The transition of the automotive retail sector into the “Agentic Era” is no longer a speculative future but a current operational reality. In early 2026, the industry sits at a critical technical inflection point where the sheer volume of customer data and the complexity of modern dealership management systems (DMS) have outpaced the capacity of traditional human staffing models.¹ Automotive dealerships, which represent a trillion-dollar backbone of the American economy, have historically struggled with a consumer experience tethered to 20th-century manual workflows.¹ This structural lag is characterized by fragmented communication tools, high annual staff turnover exceeding 80%, and a consistent 15% to 30% missed-call rate that leads to direct revenue attrition.⁵

The emergence of Mia Labs and its recent $20 million Series A funding round signifies a shift toward what industry analysts term “disciplined orchestration”—the integration of AI-native agents that do not merely assist but act as autonomous “Super Employees”.¹ This report examines the technical architecture, market positioning, and strategic implications of Mia Labs within the broader 2026 enterprise AI landscape, particularly as the industry converges for the NADA 2026 Show in Las Vegas.

The Crisis of Fragmentation in Automotive Retail

To understand the necessity of Mia Labs’ platform, one must first analyze the deep-seated fragmentation within the dealership technology stack. For decades, automotive retail has operated on a patchwork of disconnected systems. A single rooftop might employ a DMS for accounting and inventory, a CRM for lead management, a separate third-party scheduler for the service department, and a legacy IVR for phone routing.¹ These systems rarely communicate in real-time, creating a “data silos” effect that forces human employees to act as manual bridges—copying data from one screen to another while customers wait on hold.¹

The human cost of this fragmentation is significant. Staffing challenges and high turnover rates create an environment of inconsistent customer service.⁶ When an advisor is overwhelmed or out for the day, calls go to voicemail or, worse, remain unanswered. Data suggests that after-hours and weekend inquiries often go unaddressed until the next business day, by which time a motivated car buyer has likely moved on to a competitor.⁶ In 2025, dealerships using traditional methods saw a persistent “leak” in their sales and service pipelines due to these operational gaps.⁶

Mia Labs: The Architectural Shift to AI-Native Operations

Founded in 2023, Mia Labs represents a new breed of technology company that prioritizes “vertical AI”—systems built specifically for the nuances of a single industry rather than general-purpose models.⁴ The company’s leadership team, including Brian Hoang, Kelvin Pho, and Marwan Kodeih, brings a combined 100 years of automotive experience, ensuring that the AI architecture addresses real-world dealer pain points rather than theoretical use cases.¹

The Technical Maturity of the “AI Super Employee”

The term “Super Employee” is an intentional departure from the “chatbot” moniker. In the 2026 enterprise context, a chatbot is an interface; an AI agent is infrastructure.¹¹ Mia’s platform is designed to perform autonomous tasks that traditionally required human cognition and system access. This includes checking live inventory for specific vehicle configurations, understanding service “op-codes” to schedule maintenance accurately, and navigating the complexities of multi-departmental call routing.⁶

A critical technical benchmark for Mia Labs is the “AI Maturity Test,” a vetting checklist shared by CTO Kelvin Pho for dealerships evaluating modern technology. This test focuses on three core pillars: latency, safety, and integration depth.⁸

• Latency Benchmarks: Mia operates with a human-like latency of sub-2 seconds.⁹ In conversational AI, the “P90 latency”—the speed at which 90% of interactions occur—is the primary driver of customer trust. Long pauses or lag times signal to the caller that they are talking to a machine, often leading to frustration and hang-ups. Mia’s architecture, built on Microsoft Azure, utilizes advanced interruption and turn-detection algorithms to maintain a natural flow.⁸
• Safety and Content Controls: Operating in a high-stakes environment like automotive sales requires robust guardrails. Mia utilizes bank-level security and systems like Microsoft Defender for Cloud to prevent “AI hallucinations” or rogue behavior.⁸ This is essential for maintaining brand integrity and ensuring that the AI does not offer unauthorized discounts or incorrect vehicle specifications.⁸
• Integration Depth: The true power of the Mia platform lies in its ability to connect with over 35 systems across the DMS, CRM, and scheduling categories.⁶ This includes deep bi-directional integrations with industry standards such as CDK Global, Reynolds & Reynolds, Tekion, and Xtime.⁶

Performance Data and Revenue Impact

By the end of 2025, the impact of Mia’s agentic approach was measurable across its footprint of 350+ franchise dealerships.¹ The company reported that its AI powered more than 1 million customer conversations, leading to over 130,000 sales and service appointments.¹ This volume translated into approximately $45 million in enabled dealership revenue from AI-booked appointments alone.¹

For the service department, Mia has demonstrated a 30% appointment booking rate, effectively turning routine inquiries into scheduled revenue without hold times.¹² On average, dealerships utilizing Mia’s service agents generate an additional $50,000 in monthly revenue.⁹ This is achieved by maximizing service bay utilization—filling slots that might otherwise remain empty due to missed calls or delayed human follow-up.¹²

The 2026 Strategic Funding: A Market Signal

The $20 million Series A announced in January 2026 is a significant marker for the automotive tech sector. Led by Permanent Capital Ventures, the round reflects a broader trend in venture capital where investors are moving away from general-purpose AI toward specialized platforms with proven ROI and deep vertical integration.¹

Permanent Capital Ventures and the Human Connection

Mike Gamson, Managing Partner at Permanent Capital Ventures, brings a unique perspective to this investment. Having scaled LinkedIn’s global revenue functions, Gamson prioritizes the intersection of technology and human connection.¹⁴ His investment thesis for Mia Labs is rooted in the belief that AI should not replace human employees but should remove the “operational friction” that prevents humans from doing their best work.¹

This capital infusion positions Mia Labs as a dominant player in the “Automotive AI Cagematch,” a term used to describe the intense competition among vendors like Impel, Stella, and Pinewood as they vie for market share at NADA 2026.⁹

The 7CTOs Influence: Technical Leadership and the Agentic Blueprint

A significant component of Mia Labs’ credibility within the technical community stems from its involvement with 7CTOs, an organization dedicated to the professional and emotional development of Chief Technology Officers.¹⁶ Kelvin Pho, CTO and co-founder of Mia Labs, is an active member and speaker within the 7CTOs community, often sharing tactical insights on how to move from “hype” to “infrastructure”.⁸

The CTO’s “Maturity Test” for AI Agents

During the 13th CTO Colloquium in Austin, Pho presented a session titled “Off the Hook: Agentic Calls, Texts, and Customer Experience,” where he outlined the shift from reactive to proactive AI.¹⁷ For 7CTOs members, the “win” is not just in adopting AI, but in doing so with a rigorous understanding of the underlying engineering. Pho’s advocacy for measuring P90 latency and interruption detection serves as a blueprint for other technical leaders who are tasked with modernizing legacy stacks without compromising security or customer trust.⁸

The 7CTOs community emphasizes that “AI doesn’t arrive perfect; it’s like hiring a new employee and it needs training”.⁸ This philosophy is embedded in the Mia platform, which allows for “Customizable Dialog Logic” and “Graceful Fallback Handling,” ensuring that if the AI encounters a scenario it cannot handle, it seamlessly escalates to a live agent with full context.⁹

Competitive Landscape: NADA 2026 and the Innovation Stage

The NADA 2026 Show in Las Vegas is the primary arena for demonstrating the practical utility of automotive AI. The show has moved away from the “disruptive threat” narrative of 2025 toward a “competitive advantage” focus, with an expanded Expo and a dedicated “Product Demo Stage”.¹⁸

Comparative Analysis of Key Players

As dealerships evaluate their options at NADA, the distinction between different AI philosophies becomes clear. While some vendors focus on “merchandising” or “lead generation,” others, like Mia, are building comprehensive “operating systems” for dealership communication.⁶

• Impel AI (Booth 4331W): Positioned as the industry’s only “AI Operating System,” Impel serves over 8,000 dealers and OEMs globally.²¹ Their approach is focused on an “AI Super Stack” that covers sales, service, chat, and merchandising. Impel’s strength lies in its massive scale and its ability to provide an “all-in-one” platform that eliminates vendor redundancy.²¹
• Stella Automotive AI: Focused heavily on conversational AI for both sales and service, Stella has made significant strides in OEM-level partnerships, such as its collaboration with Encora to streamline the vehicle journey from design to retail.²² Stella is often cited for its focus on the “human side of AI” and the challenges of customer adoption.²³
• AI (Booth 7707N): A global player making its North American debut at NADA 2026, Pinewood.AI acquired the automotive AI company Seez in 2025.²⁴ Their new “Project Intelligence” (Pi) solution is an autonomous agent that can “click, type, read, and make intelligent decisions” directly within the DMS, acting more like a digital assistant than a phone agent.²⁴
• Spyne (Booth 7729N): Spyne focuses on the visual and conversational aspects of dealership operations. Their “Vini” agent handles inbound and outbound conversations, while their “Studio AI” automates vehicle merchandising by creating cleaner, faster visuals for inventory listings.²⁰
• Fullpath: Known for launching the “Agentic CRM,” Fullpath focuses on creating a comprehensive sales ecosystem where the AI is embedded into the core database of the dealership, automating the “sales slayer” mentality.²¹

The “ROI Awakening” and the Move to Production

A recurring theme in the 2026 analyst reports from firms like Deloitte, PwC, and Blue Prism is the “ROI Awakening”.³ In 2025, many enterprises were in “pilot mode.” In 2026, the question has shifted to: “Is it working?”.¹³ Mia Labs’ ability to demonstrate specific revenue outcomes—such as the $50,000 monthly gain in service—positions it well for this new era of accountability. PwC’s “2026 AI Predictions” suggest that senior leadership is now moving toward a “top-down program” where the most critical workflows are prioritized for AI investment.⁷ In the dealership context, these critical workflows are inbound call handling and service scheduling.⁷

Deep Dive: The Anatomy of a Mia Labs Call

To appreciate the complexity of the Mia Labs platform, one must examine the multi-layered process that occurs during a standard customer interaction. When a customer calls a Mia-powered dealership, the system does not just “answer the phone”—it initiates a high-speed agentic workflow.²

Step 1: Intelligent Reception and Intent Recognition

The call is answered with sub-2-second latency. Mia’s natural language processing (NLP) engine identifies the caller’s intent—whether it’s a sales inquiry, a service request, or a general question like “What time do you open?”.⁶ If the caller has a history with the dealership, Mia pulls relevant context from the CRM or DMS instantly.⁹

Step 2: System Access and Dynamic Logic

If a customer asks about vehicle availability (e.g., “Is the black Lexus RX350 stock number 35021 still on the lot?”), Mia does not guess. It queries the inventory management system in real-time.⁶ If the vehicle is available, it moves to the next logical step: scheduling a test drive. Mia accesses the salesperson’s calendar and the CRM to book the appointment and notify the staff.⁶

Step 3: Complex Service Scheduling

For service calls, the complexity increases. Mia must identify the correct “op-codes” for the requested maintenance (e.g., an oil change for a 2024 Toyota Sienna), check the live capacity of the service bays, and find an open slot that fits the customer’s schedule.¹² This requires deep integration with tools like Xtime or Tekion.⁶

Step 4: Multi-Channel Continuity and “SMS Rescue”

If a call is dropped—a common occurrence in mobile communications—Mia’s “SMS Rescue” feature kicks in. The system automatically sends a follow-up text: “Hi, this is Mia… did you still need to book your tire appointment?”.⁶ This ensures that the conversation continues on the channel most convenient for the customer, resulting in a significantly higher conversion rate than traditional “call-back” methods.⁶

Broader Industry Trends: 2026 and the Future of AI Agents

The 2026 reports from major technology consultancies provide a macro-level context for Mia Labs’ trajectory. The consensus is that AI is transitioning from “interfaces” to “infrastructure”.¹¹

The Move from Copilots to Orchestrators

Google Cloud’s “2026 AI Agent Trends Report” predicts that “agentic workflows” will become a core part of business processes.² This involves multiple agents collaborating to automate complex tasks. For Mia, this means connecting the “Sales Agent” with the “F&I (Finance and Insurance) Agent” or the “Service Agent” to manage the entire lifecycle of a customer’s vehicle ownership.²

The Rise of Sovereign AI

Deloitte highlights the importance of “Sovereign AI”—systems where data and infrastructure are managed under the strategic independence of the organization.³ Mia’s choice to build on a secure, bank-level infrastructure like Azure reflects this need for dealerships to maintain control over their most valuable asset: their first-party customer data.³

The Human-in-the-Loop Requirement

Despite the move toward autonomy, the 2026 era is defined by “Human + Agent collaboration”.¹³ PwC and Blue Prism both emphasize that the goal of AI should be to empower employees to “reimagine” their roles.³ In the dealership, this means a service advisor no longer spends four hours a day on the phone but instead focuses on high-touch interactions with customers on the service drive.¹

Strategic Recommendations for Dealership Leaders

As NADA 2026 approaches, dealership owners and managers face a crowded and confusing marketplace. Based on the performance data and technical analysis of Mia Labs, several strategic recommendations emerge for leaders looking to navigate this transition.

1. Prioritize Integration Over Features

A standalone AI agent that cannot “read” or “write” to the DMS or CRM is simply another data silo. Dealerships should prioritize platforms like Mia that offer deep, bi-directional integration with their existing systems of record.¹

2. Measure What Matters: The “AI Maturity” Audit

Dealers should move beyond demos and perform their own “AI Maturity Audit.” This includes testing the AI’s ability to handle complex service requests, measuring the latency of its responses, and verifying its multi-language capabilities.⁸

3. Embrace the “Super Employee” Paradigm

Leadership should view AI not as a cost-cutting tool but as a growth engine. By deploying an AI agent like Mia, dealerships can “rescue” the 15-30% of missed calls that currently represent lost revenue.⁵

4. Invest in Training for Human-AI Collaboration

The most successful dealerships in 2026 are those that train their human staff to work alongside AI agents. This involves learning how to manage the leads generated by Mia and focusing on the high-value, human-centric parts of the car-buying and service journey.²

FOR IMMEDIATE RELEASE

Mia Labs Secures $20 Million Series A to Scale AI ‘Super Employees’ Across 350+ Automotive Dealerships

AUSTIN, Texas — January 22, 2026 — Mia Labs, Inc., the pioneer in AI-native conversational platforms for the automotive industry, today announced it has raised $20 million in Series A funding. The round was led by Permanent Capital Ventures, with participation from previous investors including J Ventures, bringing the company’s total capital raised to $29 million.

The capital will be used to accelerate the expansion of “Mia,” an AI-powered conversational platform that acts as a dealership’s 24/7 “Super Employee.” Unlike traditional chatbots or legacy IVR systems, Mia is a fully autonomous agent capable of managing complex, multi-step customer workflows across sales, service, and reception departments.

Modernizing a Trillion-Dollar Industry

The automotive retail sector is a vital component of the U.S. economy, yet it has long been hampered by fragmented technology and staffing challenges. Dealerships typically miss between 15% and 30% of incoming calls, leading to significant revenue loss and poor customer experiences.

“In today’s competitive landscape, dealerships can’t afford outdated tools and broken data that slow them down,” said Brian Hoang, CEO and co-founder of Mia Labs. “We are directly addressing this by building the most sophisticated AI super employee in the automotive space—one that is deeply familiar with dealership operations, elevates the customer experience, and continually improves to help dealers drive more revenue.”

Proven ROI and Technical Superiority

In 2025, Mia Labs demonstrated the massive scale of its impact, expanding to over 350 franchise dealerships nationwide. The platform enabled more than $45 million in dealership revenue while saving over 1.5 million human hours through automated customer conversations.

Key performance milestones for Mia Labs include:

• Revenue Generation: Dealerships generate an average of $50,000 in monthly revenue from AI-booked service appointments.
• High Conversion: Mia achieves a 30% appointment booking rate for service inquiries and reactivates 19% of sales leads through automated follow-up.
• Industry-Leading Latency: Built on Microsoft Azure, Mia operates with human-like latency of sub-2 seconds, ensuring natural and seamless customer interactions.
• Deep Integrations: Mia features bi-directional connectivity with over 35 industry-leading systems, including CDK Global, Reynolds & Reynolds, Tekion, and Xtime.

Leadership at the Intersection of AI and Automotive

The Mia Labs team brings together more than 100 years of combined automotive experience, spanning dealership operations, OEMs, and automotive software. This deep, firsthand understanding of the industry ensures the platform is built for real-world environments, not theoretical use cases.

“Mia Labs is addressing one of the most mission-critical challenges in automotive retail: customer communication at scale,” said Mike Gamson, Managing Partner at Permanent Capital Ventures. “Mia stands out because it was built by people who deeply understand dealership workflows and the realities operators face every day. Their approach to AI is practical, results-driven, and purpose-built for automotive.”

NADA 2026: The Future of the Dealership

On the heels of this announcement, Mia Labs will be showcasing its latest innovations at the NADA 2026 Show in Las Vegas. From February 4–6, attendees can experience live demos of the Mia platform and its “Super Employee” capabilities at Booth 6568N in the North Hall.

“I believe Mia is becoming a foundational platform for modern dealerships,” said Yossi Levi, Founder of Car Dealership Guy. “They’ve moved past the hype to deliver a tool that works as hard as a dealership’s best employee, 24/7/365.”

About Mia Labs, Inc.

Mia Labs, Inc. is modernizing automotive retail with AI technology built for dealership operations. Founded in 2023, Mia combines decades of automotive retail experience with advanced artificial intelligence to create an AI super employee that answers calls, engages customers, and converts conversations into revenue opportunities. Mia integrates directly with dealership systems, streamlines technology stacks, and is customizable across sales, service, and reception. For more information, visit www.mia.inc.

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Conclusion: The New Standard for Automotive Retail

The 2026 automotive retail market is no longer a place for experimental technology. The “ROI Awakening” has forced a consolidation around platforms that can prove their value through revenue generation and operational efficiency.¹³ Mia Labs’ Series A funding and its established footprint of 350+ dealerships indicate that the “AI Super Employee” is becoming the new standard for modern operations.¹

As the industry moves toward NADA 2026 and beyond, the success of a dealership will increasingly depend on its ability to leverage agentic AI to bridge the gap between human staff and legacy systems.² For technical leaders, particularly those within the 7CTOs community, Mia Labs provides a blueprint for how to scale AI with integrity, security, and a relentless focus on the customer experience.⁸ The transition from “interface” to “infrastructure” is complete, and Mia Labs is positioned at the forefront of this new, agentic era of automotive retail.⁶
As the industry moves toward NADA 2026 and beyond, the success of a dealership will increasingly depend on its ability to leverage agentic AI to bridge the gap between human staff and legacy systems.² For technical leaders, particularly those within the 7CTOs community, Mia Labs provides a blueprint for how to scale AI with integrity, security, and a relentless focus on the customer experience.⁸ The transition from “interface” to “infrastructure” is complete, and Mia Labs is positioned at the forefront of this new, agentic era of automotive retail.⁶

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