Private Network Site Survey Readiness Checklist for Manufacturing
Before commissioning an RF survey or engaging a deployment partner, confirm your site is ready. This tool diagnoses your readiness across six domains, flags information gaps and deployment blockers, and generates a manufacturing-specific site survey checklist, required documents list, and field validation sequence.
Consultant-grade AI prioritisation for discrete and process manufacturers - OT integration complexity, brownfield weighting, and 10 factory-specific use cases.
25+ continuously updated decision cards covering factory automation, robotics, IIoT, and Industry 4.0 strategies backed by real evidence from global private network deployments.
Transparent 5-year financial model for private LTE or 5G in manufacturing - 8 use cases, industry deployment benchmarks, annual cashflow, and full methodology disclosure.
Select from 5 use cases โ AMR, Cobots, AR, predictive maintenance โ and enter factory revenue and headcount. Returns 5-year ROI and payback period. Based on Ericsson/Hexagon/ADL study.
17 questions across region, vertical, devices, spectrum, and commercial model - returns a consultant-grade technology recommendation with rationale and vendor guidance.
15 questions to determine the right deployment architecture - SNPN, enterprise RAN, managed breakout, or hybrid - with responsibility matrix and vendor engagement sequence.
Get a planning-grade estimate of how many radios your private network deployment will likely require - and whether coverage or capacity is the binding constraint. Produces a range based on your site area, environment complexity, spectrum band, device mix, and use case profile. Useful for budget sizing and vendor conversations before formal RF design.
Generate a structured, weighted vendor evaluation framework for your private network procurement. Calibrated to your vertical, use cases, architecture, compliance requirements, and procurement priorities. Produces a weighted scorecard, vendor question bank, red flags, required proof points, and evaluation process guide.
Translate your operational use cases into precise technical SLA requirements - latency, jitter, throughput, availability, QoS class, handover, redundancy, and spectrum implications. Built for enterprise architects, OT/IT teams, and procurement teams specifying private network requirements.
Independent 5-year TCO comparison for enterprise wireless networks, covering hardware, installation, spectrum, management, and operating costs across Wi-Fi, CBRS, private LTE, and private 5G. Built on TeckNexus intelligence, published research, deployment benchmarks, and region-specific cost assumptions. Calibrated by region, site type, and deployment environment.
How resilient is your network against today's threat landscape - signalling protocol attacks, AI-weaponised social engineering, ransomware, inter-roaming exploits, and 5G-specific vulnerabilities? This assessment benchmarks your security posture across five dimensions: threat awareness, network architecture, detection and response, AI and automation, and governance.
Compare total cost of ownership across private wireless connectivity options. Input operational parameters to model TCO over a multi-year period and identify the lowest-cost architecture for your environment.
Side-by-side comparison tool for private wireless technology options - LTE, 5G, Wi-Fi, and CBRS - across key performance, cost, and operational dimensions to support technology selection decisions.
Deployment-backed analysis of CBRS total cost of ownership across multiple industries. Provides real-world ROI benchmarks from live CBRS deployments โ useful for validating business cases and comparing against vendor estimates.
Quick-estimate tool for private 5G deployment costs. Input site size, device count, and coverage requirements to get an indicative infrastructure cost range - useful for early-stage budget planning.
Estimate the sustainability impact of deploying private wireless โ including energy efficiency gains, carbon reduction, and ESG reporting metrics - across industrial and enterprise environments.
Model the total cost of ownership of deploying Celona's 5G LAN solution versus existing Wi-Fi or wired infrastructure. Useful for enterprise and industrial sites evaluating CBRS-based private 5G.
Search US licensed spectrum availability by frequency, geography, and licensee. Essential for US-based private network spectrum planning and CBRS/PAL availability checks.
Compare on-premises infrastructure costs against AWS cloud deployment. Useful for modelling edge AI and private network core cloud migration scenarios.
Model infrastructure costs for on-premises vs Azure cloud. Relevant for enterprises evaluating hybrid private network and AI workload deployments on Azure edge.
Use structured tools built from real deployment evidence to select technologies, prioritise use cases, and build the business case โ without weeks of research or expensive consulting.
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Understand what enterprise buyers are evaluating, where deployment decisions are heading, and how your deployment approaches align with what the market actually needs.
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Is Wi-Fi really cheaper than private 5G? It depends on your site. The TeckNexus Private Network TCO Comparator models five-year capex and opex across Wi-Fi 6, CBRS, Licensed Private LTE, and Private 5G SA โ for your specific environment, scale, and use case.
Deciding how to structure your private network deployment is as important as picking the technology. TeckNexus's free Architecture Selector asks 15 questions and tells you who should own what, where your data sits, and how to engage vendors โ vendor-neutral and free.
T-Mobile and Ericsson are delivering measurable AI-native RAN results at commercial scale on a live 5G Advanced network. Ericsson's AI-native Scheduler with Link Adaptation replaces rule-based logic with a neural network that predicts RF conditions in real time, achieving close to 10 percent spectral efficiency improvement and up to 15 percent downlink throughput gains. Separately, Ericsson validated its Cloud RAN software running on NVIDIA AI infrastructure, enabling hardware-agnostic deployment. Together, these advances signal that AI-native networking is no longer theoretical โ it is executing at national scale.
Samsung Electronics and Qualcomm Technologies have jointly validated Power Class 1 capability for 5G Fixed Wireless Access on a virtualized RAN architecture โ a combination the industry has not demonstrated before. Testing showed up to ten times higher uplink throughput at the cell edge and up to 40% greater coverage range versus Power Class 1.5. With field trials already underway on a U.S. Tier-1 operator network and commercial availability targeted for 2027, this milestone signals a meaningful shift in uplink performance, coverage economics, and vRAN capability for operators and enterprise buyers alike.
April 2026 was one of the most active months on record for private 5G and LTE. Across factory floors, mine sites, stadiums, utility grids, and remote film locations, the private network ecosystem moved on every front simultaneously. This month's update covers 18 deployment updates, 7 partnerships, 9 industry analyses, 14 feature updates, 4 spectrum and policy developments, and 3 award updates.
Samsung Electronics is accelerating its U.S. foundry strategy with the Taylor plant set to begin operations, anchored by 2-nanometer AI chips for Teslaโs next-generation self-driving platforms. After breaking ground in late 2022 with an initial $17 billion investment, Samsungโs Taylor fab is now holding its equipment installation ceremony and transitioning from build-out to run-up. For the U.S. semiconductor base, Taylor represents an advanced-node capacity point that complements Samsungโs existing Austin operations and expands domestic options beyond a single supplier. Teslaโs AI5 design has taped out, signaling it is ready for volume manufacturing, with AI6 following closely and expected to incorporate low-power DDR (LPDDR) memory to meet stringent automotive power budgets.
AT&Tโs new collaboration with Cisco and NVIDIA signals a decisive shift from cloud-centric AI to network-driven edge intelligence for enterprise operations. Enterprises want real-time decisioning without shipping sensitive data to distant clouds, and operators need a scalable way to deliver it. By combining AT&Tโs dedicated IoT core with Ciscoโs mobility services platform and NVIDIA-powered AI infrastructure, the trio is packaging deterministic connectivity, near-device inference, and policy enforcement into a single, operator-grade platform. The promise: lower latency, tighter data control, and a path to production for AI at industrial scale.
NTT DOCOMO and Keio University have validated that commercial 5G Standalone (SA) can stably support haptic-grade robot teleoperation using network slicing and configured grantโturning years of URLLC theory into practical results. By pairing 3GPP-configured grant scheduling with a low-latency slice and Keioโs Real Haptics technology, DOCOMO showed that public 5G SA can carry force and tactile feedback with the determinism required for safe, precise manipulation. The KPIs demonstrate material improvements in latency stability, force fidelity, and motion smoothnessโindicators that the control loop is resilient enough for practical tasks.
NTT DATAโs private 5G rollout across 50 Cargill facilities signals that industrial connectivity is moving from pilot projects to standardized, multi-site execution. NTT DATA has deployed private 5G at Cargill manufacturing and processing locations worldwideโmostly in the United States with live sites in Europeโenabling a connected workforce, robotics, and edge AI across plants that are often too large and complex for conventional WiโFi or wired networks to cover reliably. Manufacturers are consolidating on common digital platforms and need predictable, low-latency wireless for operational data, mobile humanโmachine interfaces, and autonomous systems; private 5Gโbuilt on 3GPP standards with SIM-based security and policy-based QoSโoffers deterministic performance at scale where legacy networks struggle.
Frequently Asked Questions
About our tools, how they are built, and how to get involved.
TeckNexus Independent Tools
TeckNexus independent tools are assessments, selectors, ROI calculators, and AI prioritisation tools developed entirely by TeckNexus. The methodology, scoring logic, and outputs are owned by TeckNexus โ no vendor funds, influences, or has visibility into individual results. They are free to complete. Accessing the full output and PDF report requires registration.
No. TeckNexus owns the methodology, scoring, and output logic for all independent tools. No vendor has paid to influence recommendations or results. If a vendor is referenced in an output โ for example, as a category of solution โ it is because the evidence supports it, not because of a commercial relationship.
Registration allows TeckNexus to generate and deliver a personalised PDF report, track your results if you return, and โ with your permission โ notify you of updated benchmarks or relevant intelligence. Registration is free. Your data is not shared with any vendor without your explicit consent.
Individual submission data is held by TeckNexus and not shared with any third party without your explicit consent. Aggregated and anonymised data may be used to produce industry benchmark reports. No personally identifiable information is included in any published output.
All tools labelled TeckNexus in the directory โ including the Private Network Technology Selector, Private Network Architecture Selector, AI Use Case Prioritisers (Manufacturing, Mining, Ports, Airports, Utilities), and the Private Network ROI Calculators (Manufacturing, Mining). More tools are added regularly.
Co-Developed & Sponsored Tools
Co-developed tools are built by TeckNexus in partnership with an industry sponsor. The sponsor co-funds development and is clearly disclosed on the tool. TeckNexus owns the methodology, platform, and output logic โ the sponsor does not influence scoring or results. These tools are free for users to complete.
Your contact details may be shared with the named sponsor โ but only with your explicit consent at the point of form submission. Your results and individual response data are not shared. The consent step is clearly presented before submission.
No. Sponsorship funds the development and hosting of the tool โ it does not influence the methodology, scoring, or outputs. TeckNexus retains full editorial control. Sponsored tools go through the same methodology review as independent tools.
Yes. TeckNexus works with vendors, operators, and industry bodies to co-develop tools that serve enterprise decision-makers. Use the partner enquiry form on this page to tell us what you have in mind โ tool category, target vertical, and what you are trying to achieve. We will get back to you to discuss fit and next steps.
Third-Party Tools (Curated Directory)
Third-party tools are ROI calculators, TCO models, decision aids, and planning resources produced by vendors, operators, or industry bodies. They are included in the TeckNexus directory because they offer genuine utility to enterprise decision-makers โ but they are clearly labelled as vendor-produced. TeckNexus curates the directory and does not endorse any individual tool or vendor.
Tools are assessed for relevance, utility, and credibility. We look for tools that offer meaningful input fields and substantive outputs โ not marketing calculators with fixed results. Listing is not paid placement. Any vendor can submit a tool for consideration using the form on this page.
Standard directory listings are unpaid. TeckNexus does not accept payment to influence which third-party tools are listed or how they are described. Separate commercial arrangements exist for co-developed and sponsored tools, which are clearly labelled as such.
Use the tool submission form at the bottom of this page. You will need to provide tool details, vendor information, and confirm that you are authorised to submit on behalf of the organisation. TeckNexus reviews all submissions before listing.
Vertical Intelligence Platforms (Paid)
Each Vertical Intelligence Platform is a structured set of 25+ decision cards built from TeckNexus analysis of real enterprise private network deployments. They cover a specific industry โ Manufacturing, Mining, Ports, Airports โ and are organised into six sections: vertical overview, business priorities and use cases, private wireless strategy, proof and ecosystem, decision framework, and deployment readiness. They are updated continuously as new deployments emerge.
A subscription to one vertical gives you access to all 25+ decision cards for that industry, continuous updates as new deployments are analysed, and the ability to share access across your team. Each card is structured around a specific decision โ use case selection, vendor shortlisting, deployment model, ROI prioritisation โ so you can navigate directly to what you need.
A research report gives you a snapshot at a point in time. The Vertical Intelligence Platform is continuously updated and structured around decisions, not narrative. Instead of reading a 60-page PDF, you navigate directly to the card relevant to your current question โ vendor selection, use case validation, deployment model โ and get evidence-backed guidance without the research overhead.
No. Each vertical is subscribed to separately at $1,200 per year. This keeps pricing proportionate to what you actually need. If you require multiple verticals, contact us to discuss multi-vertical access.
Yes. Each vertical has a sample platform available โ accessible from the tool cards on this page. The sample gives you a representative selection of decision cards so you can assess the depth and format before committing.
The platforms are built for enterprise technology and operations teams evaluating private network investment, vendors building go-to-market strategies for specific industries, and consultants or system integrators advising clients on deployment options. They are also used by telcos and managed service providers tracking enterprise buyer priorities by vertical.
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