\"19\"\u003e\u003c\/line\u003e\u003cline x1=\"5\" y1=\"12\" x2=\"19\" y2=\"12\"\u003e\u003c\/line\u003e\u003c\/svg\u003e\u003c\/summary\u003e\u003cdiv class=\"ans justify\"\u003eArtificial Intelligence Monitoring s.r.l., a Naples company registered on 2 October 2020 and entered the same day in the Italian register of innovative startups. It is a very small team, with three co-founders shown on the site.\u003c\/div\u003e\u003c\/details\u003e\u003cdetails\u003e\u003csummary\u003eIs the product available in English? \u003csvg viewbox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\" width=\"14\" height=\"14\"\u003e\u003cline x1=\"12\" y1=\"5\" x2=\"12\" y2=\"19\"\u003e\u003c\/line\u003e\u003cline x1=\"5\" y1=\"12\" x2=\"19\" y2=\"12\"\u003e\u003c\/line\u003e\u003c\/svg\u003e\u003c\/summary\u003e\u003cdiv class=\"ans justify\"\u003eNot publicly. The website is entirely in Italian, offers no language switcher, and the vendor declares no interface language for the platform itself.\u003c\/div\u003e\u003c\/details\u003e\u003cdetails\u003e\u003csummary\u003eHow long does it take to be fully operational? \u003csvg viewbox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\" width=\"14\" height=\"14\"\u003e\u003cline x1=\"12\" y1=\"5\" x2=\"12\" y2=\"19\"\u003e\u003c\/line\u003e\u003cline x1=\"5\" y1=\"12\" x2=\"19\" y2=\"12\"\u003e\u003c\/line\u003e\u003c\/svg\u003e\u003c\/summary\u003e\u003cdiv class=\"ans justify\"\u003eA first fully configured version of the platform is delivered in roughly two weeks after the data acquisition stage. Full integration of the predictive models takes between three and six months.\u003c\/div\u003e\u003c\/details\u003e\n\u003c\/div\u003e\u003c\/section\u003e\n\u003csection class=\"block conclusion\" id=\"conclusion\"\u003e\u003cdiv class=\"head\"\u003e\n\u003cspan class=\"eyebrow\"\u003eConclusion\u003c\/span\u003e\u003ch2\u003eShould you pick Predeep?\u003c\/h2\u003e\n\u003c\/div\u003e\n\u003cdiv class=\"rich justify\" style=\"max-width:80ch\"\u003e\n\u003cp\u003ePredeep is a real product from an identifiable vendor. Artificial Intelligence Monitoring s.r.l. is registered and active in Naples, its VAT number resolves to the name and address printed on the site, and the development of the platform is backed by a named European regional grant with a verifiable project code. The proposition is clear and well bounded: bring maintenance planning and failure prediction together on the machines and sensors a plant already owns, rather than selling a new instrumentation layer.\u003c\/p\u003e\n\u003cp\u003eThe weakness is commercial opacity rather than technical substance. There is no price, no plan, no terms and conditions, no legal notice, no data processing agreement, no list of subprocessors and no statement of where customer data is hosted. The single legal document online is a privacy policy that explicitly covers the marketing website, not the platform. No security certification is claimed, and the headline figures of 45% less downtime and 30% lower maintenance costs are self-declared averages with no named customer or published study behind them.\u003c\/p\u003e\n\u003cp\u003eThat combination points to a specific reader. Predeep suits an Italian industrial site that is already instrumented, has a production or maintenance manager willing to sponsor the project, and can absorb a three to six month ramp-up. For that buyer the modularity is genuinely useful, since the predictive module can be switched on alone alongside an existing maintenance system.\u003c\/p\u003e\n\u003cp\u003eThe sensible approach is to treat the demo as a due diligence session rather than a sales pitch, and to ask in writing for everything the website does not publish: the price and its billing unit, the contract, where the data will be hosted, who the subprocessors are, and what happens to the machine data and the trained models if the relationship ends.\u003c\/p\u003e\n\u003c\/div\u003e\n\u003cdiv class=\"cta-row\"\u003e\u003ca class=\"btn btn-primary\" href=\"https:\/\/www.aimonitoring.net\/\" target=\"_blank\" rel=\"noopener\"\u003e\u003csvg viewbox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"2\" stroke-linecap=\"round\" stroke-linejoin=\"round\" width=\"16\" height=\"16\"\u003e\u003cpath d=\"M15 3h6v6\"\u003e\u003c\/path\u003e\u003cpath d=\"M10 14 21 3\"\u003e\u003c\/path\u003e\u003cpath d=\"M18 13v6a2 2 0 0 1-2 2H5a2 2 0 0 1-2-2V8a2 2 0 0 1 2-2h6\"\u003e\u003c\/path\u003e\u003c\/svg\u003e Visit Predeep\u003c\/a\u003e\u003c\/div\u003e\u003c\/section\u003e\n\u003c\/div\u003e","brand":"Artificial Intelligence Monitoring s.r.l.","offers":[{"title":"Default Title","offer_id":58389742420299,"sku":null,"price":0.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/1038\/0905\/7099\/files\/official-predeep-by-guidaio_d5a85a1b-de1c-447f-99ad-6a64530b1aa0.png?v=1788734324","url":"https:\/\/guidaio.com\/products\/predeep","provider":"Guidaio","version":"1.0","type":"link"}