
Plant documents. Live SCADA and IoT data. And — most importantly — the expertise your senior technicians have gained over years of experience. Dovient unifies all three into one verified knowledge layer that gives your frontline instant, cited answers in the moment of work.
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“Reduced unplanned downtime by 35% and cut maintenance costs by 28% within 90 days.”
Sridhar, Senior Maintenance ManagerKayempee Foods
“Consolidated Preventive Maintenance, Vendor Management, and Calibrations onto a single platform.”
Maintenance LeadTKIL (Thyssenkrupp Industries India)
“Brought assets from five petrochemical and pharma sites onto Dovient — now audit-ready with SOP-driven maintenance.”
Sri Hari, Senior Maintenance ManagerVirchow Group
“Now monitoring critical equipment like chillers and refrigerators — fixing issues before breakdowns and reducing wastage by 85%.”
Chandra Sekhar, Maintenance HeadBikanerwala
Three failure modes every multi-site operator recognizes.
The Pattern Behind All Three
Your operating knowledge isn't missing. It's unreachable.
Manufacturing plants already have the knowledge, but it's scattered across systems, buried in Excel sheets, locked inside manuals of 1000 pages, and is in the heads of experienced technicians.
Forcing technicians to waste precious time “searching for the fix” when every minute of downtime matters.

Average cost of unplanned downtime
Knowledge gaps are the leading cause
Typical technician 'wrench time'
The rest is spent searching for information
Of critical knowledge is undocumented
Walks out the door when veterans retire
Sources: Siemens True Cost of Downtime 2024, Reliable Plant / ATS wrench-time studies, Deloitte & Manufacturing Institute
Every plant runs on two knowledge bases — the documented one, and the undocumented one. The undocumented base erodes with every retirement, transfer, and shift change. Dovient captures both and unifies them into one verified, source-traceable graph.
The Documented Layer
SOPs, OEM manuals, work-order history, equipment specs, and maintenance logs — ingested and structured for query.
The Undocumented Layer
The reasoning, workarounds, and failure-mode judgment your most experienced technicians built over years on the floor — captured through structured elicitation, scenario walkthroughs, and in-context validation.
The Dovient Platform
Two inputs — your veterans' tacit knowledge and your plant documentation. Dovient's AI converts them into one verified knowledge layer, then delivers it to your frontline inside every workflow on the platform — for repair, maintenance, and inspection.
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Where Your Knowledge Goes to Work
Add Operations, Quality, and the rest when you're ready. The knowledge layer is already built, so turning on the next workflow is a switch, not another implementation.
When a machine goes down, the technician gets the diagnosis and exact repair steps for this asset — generated from your own manuals and your veterans' fixes — on their phone, in seconds.
FMEA-Based Maintenance Planning
Maintenance plans built around the failure modes that actually threaten this plant — ranked from your equipment history and your engineers' know-how — so effort lands where the risk is, not where a template says.
Service Requests & Breakdown Management
The moment a line stops, the technician gets the likely cause and the exact fix for this machine — pulled from your own manuals and how your veterans fixed it last time.
Work Orders
Every order carries the cited answer with it — no hunting through binders, no waiting on the one person who knows.
Preventive Maintenance
PM steps written from this equipment's real history and your team's hard-won shortcuts — not a vendor's generic template.
Anomaly Detection
Live SCADA and IoT signals catch the early warning; the knowledge layer tells the frontline what it means and what to check first.
Inventory & Spares
The right part, identified and located in the moment of repair — because parts knowledge lives where the fix happens.
The right permits, LOTO steps, and job-safety analysis surfaced at the point of work — so the safe way is the obvious way, grounded in how your plant actually does it.
Shift handovers, standard work, and digital rounds that carry tribal know-how forward — so a new operator runs the line like a veteran.
When a defect or deviation shows up, the frontline gets the likely cause and the proven corrective action — cited from your plant's own quality history.
…and the supporting workflows your frontline touches every day
Utilities & Energy
Frontline visibility into utilities and energy on rounds, with the same cited, in-context answers when a reading drifts out of range.
Training & Skills
Training built from your plant's captured expertise — the foundation for our roadmap to develop the next generation of skilled frontline talent.
One platform. One knowledge graph. No second integration. No second contract.
Outcomes
When a line goes down
During a breakdown, Dovient retrieves what the technician needs at each step — lockout verification, diagnostic sequence, relevant historical fixes, repair procedure, and spare-part identifier. Each step is cited and presented in execution order.
MTTR reductions of 30–40% across initial deployments.
When you need consistency across sites
Dovient transforms operator expertise and existing documentation into illustrated, video-supported SOPs in every operator's native language — whether the work is in Hyderabad, Stuttgart, or Houston.
Same approved procedure, every line, every site. Measurably shorter ramp for new operators.
Generic AI generates fluent answers from whatever it was trained on, with no built-in way to know when it lacks context. That's why generic AI hallucinates in manufacturing.
MissingDots closes that gap. Before any answer reaches your team, it checks whether your plant's combined knowledge contains enough context to answer with confidence. If it doesn't, it refuses to guess — it surfaces what's missing and asks for it instead.
Honest uncertainty over fabricated confidence.
“Why is Line 3 vibrating above threshold after the bearing replacement?”
Step-by-step fix with cited sources, spare part numbers, and safety precautions. Every claim traceable to your documentation.
Interoperable by Design
Dovient sits on top of your existing stack — ERPs, CMMS / EAM, historian and SCADA, IoT gateways, and your DMS. Standard connectors deploy in 1–2 weeks. Edge gateways available for low-connectivity sites.
No six-month implementation. No multi-vendor consulting engagement.

Drop in your SOPs, manuals, and work orders. Dovient ingests and structures everything into a searchable knowledge graph.
Your team begins asking questions. MissingDots verifies every answer against source documents in real time.
Roll out across lines and plants. Automate routine checks, generate compliance reports, and capture new knowledge as it happens.
Backed by leading accelerators and industry bodies



Digitize your plant's tacit knowledge first.
Answers to the questions every operations and digital leader brings to the evaluation.
Free learning guides
Practical, technician-written guides on the fundamentals of maintenance, KPIs, preventive and predictive strategies, and shift-level knowledge management.
Implement CMMS without the common pitfalls. Step-by-step plan covering data migration, team training, configuration, pilot rollout, and go-live.
Read guideThe essential maintenance KPIs with formulas, benchmarks, and improvement strategies. OEE, MTTR, MTBF, PM compliance, schedule compliance, and more.
Read guideEvery shift change is a potential information gap. The outgoing crew knows about the intermittent fault on Line 3, the part that was ordered but has not arrived, and the workaround on the packaging machine. If that does not transfer, the incoming crew starts from zero.
Read guideTotal Productive Maintenance turns operators into your first line of defense. Learn the 8 TPM pillars, how to implement autonomous maintenance, and why plants with mature TPM programs see 15-25% OEE gains.
Read guideUnderstand the key differences between predictive and preventive maintenance. Learn when to use each strategy, cost comparisons, and how AI is changing the equation.
Read guideRCM methodology explained practically. The 7 questions, FMEA integration, decision logic, and how to implement RCM without paralyzing your team with analysis.
Read guideFrom the blog
Field-tested writing on OEE, predictive maintenance, MTTR, CMMS selection, and the knowledge-capture problems that keep plants running below target.
The 3-year financial model behind predictive maintenance programs — with the honest cost of sensors, software, and the team needed to act on the data.
Read articleHow to run an RCA that actually finds the failure point instead of stopping at the symptom. Templates, pitfalls, and real factory examples.
Read articleThe OEE formula broken down with real numbers from three different plants, plus the traps that make OEE look better than it is.
Read articleA plain-language explainer of what CMMS does, what it does not do, and how it differs from EAM, APM, and an AI copilot.
Read articleWhy most MTTR projects stall, and the three strategies (prioritization, parts availability, and skill-matching) that cut mean-time-to-repair in half.
Read articleSide-by-side comparison of the CMMS platforms manufacturers actually evaluate, including pricing, AI capability, and mobile usability.
Read articleEvery retiring technician takes 20+ years of unwritten 'how this machine really behaves' with them. Here's the capture playbook plants are using now.
Read articleReady-to-use PM checklists for motors, pumps, conveyors, HVAC, and compressors — with the inspection items, frequencies, and tolerances that hold up in audits.
Read article