Olelo Intelligence Raises $1M in Angel Funding to Scale AI Sales Coaching for High-Volume Auto Repair Shops

Olelo Intelligence, a Honolulu-based AI sales coaching company focused on high-volume automotive repair shops, has announced the close of a $1 million angel round to accelerate growth across North America. For the ai world organisation audience tracking real-world AI adoption, this is a clear example of conversational intelligence moving from “nice to have” analytics into operational tooling that directly targets revenue recovery inside service businesses.

Funding announcement and who backed it

The newly announced $1 million angel round positions Olelo Intelligence to push further into the U.S. and Canada at a time when repair shops are balancing rising customer expectations, tighter labor availability, and more complex service operations. In the announcement, Olelo described its platform as an AI sales coaching solution designed to analyze service advisor calls in real time, spot missed sales opportunities, and coach managers on how to improve outcomes—ultimately helping shops convert more calls into booked appointments without adding headcount.

The round was led by Hawaiʻi Angels, which contributed $500,000 of the financing, and the deal for the investor group was shepherded by Clif Purkiser. Hawaiʻi Angels describes itself as a Honolulu-based network of early-stage investors supporting founders with capital and coaching “since 2002,” operating as a forum that connects entrepreneurs and early-stage investors. This matters because networks like Hawaiʻi Angels often provide more than funding; they can help founders sharpen go-to-market execution, recruit key introductions, and pressure-test operational scale-up plans—especially important for B2B SaaS products sold into multi-location franchise environments.

Clif Purkiser’s comments in the release framed the decision in terms of traction and execution, pointing to strong adoption, early revenue, and momentum, while also emphasizing the size of the opportunity in the U.S. auto repair sector. For readers following the ai world summit narrative around applied AI, this is a reminder that “AI success” in the market is frequently defined less by model novelty and more by whether the product ships, integrates, and measurably improves day-to-day workflows.

Why call coaching is becoming a growth lever

Automotive repair is a phone-heavy industry, and the phone call is still one of the highest-intent moments in the customer journey: a driver calls because something is wrong, time matters, and trust is being formed in real time. Olelo’s approach focuses on that moment by analyzing service advisor calls and surfacing where sales opportunities are missed, then giving coaching guidance that managers can use to improve performance.

One reason this space is attractive to AI builders is that the “data exhaust” already exists: many shops have call recordings, call tracking, and daily operational logs, but they lack the time and structure to translate those signals into repeatable coaching that lifts conversion and authorization rates. Olelo’s release highlights that the goal is not simply to transcribe calls, but to identify missed opportunities and provide actionable insights that can move metrics like appointment booking and service authorization. In practical terms, this means helping operators answer questions such as: which calls were missed, which calls were handled but not converted, which objections repeatedly stall authorizations, and where follow-up breaks down when the shop gets busy.

The second driver is coverage. Many repair shops face demand outside business hours, and if nobody answers or follows up quickly, the opportunity disappears to a competitor that feels more responsive. Olelo notes that customers have adopted both daytime call coaching and after-hours AI phone agents designed to capture opportunities when staff are unavailable. That blend—coaching humans when humans are on the line, plus automation when they are not—illustrates a broader pattern that continues to show up across ai world organisation events discussions: AI systems win when they reduce friction at the “handoff” points where businesses leak revenue.

Olelo’s product, traction, and reported impact

Olelo Intelligence was founded by CEO and co-founder Miki Hardisty and co-founder Ed Moore, and the company positions itself as a Hawaii-based AI sales guidance platform built specifically for high-volume automotive repair shops. The press release explains that the platform aims to increase revenue by identifying missed sales opportunities in service advisor calls and delivering actionable insights that improve call conversion, appointment booking, and service authorization. In other words, it is not trying to be a generic call center tool; it is built to map directly onto the operational reality of shops where advisors juggle customers in the lobby, technicians in the bays, parts availability, and constant inbound calls.

Momentum is one of the strongest signals investors look for at the angel stage, and Olelo’s update includes concrete scale indicators. The company said it has scaled to more than 100 live shop locations across 62 franchisees, and it cited a national partnership with AAMCO Transmissions & Total Car Care. Those details matter because multi-location deployment creates a tougher bar than a single-shop pilot; it forces the product to work across different phone systems, management styles, service menus, and customer demographics, all while maintaining consistent reporting that franchise leadership can trust.

The announcement also includes a performance claim from a multi-location franchise operator, who reported roughly a 15% increase in revenue per store—about $20,000 a month per location—within about two months, attributing the lift to visibility into missed calls and the ability to recover deals quickly. While outcomes will naturally vary by operator, the specificity of the statement is notable because it ties the product to a business metric owners care about: incremental monthly revenue per location. For the ai world summit audience looking at applied ROI, this type of metric is often what moves AI projects from “pilot” to “standard operating procedure.”

On the product side, Olelo’s website describes capabilities such as an AI Voice Agent that answers overflow and after-hours calls, books appointments, and sends instant SMS alerts, alongside real-time notifications and personalized coaching. The same site also shares example results and testimonials, including improvements in scheduled appointment rate and conversion-rate lift figures cited by franchise operators. For shop operators, the appeal is straightforward: turn phone activity into a measurable pipeline, make coaching less subjective, and reduce the “lost opportunity” problem that happens when a busy advisor simply cannot get to every call or follow-up.

The press release adds more context on leadership as well. It states that Miki Hardisty has experience building and scaling applied AI and technology solutions, including roles such as National CTO at Jack in the Box and CTO and COO at ProService Hawaiʻi, and that Ed Moore has built and led billion-dollar sales organizations. The relevance of that background is not just prestige; it suggests a team that understands both enterprise-grade operational execution and revenue leadership—two skill sets that often determine whether an AI product becomes an integrated workflow or remains a dashboard that teams ignore.

What’s next, and why this fits the AI World lens

The financing is intended to support Olelo’s growth and expansion across the U.S. and Canada, and the company frames the round as fuel to deepen the product and scale measurable results quickly. The release also notes that after participating in the Blue Startups Accelerator, Olelo raised capital from Hawaiʻi Angels and leveraged that foundation to scale across the U.S. and Canada, while pointing to the fragmented nature of the U.S. market with nearly 300,000 automotive service locations. That “fragmented, large market” reality is exactly where vertical SaaS and vertical AI companies often thrive, because the opportunity is huge, the pain points are repeatable, and buyers respond well to solutions that reflect their actual workflows and language.

For the ai world organisation editorial angle, Olelo’s raise is a useful case study in practical conversational AI—less about flashy demos and more about operational improvement in a blue-collar, service-heavy category. This is the kind of story that fits naturally into the ai world summit programming because it connects AI to measurable business outcomes, shows how AI can augment frontline staff rather than replace them, and highlights the strategic value of improving customer experience at the “moment of truth” when a caller is deciding where to take their vehicle. It also reinforces a theme that repeatedly shows up across ai conferences by ai world: AI adoption accelerates when solutions are purpose-built for a specific industry and can be deployed quickly without disrupting existing systems.

As the ai world summit 2025 and ai world summit 2026 cycles continue, funding updates like Olelo’s help map where investors believe applied AI is delivering durable value, particularly in sectors where revenue leakage is driven by missed calls, inconsistent follow-up, and uneven coaching. For readers who follow ai world organisation events year-round, the takeaway is that “AI in automotive” is not limited to vehicle autonomy or manufacturing; it also includes the customer-operations layer that determines whether service businesses capture demand efficiently and maintain trust. To stay aligned with this applied-AI focus, the ai world organisation will continue spotlighting real deployments, measurable metrics, and operator-led transformation stories across its news coverage and summit conversations.