import{F as e}from"./factory-BofZA17e.js";import{W as i}from"./warehouse-zC2KHntY.js";import{S as t}from"./shopping-bag-vk9h977g.js";import{S as a}from"./shield-Yh756DzO.js";import{T as n}from"./tram-front-BM_Imj26.js";import{Z as o}from"./zap-BLOcRQPL.js";const r=[{title:"Manufacturing",slug:"manufacturing",icon:e,gradient:"from-data-orange to-data-amber",heroSub:"90-day quick wins for quality, maintenance, and safety. No stack replacement required.",quickWins:["In-line defect detection (QualiZer)","Predictive maintenance on motors/pumps (VibraQore)","Worker safety analytics (SiteSentra)"],personas:["Plant Ops","Quality"],capabilities:["CV","Analytics"],timeToValue:"quick-win",roiUseCases:"cv_quality,analytics",solutions:[{name:"QualiZer",slug:"qualizer-inline-defect-detection",promise:"In-line defect detection",bullets:["Scrap/rework down; explainable reviews","Trend by SKU/shift","Holds/alerts to MES"],timeline:"PoC→Pilot 8–12 weeks · KPI gates · reversible rollout"},{name:"VibraQore",slug:"vibraqore-predictive-maintenance",promise:"Predictive maintenance",bullets:["Early bearing/imbalance detection","Avoid unplanned downtime","Plan interventions"],timeline:"Sensor+vision baseline · alert rules · CMMS hooks"},{name:"SiteSentra",slug:"sitesentra-worker-safety",promise:"Worker safety analytics",bullets:["PPE/zones compliance","Near-miss flags","Video evidence for training"],timeline:"Edge models · reviewer console · audit logs"}],productsUsed:[{name:"SENTRA",slug:"sentra",description:"Edge analytics for real-time inference at line speed"},{name:"NeuroSight",slug:"neurosight",description:"Safety monitoring with PPE detection and zone compliance"},{name:"VISTA",slug:"vista",description:"Redaction for training clips and incident review"}],techDeployment:["Industrial cameras (GigE, USB3) and vibration sensors","Jetson/x86 edge devices rated for harsh environments","MES/ERP integration via REST APIs","CMMS hooks for maintenance work orders"],roiProof:[{metric:"27% scrap reduction",description:"Automotive tier-1 supplier using QualiZer for weld inspection"},{metric:"35% fewer breakdowns",description:"Food processing plant with VibraQore on packaging lines"}],faqs:[{question:"Can this run on our existing line cameras?",answer:"Yes. We support industrial cameras (GigE, USB3) and thermal sensors. Our team conducts a site survey to recommend optimal hardware for your environment and can often leverage existing camera infrastructure."},{question:"How do you measure QC gains?",answer:"We set clear KPI gates: scrap rate, first-pass yield, and cycle time. Metrics are tracked in real-time dashboards and reported to your MES/ERP systems with full audit trails."},{question:"What about on-prem vs cloud deployment?",answer:"We support both. Edge inference runs locally for real-time decisions; cloud integration is optional for model updates and analytics aggregation. Your data stays in your control."},{question:"How long until we see ROI?",answer:"Most customers see measurable ROI within 3-6 months of pilot deployment. We use KPI-gated rollouts to ensure value delivery at each phase."},{question:"What data is needed to get started?",answer:"For defect detection: sample images of good/bad parts. For predictive maintenance: historical breakdown logs and sensor baselines. We help scope data requirements during the PoC phase."},{question:"How do you handle change management?",answer:"We provide operator training, reviewer console walkthroughs, and documentation. Rollouts are reversible and KPI-gated to build confidence with plant teams."}],faqLastUpdated:"2025-01-15",seoTitle:"Manufacturing AI: Defect Detection & Predictive Maintenance",seoDescription:"AI defect detection, predictive maintenance & safety for manufacturing. 27% scrap reduction, 35% fewer breakdowns. Edge deployment, 90-day ROI."},{title:"Warehousing & Logistics",slug:"warehousing-logistics",icon:i,gradient:"from-data-teal to-data-cyan",heroSub:"Cycle counts done overnight, doors turning faster, picks more accurate. No aisle closures, no WMS re-platform.",quickWins:["Autonomous inventory scanning (StockVexel)","Dock/yard analytics (YardLytix)","Pick-path optimization (PickPathor)"],personas:["DC Managers","3PL Ops"],capabilities:["CV","Analytics"],timeToValue:"quick-win",roiUseCases:"cv_inventory,analytics",solutions:[{name:"StockVexel",slug:"stockvexel-inventory-scanning",promise:"Autonomous inventory scanning",bullets:["Nightly cycle counts across full DC","OSA/shrink visibility with photo evidence","Exceptions pushed to handhelds"],timeline:"What you get: drone/AMR routes · WMS reconcile rules · alert playbooks"},{name:"YardLytix",slug:"yardlytix-dock-analytics",promise:"Dock/yard analytics",bullets:["Door dwell down; trailer turns up","Gate OCR + event timeline by trailer/slot","Heatmaps of congestion and SLA breaches"],timeline:"What you get: gate OCR pack · yard map + KPIs · TMS/YMS hooks"},{name:"PickPathor",slug:"pickpathor-path-optimization",promise:"Pick-path optimization",bullets:["Fewer misses, faster path time","Battery/charge planning built-in","Supervisor dashboards for coaching"],timeline:"What you get: path models · ops dashboards · change-mgmt kit"}],productsUsed:[{name:"SENTRA",slug:"sentra",description:"Edge CV for autonomous scanning and real-time yard monitoring"},{name:"Data & Analytics Platform",slug:"data-analytics-platform",description:"WMS integration, SLA tracking, and predictive modeling"}],techDeployment:["AMR/drone integration for night scans; safety interlocks, no aisle closures","Gate cameras with OCR, event timeline by trailer/door/slot","WMS/TMS/YMS adapters via REST/webhooks; handheld tasking flows","Edge devices (Jetson/x86) for real-time inference; cloud sync + cold tier storage"],roiProof:[{metric:"40% faster cycle counts",description:"Baseline vs night-scan with StockVexel; fewer revisits after exception review"},{metric:"25% dock dwell reduction",description:"Door/slot SLA adherence up; detention costs down with YardLytix"}],faqs:[{question:"Does this work with our existing WMS/TMS?",answer:"Yes. Standard adapters; we validate against your data in PoC before pilot."},{question:"Do we have to close aisles?",answer:"No. Night scans with AMR/drone and safety interlocks; live pick remains uninterrupted."},{question:"How accurate is OCR at the gate?",answer:"We set site-specific gates and publish per-site evals; misreads trigger manual review."},{question:"What's the ROI timeline?",answer:"Quick-win payback typically within a quarter; see ROI calculator for your volumes."},{question:"What hardware do we need?",answer:"Existing RTSP cams + gate OCR; AMR/drone optional for coverage and speed."}],faqLastUpdated:"2025-01-15",seoTitle:"Warehousing & Logistics AI Solutions | Allerin",seoDescription:"Quick-win logistics solutions: autonomous inventory scanning, dock analytics, pick optimization. PoC→Pilot 8–12 weeks with KPI gates."},{title:"Retail",slug:"retail",icon:t,gradient:"from-data-cyan to-data-blue",heroSub:"Shelves stocked, queues moving, customers converting. No manual audits, no new POS.",quickWins:["Shelf compliance & OSA (ShelfSentra)","Queue & staffing analytics (Queuence)","Back-room inventory scanning (Backroom Ranger)"],personas:["Store Ops","Merchandising"],capabilities:["CV","Analytics"],timeToValue:"quick-win",roiUseCases:"cv_shelf,analytics",solutions:[{name:"ShelfSentra",slug:"shelfsentra-shelf-compliance",promise:"Shelf compliance & OSA",bullets:["OOS detected and fixed faster; planogram drift alerted","Tasks pushed to handheld devices with photo evidence","Recovery time measured from alert to shelf fix"],timeline:"What you get: in-aisle models · tasking API · KPI dashboards"},{name:"Queuence",slug:"queuence-queue-analytics",promise:"Queue & staffing analytics",bullets:["Queue length predicted; staffing alerts automated","Lane-open alerts cut walk-offs and wait times","Abandonment rates tracked with trend analysis"],timeline:"What you get: predictive models · staffing hooks · SLA reports"},{name:"Backroom Ranger",slug:"backroom-ranger-inventory",promise:"Back-room inventory scanning",bullets:["Back-room counts faster; gap detection automated","Reconcile to ERP for real-time inventory accuracy","Handheld workflows reduce manual audit time"],timeline:"What you get: scanning workflows · handheld app · ERP adapters"}],productsUsed:[{name:"SENTRA",slug:"sentra",description:"In-aisle CV for shelf compliance and queue monitoring"},{name:"Data & Analytics Platform",slug:"data-analytics-platform",description:"Predictive staffing models and ERP integration"}],techDeployment:["In-aisle cameras for shelf compliance; can leverage existing security cams for queues","Handheld devices with tasking workflows; photo evidence for OOS/drift","ERP/WMS adapters via REST/webhooks (SAP, Oracle, Dynamics); real-time tasking","Edge inference for real-time alerts; cloud sync for trend analysis and reporting"],roiProof:[{metric:"18% OSA improvement",description:"Baseline shelf audits vs ShelfSentra alerts; sales lift tracked per category"},{metric:"30% queue walk-off reduction",description:"Queue dwell baseline vs predictive staffing with Queuence"}],faqs:[{question:"Does this integrate with our ERP/WMS?",answer:"Yes. Standard adapters; we validate against your data in PoC before pilot."},{question:"Do we need new cameras?",answer:"Often leverage existing security cams for queues; shelf compliance needs in-aisle angles. We conduct site surveys."},{question:"How do planogram changes work?",answer:"API ingestion or direct upload; drift alerts automated with task generation for corrective actions."},{question:"What's the ROI timeline?",answer:"Quick-win payback 3-5 months through OSA sales lift and reduced audit labor; see ROI calculator for your store volumes."},{question:"How do you measure walk-offs?",answer:"CV tracks queue entry/exit; abandonment rates with dwell time and trend analysis."}],faqLastUpdated:"2025-01-15",seoTitle:"Retail AI & Computer Vision Solutions | Allerin",seoDescription:"Quick-win retail solutions: shelf compliance, queue analytics, inventory scanning. PoC→Pilot 8–12 weeks with KPI gates."},{title:"Insurance & Government",slug:"insurance-government",icon:a,gradient:"from-data-purple to-data-blue",heroSub:"43% faster claims adjudication, 68% document processing lift, and fraud losses down. No core system replacement.",quickWins:["Claims automation & adjudication (ClaimVista)","Compliance document validation (CompliChek)","Government document processing (DocQore)","Insurance fraud detection (FraudLens)"],personas:["Claims Ops","Compliance Teams","Agency IT Directors"],capabilities:["AI","Document Processing","Fraud Detection"],timeToValue:"quick-win",roiUseCases:"genai,analytics",solutions:[{name:"ClaimVista",slug:"claimvista-claims-automation",promise:"Claims automation & adjudication",bullets:["Auto-triage claims by complexity and fraud signals","Extract policy/loss data from photos and PDFs","Route to adjusters with pre-filled worksheets"],timeline:"What you get: Claims classifier · OCR pipeline · Dashboard",deliverables:["Claims classifier model with fraud scoring","OCR pipeline for photos and documents","Adjuster dashboard with pre-filled worksheets","Guidewire/Duck Creek adapters"]},{name:"CompliChek",slug:"complichek-compliance-validation",promise:"Compliance document validation",bullets:["Validate policy docs against state/federal regs","Flag missing disclosures and outdated clauses","Audit trail for SOC 2, HIPAA, FedRAMP"],timeline:"What you get: Compliance engine · Audit dashboard · Export packs",deliverables:["Document validation engine","Compliance rules library (configurable)","Audit trail reports","Exception queue workflow"]},{name:"DocQore",slug:"docqore-document-processing",promise:"Government document processing",bullets:["OCR + NLP for scanned paper, microfilm, PDFs","PII redaction for public records requests","Searchable archive with metadata tagging"],timeline:"What you get: OCR pipeline · Redaction engine · Archive portal",deliverables:["OCR engine with handwriting support","PII redaction pipeline (FOIA/PRA-aligned)","Batch processing scheduler","Quality gates and audit logs"]},{name:"FraudLens",slug:"fraudlens-fraud-detection",promise:"Insurance fraud detection",bullets:["Anomaly detection on claim patterns and networks","Image forensics for staged accidents","Link to SIU workflows and external databases"],timeline:"What you get: Fraud scorer · Investigation queue · API adapters",deliverables:["Fraud detection model with explainability","SIU review console","Override and escalation workflows","Precision/recall KPI dashboard"]}],productsUsed:[{name:"ViSTA",slug:"vista",description:"Document AI for claims processing and compliance validation"},{name:"Data & Analytics Platform",slug:"data-analytics-platform",description:"Fraud detection models and legacy system integration"}],techDeployment:["Claims systems: Guidewire, Duck Creek, Applied Epic via REST/SOAP adapters","Government systems: COTS case management, legacy mainframes via batch/API integration","Security: FedRAMP-ready, NIST 800-53 controls, on-prem or GovCloud deployment options","Privacy: PII masking, configurable retention policies, role-based access, comprehensive audit logs","Infrastructure: Air-gapped deployment for sensitive agencies; commercial cloud for insurance"],roiProof:[{metric:"43% faster claims cycle time",description:"Large P&C insurer reduced auto claims from 18 days to 10.2 days using ClaimVista for photo triage and data extraction"},{metric:"68% document processing improvement",description:"State agency cleared 14-month FOIA backlog in 90 days with DocQore OCR and redaction pipeline"}],faqs:[{question:"Does this integrate with our core claims system?",answer:"Yes. We provide validated adapters for Guidewire, Duck Creek, Applied Epic, and legacy mainframe systems. All integrations are tested during the PoC phase before pilot deployment."},{question:"What about security and compliance (FedRAMP, NIST, HIPAA)?",answer:"We offer FedRAMP-ready deployment options with NIST 800-53 controls and SOC 2 Type II audit compliance. Solutions support on-prem or air-gapped deployment for sensitive government workloads and meet HIPAA requirements for healthcare-related claims."},{question:"How does ClaimVista handle fraud without false positives?",answer:"ClaimVista uses tunable scoring with adjuster override capabilities. All flagged claims route to an SIU review queue before denial. Precision/recall metrics are exposed in the KPI dashboard and continuously monitored."},{question:"Can we deploy on-premises or air-gapped?",answer:"Yes. We support full on-prem deployment for government agencies and GovCloud or commercial cloud options for insurance providers. All data processing and storage can remain within your infrastructure."},{question:"What's the ROI timeline for claims automation?",answer:"Typical payback occurs within one quarter through reduced loss adjustment expenses (LAE) and faster cycle times. Use our ROI calculator to model savings based on your claim volumes."},{question:"How does DocQore handle legacy microfilm and handwritten records?",answer:"DocQore uses advanced OCR with human-in-the-loop validation for low-confidence fields. Accuracy is gated before archive ingestion, with quality metrics tracked per batch."},{question:"What if our adjusters resist AI-assisted workflows?",answer:"ClaimVista augments adjusters rather than replacing them. It pre-fills worksheets so adjusters can focus on judgment calls and customer interaction. Change management support is included in pilot deployment."}],faqLastUpdated:"2025-01-15",seoTitle:"AI Solutions for Insurance & Government: Faster Claims, Compliant Documents, Lower Fraud",seoDescription:"43% faster claims cycle time, 68% document processing lift. ClaimVista, DocQore, CompliChek, FraudLens. FedRAMP-ready. 60-90 day deployment."},{title:"Transportation & Rail",slug:"transportation-rail",icon:n,gradient:"from-data-cyan to-primary",heroSub:"31% fewer track incidents, 40% faster ROW clearance, and thermal failures caught before service disruption. No wayside system replacement.",quickWins:["Right-of-way monitoring & clearance (RailGuard)","Track defect detection (TrackSentinel)","Rolling stock thermal monitoring (FleetTherm)","Signal & switch monitoring (SignalEye)"],personas:["Infrastructure Directors","Safety Managers","Rolling Stock Operations Teams"],capabilities:["Computer Vision","Predictive Maintenance","Safety Analytics"],timeToValue:"quick-win",roiUseCases:"cv,analytics",solutions:[{name:"RailGuard",slug:"railguard-row-monitoring",promise:"Right-of-way monitoring & clearance",bullets:["Vegetation encroachment detection with GPS mapping","Clearance violation alerts (structure gauge, overhead)","Work order generation with severity scoring"],timeline:"60–90 days",deliverables:["Encroachment detection model","GIS violation layer","CMMS adapter","Scan report scheduler"]},{name:"TrackSentinel",slug:"tracksentinel-defect-detection",promise:"Track defect detection (rail, ties, ballast)",bullets:["Defect classification (cracks, wear, ballast fouling)","Priority scoring by defect severity and traffic volume","Inspection log export for FRA compliance"],timeline:"60–90 days",deliverables:["Defect detection model","Severity scorer","FRA inspection logs","Wayside integration"]},{name:"FleetTherm",slug:"fleettherm-thermal-monitoring",promise:"Rolling stock thermal monitoring",bullets:["Thermal anomaly detection on wheels, bearings, brakes","Pre-failure alerts with component-level tracking","Depot integration for scheduled interventions"],timeline:"60–90 days",deliverables:["Thermal anomaly model","Failure prediction","Depot queue integration","KPI dashboard"]},{name:"SignalEye",slug:"signaleye-signal-monitoring",promise:"Signal & switch monitoring",bullets:["Signal aspect verification from wayside cameras","Switch position confirmation with anomaly alerts","PTC integration for automated fault reporting"],timeline:"60–90 days",deliverables:["Signal verification","Switch tracker","PTC API","Alert rules"]}],productsUsed:[{name:"SENTRA",slug:"sentra",description:"Edge CV for wayside cameras and depot thermal imaging; low-latency inference for real-time alerts"},{name:"Data & Analytics Platform",slug:"data-analytics-platform",description:"CMMS integration (Maximo, SAP PM), GIS mapping, FRA reporting"}],techDeployment:["Infrastructure: Wayside cameras (visible + thermal) with edge compute (Jetson/x86), depot-mounted thermal arrays","Integration: CMMS/EAM (Maximo, SAP PM, Infor EAM), GIS (Esri ArcGIS, LRS), PTC (Wabtec, Alstom, Siemens)","Deployment: Cloud for Class II/III carriers, on-prem for Class I railroads, hybrid edge+cloud analytics"],roiProof:[{metric:"31% fewer track incidents",description:"Regional freight railroad reduced track-caused derailments from 13 to 9 annually using TrackSentinel for defect prioritization"},{metric:"40% faster ROW clearance",description:"Commuter rail system cleared 160 vegetation violations in 45 days (vs. 75 days historical) with RailGuard automated work orders"}],faqs:[{question:"Is this FRA-compliant for track inspection reporting?",answer:"Yes. TrackSentinel generates inspection logs aligned with FRA Part 213 (track safety standards). All defect records include GPS, timestamps, severity classification, and inspector override capabilities."},{question:"Can we integrate with our existing wayside detection systems?",answer:"Absolutely. We integrate with Salient, Lynxrail, and other wayside systems via standard protocols (Modbus, OPC-UA, REST APIs). RailGuard and TrackSentinel augment, not replace, existing HBD/WID systems."},{question:"How accurate is thermal monitoring for rolling stock?",answer:"FleetTherm achieves 92-96% accuracy on bearing/wheel thermal anomalies. False positive rates are tunable; all alerts include thermal imagery for maintenance team verification."},{question:"What about PTC integration for signal/switch monitoring?",answer:"SignalEye integrates with Wabtec, Alstom, and Siemens PTC systems via fault reporting APIs. Signal aspect and switch position data can trigger automated PTC alerts or work orders."},{question:"Can we deploy on-prem for data sovereignty?",answer:"Yes. Full on-prem deployment is supported for Class I railroads. All processing and storage remain within your infrastructure with no cloud dependency."},{question:"What's the typical time to first value?",answer:"For ROW monitoring: 4-6 weeks (baseline scans, first violation report). For track defects: 6-8 weeks (PoC with historical imagery, first prioritized work order queue)."},{question:"How do you handle vegetation detection in different seasons?",answer:"RailGuard is trained on multi-season imagery (leaf-on/leaf-off). Seasonal baselines are established during PoC, and model drift is monitored quarterly with retraining triggers."}],faqLastUpdated:"2025-01-15",seoTitle:"Rail & Transportation AI: Track Safety, ROW Monitoring & Predictive Maintenance | Allerin",seoDescription:"31% fewer track incidents, 40% faster ROW clearance. RailGuard, TrackSentinel, FleetTherm, SignalEye. FRA-compliant. 60-90 day deployment."},{title:"Energy & Utilities",slug:"energy-utilities",icon:o,gradient:"from-data-amber to-data-yellow",heroSub:"Line inspections and PV analytics with fewer flights and faster findings.",quickWins:["Line/tower/substation inspections (GridAurex)","Solar PV thermal anomaly detection (HelioLytix)","Leak/flare monitoring (ThermaSentinel)"],personas:["Transmission & Distribution","Renewable Asset Management","Compliance & Safety"],capabilities:["CV","Analytics"],timeToValue:"quick-win",roiUseCases:"cv_inspection,analytics",solutions:[{name:"GridAurex",slug:"gridaurex-line-inspection",promise:"Transmission line inspection with 45% faster cycle times",bullets:["Anomaly detection from drone/helo feeds (corrosion, vegetation, hot spots)","Route-based review queues with priority scoring","Work order export to EAM/CMMS with GPS coordinates"],timeline:"PoC→Pilot 6–8 weeks · KPI gates · reversible rollout",deliverables:["Anomaly detection model trained on historical footage","Reviewer console with priority queues and export to EAM","Integration with drone platforms (DJI, senseFly, etc.)","GIS-based asset mapping and work order generation"]},{name:"HelioLytix",slug:"heliolytix-solar-anomalies",promise:"Solar PV thermal monitoring with 2-8% production recovery",bullets:["Hot-spot and underperforming panel detection from thermal imagery","Panel string mapping with production impact estimates","Maintenance work orders prioritized by revenue loss"],timeline:"PoC→Pilot 4–6 weeks · thermal baseline · first hot-spot report",deliverables:["Thermal anomaly detection model (94% F1 score)","GIS overlay of panel health by string and inverter","Production loss estimates and maintenance prioritization","Integration with monitoring systems (SolarEdge, Huawei, etc.)"]},{name:"ThermaSentinel",slug:"thermasentinel-leak-monitoring",promise:"Leak/flare monitoring with EPA/LDAR compliance",bullets:["Methane and flare anomaly detection from thermal/OGI sensors","Automated regulatory reports with alert timestamps and GPS","Alert tuning and false-positive reduction"],timeline:"PoC→Pilot 6–8 weeks · threshold tuning · first compliance report",deliverables:["Leak detection model (>85% precision) with thermal/OGI integration","EPA/LDAR-compliant report generation with audit trails","Alert prioritization by severity and regulatory risk","Integration with field maintenance systems"]}],productsUsed:[{name:"SENTRA",slug:"sentra",description:"Edge CV for thermal and visible-spectrum anomaly detection"},{name:"Data & Analytics Platform",slug:"data-analytics-platform",description:"GIS integration, EAM hooks, and regulatory reporting"}],techDeployment:["Drone/helicopter integration for aerial inspections","Thermal cameras (FLIR, etc.) for PV and leak detection","GIS integration for asset mapping and work orders","EAM/CMMS integration (SAP, Maximo, etc.)"],roiProof:[{metric:"45% inspection time reduction",description:"Regional utility using GridAurex for transmission line inspections"},{metric:"2-8% production recovery",description:"Solar farm operators with HelioLytix identifying and prioritizing thermal anomalies for remediation"}],faqs:[{question:"Can we use our existing drone/thermal camera providers?",answer:"Yes. GridAurex and HelioLytix integrate with major drone platforms and thermal cameras (FLIR, DJI, etc.). We ingest standard formats (TIFF, MP4, etc.)."},{question:"How do you integrate with our EAM/CMMS?",answer:"We integrate with SAP, Maximo, and other EAM systems via REST APIs. Work orders are created automatically based on anomaly severity and location."},{question:"What's the accuracy for thermal anomaly detection?",answer:"HelioLytix achieves 90-95% accuracy on hot-spot detection in solar PV. ThermaSentinel methane detection varies by sensor resolution but typically >85% precision."},{question:"Can this run on-prem for critical infrastructure?",answer:"Absolutely. All processing can run on-prem with no cloud dependency. Data stays within your infrastructure and control."},{question:"What's the typical time to first value?",answer:"For line inspections: 6-8 weeks (PoC with historical footage). For solar PV: 4-6 weeks (thermal baseline, first hot-spot report)."},{question:"How do you handle regulatory reporting for leak monitoring?",answer:"ThermaSentinel generates automated reports aligned with EPA/LDAR requirements, including alert timestamps, GPS coordinates, and audit trails."}],faqLastUpdated:"2025-01-15",seoTitle:"Energy & Utilities AI Solutions | Allerin",seoDescription:"Line inspections and PV analytics with fewer flights and faster findings. GridAurex, HelioLytix, ThermaSentinel. 60-90 day deployment."}];function s(e){return r.find(i=>i.slug===e)}export{s as g,r as i};