BEGIN:VCALENDAR VERSION:2.0 PRODID:IEEE vTools.Events//EN CALSCALE:GREGORIAN BEGIN:VTIMEZONE TZID:America/New_York BEGIN:DAYLIGHT DTSTART:20260308T030000 TZOFFSETFROM:-0500 TZOFFSETTO:-0400 RRULE:FREQ=YEARLY;BYDAY=2SU;BYMONTH=3 TZNAME:EDT END:DAYLIGHT BEGIN:STANDARD DTSTART:20261101T010000 TZOFFSETFROM:-0400 TZOFFSETTO:-0500 RRULE:FREQ=YEARLY;BYDAY=1SU;BYMONTH=11 TZNAME:EST END:STANDARD END:VTIMEZONE BEGIN:VEVENT DTSTAMP:20260710T140039Z UID:C52A8860-10B2-4985-9B09-B469B635683C DTSTART;TZID=America/New_York:20260706T190000 DTEND;TZID=America/New_York:20260706T200000 DESCRIPTION:Special Presentation by Phani Patelkhana\n\nHosted by the Exper t Tech Talks (IEEE Philadelphia Section)\n\nDate/Time: Monday\, 6 July 202 6 @ 7 PM Eastern Time\n\nTopic:\n\nInfrastructure Over Models: Why Enterpr ise AI Is Really a Control-Plane Problem\n\nAbstract:\n\nEnterprise AI oft en begins with a small and successful pilot: one team\, one model\, one da ta source\, and clearly defined security rules.\n\nAs adoption grows\, dif ferent teams introduce their own models\, data sources\, agent frameworks\ , MCP servers\, and security approaches. Each team may make reasonable cho ices\, but the overall environment can quickly become fragmented and diffi cult to govern.\n\nThis talk examines common patterns across enterprise AI programs and explains why many production risks emerge between systems ra ther than inside the model itself. Sensitive information may be sent to an unapproved model\, user or tenant context may be lost\, applications may apply inconsistent safety policies\, and agents may gain access to tools o r actions beyond what they need.\n\nThe session introduces a practical ref erence architecture built around two shared control points: an AI-aware ga teway that governs how applications interact with models\, and an executio n gateway that controls how agents access tools\, APIs\, MCP servers\, and business systems.\n\nThe talk also explores how organizations can apply c onsistent policies\, protect sensitive data\, preserve trusted identity co ntext\, approve high-risk actions\, and monitor model and tool usage—wit hout forcing every team to use the same model or application framework.\n\ nSpeaker:\n\nVenkata Phani Patelkhana is an IEEE Senior Member and Disting uished Engineer at Dell Technologies\, with more than 19 years of experien ce in enterprise API platforms\, distributed systems\, API security\, and agentic AI architectures.\n\nHis current work focuses on AI control planes \, MCP gateways\, agent identity\, runtime authorization\, and helping ent erprises transition safely from API-first to agent-first ecosystems. He ho lds patents related to decentralized API gateway architectures and regular ly writes and speaks about practical approaches to securing and governing enterprise API and AI ecosystems.\n\nCo-sponsored by: IEEE Future Networks AI/ML Working Group\n\nVirtual: https://events.vtools.ieee.org/m/565135 LOCATION:Virtual: https://events.vtools.ieee.org/m/565135 ORGANIZER:rachitjain4444@gmail.com SEQUENCE:15 SUMMARY:Expert Tech Talks - Infrastructure Over Models: Why Enterprise AI I s Really a Control-Plane Problem URL;VALUE=URI:https://events.vtools.ieee.org/m/565135 X-ALT-DESC:Description: <br /><p class="MsoNormal" style="margin-top: 12.0p t\;">Special Presentation by<strong> Phani Patelkhana</strong></p>\n<p cla ss="MsoNormal" style="margin-top: 12.0pt\;">Hosted by the Expert Tech Talk s (IEEE Philadelphia Section)</p>\n<p class="MsoNormal" style="margin-top: 12.0pt\;"><strong><span style="font-size: 14.0pt\; font-family: Copperpla te\; mso-fareast-font-family: PMingLiU\; mso-fareast-theme-font: minor-far east\; mso-bidi-font-family: Arial\; mso-bidi-theme-font: minor-bidi\; mso -ansi-language: EN-US\; mso-fareast-language: ZH-TW\; mso-bidi-language: A R-SA\;">Date/Time</span></strong><span style="font-size: 12.0pt\; font-fam ily: 'Calibri'\,sans-serif\; mso-ascii-theme-font: minor-latin\; mso-farea st-font-family: PMingLiU\; mso-fareast-theme-font: minor-fareast\; mso-han si-theme-font: minor-latin\; mso-bidi-font-family: Arial\; mso-bidi-theme- font: minor-bidi\; mso-ansi-language: EN-US\; mso-fareast-language: ZH-TW\ ; mso-bidi-language: AR-SA\;">: <strong>Monday\, 6 July 2026</strong><stro ng> @ 7 PM Eastern Time</strong></span></p>\n<p class="MsoNormal" style="m argin-top: 12.0pt\;"><span style="font-size: 12.0pt\; font-family: 'Calibr i'\,sans-serif\; mso-ascii-theme-font: minor-latin\; mso-fareast-font-fami ly: PMingLiU\; mso-fareast-theme-font: minor-fareast\; mso-hansi-theme-fon t: minor-latin\; mso-bidi-font-family: Arial\; mso-bidi-theme-font: minor- bidi\; mso-ansi-language: EN-US\; mso-fareast-language: ZH-TW\; mso-bidi-l anguage: AR-SA\;"><strong><img src="https://events.vtools.ieee.org/vtools_ ui/media/display/ae3f3e64-8a3c-4cb6-a3d7-37009d5b7996"></strong></span></p >\n<p class="MsoNormal" style="margin-top: .25in\;"><strong><u><span style ="font-size: 16.0pt\; font-family: Copperplate\;">Topic</span></u></strong ><strong><span style="font-size: 16.0pt\; font-family: Copperplate\;">:</s pan></strong></p>\n<h3><span role="text"><strong>Infrastructure Over Model s: Why Enterprise AI Is Really a Control-Plane Problem</strong></span></h3 >\n<p class="MsoNormal" style="margin-top: .25in\;"><strong><u><span style ="font-size: 16.0pt\; font-family: Copperplate\;">Abstract</span></u></str ong><strong><span style="font-size: 16.0pt\; font-family: Copperplate\;">: </span></strong></p>\n<p>Enterprise AI often begins with a small and succe ssful pilot: one team\, one model\, one data source\, and clearly defined security rules.</p>\n<p>As adoption grows\, different teams introduce thei r own models\, data sources\, agent frameworks\, MCP servers\, and securit y approaches. Each team may make reasonable choices\, but the overall envi ronment can quickly become fragmented and difficult to govern.</p>\n<p>Thi s talk examines common patterns across enterprise AI programs and explains why many production risks emerge between systems rather than inside the m odel itself. Sensitive information may be sent to an unapproved model\, us er or tenant context may be lost\, applications may apply inconsistent saf ety policies\, and agents may gain access to tools or actions beyond what they need.</p>\n<p>The session introduces a practical reference architectu re built around two shared control points: an AI-aware gateway that govern s how applications interact with models\, and an execution gateway that co ntrols how agents access tools\, APIs\, MCP servers\, and business systems .</p>\n<p>The talk also explores how organizations can apply consistent po licies\, protect sensitive data\, preserve trusted identity context\, appr ove high-risk actions\, and monitor model and tool usage&mdash\;without fo rcing every team to use the same model or application framework.</p>\n<p>< strong><span style="font-size: 16.0pt\; font-family: Copperplate\;"><u>Spe aker</u>:</span></strong></p>\n<table style="border-collapse: collapse\; w idth: 100%\;" border="1"><colgroup><col style="width: 28.878049%\;"><col s tyle="width: 71.02439%\;"></colgroup>\n<tbody>\n<tr>\n<td><img src="https: //events.vtools.ieee.org/vtools_ui/media/display/c87357b3-8867-47f0-982c-5 2ea94162082" width="264" height="264"></td>\n<td>\n<p>&nbsp\;</p>\n<p>Venk ata Phani Patelkhana is an IEEE Senior Member and Distinguished Engineer a t Dell Technologies\, with more than 19 years of experience in enterprise API platforms\, distributed systems\, API security\, and agentic AI archit ectures.</p>\n<p>His current work focuses on AI control planes\, MCP gatew ays\, agent identity\, runtime authorization\, and helping enterprises tra nsition safely from API-first to agent-first ecosystems. He holds patents related to decentralized API gateway architectures and regularly writes an d speaks about practical approaches to securing and governing enterprise A PI and AI ecosystems.</p>\n<p>&nbsp\;</p>\n</td>\n</tr>\n</tbody>\n</table >\n<p>&nbsp\;</p> END:VEVENT END:VCALENDAR