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It combines automated diagnostics, secure data collection, and local AI assisted analysis to help support engineers identify network issues faster while simplifying the troubleshooting experience for users.","\u002Fcontent\u002Fimages\u002F2026\u002F06\u002Fconniva-backend-demo-1.png","2026-06-30T10:34:43.000+08:00",[],2,"\u003Cp>Over the past few months I've been building \u003Cstrong>Conniva\u003C\u002Fstrong>, a platform born out of a problem I've encountered countless times during support sessions.\u003C\u002Fp>\u003Cp>When a customer reports a connectivity issue, support engineers often spend the first 20 to 30 minutes gathering the same information over and over again. Checking DNS, identifying NAT behavior, detecting VPNs, collecting system information, and running connectivity tests before they can even begin investigating the actual problem.\u003C\u002Fp>\u003Cp>I wanted to streamline that process.\u003C\u002Fp>\u003Cfigure class=\"kg-card kg-video-card kg-width-wide\" data-kg-thumbnail=\"https:\u002F\u002Fghost.jdneer.com\u002Fcontent\u002Fmedia\u002F2026\u002F06\u002F2026-06-29-22-36-13_thumb.jpg\" data-kg-custom-thumbnail>\n            \u003Cdiv class=\"kg-video-container\">\n                \u003Cvideo src=\"https:\u002F\u002Fghost.jdneer.com\u002Fcontent\u002Fmedia\u002F2026\u002F06\u002F2026-06-29-22-36-13.mp4\" poster=\"https:\u002F\u002Fimg.spacergif.org\u002Fv1\u002F3840x2336\u002F0a\u002Fspacer.png\" width=\"3840\" height=\"2336\" playsinline preload=\"metadata\" controls>\u003C\u002Fvideo>\n                \u003Cdiv class=\"kg-video-overlay\">\n                    \u003Cbutton class=\"kg-video-large-play-icon\" aria-label=\"Play video\">\n                        \u003Csvg xmlns=\"http:\u002F\u002Fwww.w3.org\u002F2000\u002Fsvg\" viewbox=\"0 0 24 24\">\n                            \u003Cpath d=\"M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z\">\u003C\u002Fpath>\n                        \u003C\u002Fsvg>\n                    \u003C\u002Fbutton>\n                \u003C\u002Fdiv>\n                \u003Cdiv class=\"kg-video-player-container\">\n                    \u003Cdiv class=\"kg-video-player\">\n                        \u003Cbutton class=\"kg-video-play-icon\" aria-label=\"Play video\">\n                            \u003Csvg xmlns=\"http:\u002F\u002Fwww.w3.org\u002F2000\u002Fsvg\" viewbox=\"0 0 24 24\">\n                                \u003Cpath d=\"M23.14 10.608 2.253.164A1.559 1.559 0 0 0 0 1.557v20.887a1.558 1.558 0 0 0 2.253 1.392L23.14 13.393a1.557 1.557 0 0 0 0-2.785Z\">\u003C\u002Fpath>\n                            \u003C\u002Fsvg>\n                        \u003C\u002Fbutton>\n                        \u003Cbutton class=\"kg-video-pause-icon kg-video-hide\" aria-label=\"Pause video\">\n                            \u003Csvg xmlns=\"http:\u002F\u002Fwww.w3.org\u002F2000\u002Fsvg\" viewbox=\"0 0 24 24\">\n                                \u003Crect x=\"3\" y=\"1\" width=\"7\" height=\"22\" rx=\"1.5\" ry=\"1.5\">\u003C\u002Frect>\n                                \u003Crect x=\"14\" y=\"1\" width=\"7\" height=\"22\" rx=\"1.5\" ry=\"1.5\">\u003C\u002Frect>\n                            \u003C\u002Fsvg>\n                        \u003C\u002Fbutton>\n                        \u003Cspan class=\"kg-video-current-time\">0:00\u003C\u002Fspan>\n                        \u003Cdiv class=\"kg-video-time\">\n                            \u002F\u003Cspan class=\"kg-video-duration\">0:30\u003C\u002Fspan>\n                        \u003C\u002Fdiv>\n                        \n                        \u003Cbutton class=\"kg-video-playback-rate\" aria-label=\"Adjust playback speed\">1×\u003C\u002Fbutton>\n                        \u003Cbutton class=\"kg-video-unmute-icon\" aria-label=\"Unmute\">\n                            \u003Csvg xmlns=\"http:\u002F\u002Fwww.w3.org\u002F2000\u002Fsvg\" viewbox=\"0 0 24 24\">\n                                \u003Cpath d=\"M15.189 2.021a9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h1.794a.249.249 0 0 1 .221.133 9.73 9.73 0 0 0 7.924 4.85h.06a1 1 0 0 0 1-1V3.02a1 1 0 0 0-1.06-.998Z\">\u003C\u002Fpath>\n                            \u003C\u002Fsvg>\n                        \u003C\u002Fbutton>\n                        \u003Cbutton class=\"kg-video-mute-icon kg-video-hide\" aria-label=\"Mute\">\n                            \u003Csvg xmlns=\"http:\u002F\u002Fwww.w3.org\u002F2000\u002Fsvg\" viewbox=\"0 0 24 24\">\n                                \u003Cpath d=\"M16.177 4.3a.248.248 0 0 0 .073-.176v-1.1a1 1 0 0 0-1.061-1 9.728 9.728 0 0 0-7.924 4.85.249.249 0 0 1-.221.133H5.25a3 3 0 0 0-3 3v2a3 3 0 0 0 3 3h.114a.251.251 0 0 0 .177-.073ZM23.707 1.706A1 1 0 0 0 22.293.292l-22 22a1 1 0 0 0 0 1.414l.009.009a1 1 0 0 0 1.405-.009l6.63-6.631A.251.251 0 0 1 8.515 17a.245.245 0 0 1 .177.075 10.081 10.081 0 0 0 6.5 2.92 1 1 0 0 0 1.061-1V9.266a.247.247 0 0 1 .073-.176Z\">\u003C\u002Fpath>\n                            \u003C\u002Fsvg>\n                        \u003C\u002Fbutton>\n                        \n                    \u003C\u002Fdiv>\n                \u003C\u002Fdiv>\n            \u003C\u002Fdiv>\n            \n        \u003C\u002Ffigure>\u003Cp>At the heart of Conniva is a lightweight, cross platform probe distributed as a single executable. The user simply runs it, it performs a comprehensive series of network diagnostics, collects relevant (mostly anonymous) system information, and securely uploads the results to an encrypted backend.\u003C\u002Fp>\u003Cp>Instead of exchanging log files or walking users through lengthy troubleshooting steps, the user simply shares a generated token with support. The engineer can immediately access that diagnostic session, complete with visualized results and the underlying raw JSON.\u003C\u002Fp>\u003Cfigure class=\"kg-card kg-image-card kg-width-wide\">\u003Cimg src=\"\u002Fcontent\u002Fimages\u002F2026\u002F06\u002Fconniva-backend-demo-2.png\" class=\"kg-image\" alt=\"\" loading=\"lazy\" width=\"2000\" height=\"1151\" srcset=\"\u002Fcontent\u002Fimages\u002Fsize\u002Fw600\u002F2026\u002F06\u002Fconniva-backend-demo-2.png 600w, \u002Fcontent\u002Fimages\u002Fsize\u002Fw1000\u002F2026\u002F06\u002Fconniva-backend-demo-2.png 1000w, \u002Fcontent\u002Fimages\u002Fsize\u002Fw1600\u002F2026\u002F06\u002Fconniva-backend-demo-2.png 1600w, \u002Fcontent\u002Fimages\u002Fsize\u002Fw2400\u002F2026\u002F06\u002Fconniva-backend-demo-2.png 2400w\" sizes=\"(min-width: 1200px) 1200px\" \u002F>\u003C\u002Ffigure>\u003Cp>To speed up the initial investigation, Conniva also integrates a locally hosted LLM that analyzes the collected diagnostics together with the user's problem description. It doesn't replace the engineer, but it does provide a useful starting point that can significantly reduce investigation time.\u003C\u002Fp>\u003Cp>Conniva is built around a modular architecture. There are currently \u003Cstrong>16 of 32 planned diagnostic modules\u003C\u002Fstrong> implemented, including:\u003C\u002Fp>\u003Cul>\u003Cli>RFC 5389\u002F5780 compliant NAT behavior classification\u003C\u002Fli>\u003Cli>SIP, RTP and RTSP diagnostics\u003C\u002Fli>\u003Cli>VPN detection and classification\u003C\u002Fli>\u003Cli>DNS and connectivity analysis\u003C\u002Fli>\u003Cli>System and interface inspection\u003C\u002Fli>\u003Cli>Additional network diagnostics currently under development\u003C\u002Fli>\u003C\u002Ful>\u003Cp>The NAT analyzer module builds upon \u003Cstrong>NatTypeTester-NG\u003C\u002Fstrong> and is now fully integrated into Conniva.\u003C\u002Fp>\u003Cp>\u003Ca href=\"https:\u002F\u002Fgit.jdneer.com\u002Fjd\u002FNatTypeTester-NG?ref=ghost.jdneer.com\">https:\u002F\u002Fgit.jdneer.com\u002Fjd\u002FNatTypeTester-NG\u003C\u002Fa>\u003C\u002Fp>\u003Cp>Conniva is already proving to be a huge time saver during support sessions, and there's still plenty more to build. I'm looking forward to completing the remaining modules and rolling it out with some of our larger customers.\u003C\u002Fp>\u003Cp>More updates to come.\u003C\u002Fp>","A sneak peek at Conniva, a new network diagnostics platform I'm building. It combines automated diagnostics, secure data collection, and local AI assisted...",{"src":60,"width":67,"height":68,"type":69},2000,1151,"image\u002Fpng",{"name":71,"url":10,"owner":5},"JD Bungart",[],{"left":15,"top":15,"width":26,"height":26,"rotate":15,"vFlip":13,"hFlip":13,"body":74},"\u003Cpath fill=\"none\" stroke=\"currentColor\" stroke-linecap=\"round\" stroke-linejoin=\"round\" stroke-width=\"2\" d=\"M5 12h14M5 12l6 6m-6-6l6-6\"\u002F>",{"left":15,"top":15,"width":26,"height":26,"rotate":15,"vFlip":13,"hFlip":13,"body":76},"\u003Cg fill=\"none\" stroke=\"currentColor\" stroke-linecap=\"round\" stroke-linejoin=\"round\" stroke-width=\"2\">\u003Cpath d=\"M6.5 7.5a1 1 0 1 0 2 0a1 1 0 1 0-2 0\"\u002F>\u003Cpath d=\"M3 6v5.172a2 2 0 0 0 .586 1.414l7.71 7.71a2.41 2.41 0 0 0 3.408 0l5.592-5.592a2.41 2.41 0 0 0 0-3.408l-7.71-7.71A2 2 0 0 0 11.172 3H6a3 3 0 0 0-3 3\"\u002F>\u003C\u002Fg>"]