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Matt Cavallaro, founding AE for Cresta's APAC book.
Enterprise AE who's built go-to-market from zero twice, with the conviction on vertical AI that only comes from selling both sides of it.
01 · Proof
Numbers pulled straight from the CV. No rounding up.
02 · The Fit
Mapped directly to the JD's requirements.
Full-cycle deal craft
MEDDPICC and forecast hygiene are explicit core competencies, not buzzwords: 100% median quota attainment over 5 years against a <50% team average is the receipt, including structuring and closing complex, multi-stakeholder enterprise agreements.
For this role
For a founding APAC seat: the same discipline applied to category-defining AI deals, where decision criteria and economic buyer have to tie back to a business outcome the buyer already cares about, not a feature list.
Executive alignment
Led multi-threaded campaigns targeting CIOs, Chief Digital Officers, and Procurement Heads to align technology investment with institutional outcomes, and personally navigated a co-CEO economic buyer on ROI, tech debt, and growth capacity.
For this role
For Cresta: the counterpart shifts to CX and contact center leaders, CFOs, and COOs evaluating AI ROI. The skill is the same: threading a technical buyer and an economic buyer through one narrative.
Cross-functional deal leadership
Recruited and developed a network of systems-integrator partners to support a new market, ran partner-led pipeline-generation events, and partnered cross-functionally with engineering, product, and marketing to shape go-to-market.
For this role
Maps directly to what this role asks for: leading cross-functional teams through major deal processes, working closely with Product, Marketing, Customer Success, and Engineering to close and land strategic accounts.
Founder-level territory building
Built an entirely new market (ANZ K-12) from zero at Salesforce, growing it to $2M TCV, and is now a founding go-to-market contributor at an early-stage AI startup, engineering territory strategy from zero in a high-ambiguity, fast-moving environment.
For this role
This is the exact mandate of a founding APAC AE: no existing playbook, no inherited territory. Prove the model live, then help define the regional sales process for whoever comes next.
03 · Why Vertical AI, Why Cresta
I've sold AI from both sides. That's why I believe in this one.
Enterprise AI, from the inside
Salesforce, Education Cloud
I sold Education Cloud into K-12 and higher-ed organizations that had spent years being told a broad, general-purpose platform would eventually solve their specific problem. It rarely did, fast enough. The deals that actually landed and expanded were the ones where we could point to a purpose-built workflow, a Student Information System running on top of the platform, and prove real value inside the exact process the buyer already lived in every day.
Horizontal AI, from the inside
monō ai, GTM Lead
At monō ai I'm building go-to-market for a horizontal AI platform, one built to be flexible across use cases. That flexibility is genuinely powerful, and it's also the thing that slows enterprise buying down: a horizontal platform asks the customer to do the last mile of specialization themselves, and that last mile is exactly where deals stall in procurement, and where a buyer starts asking why they wouldn't just build it themselves.
The bet
Cresta bets on the opposite model: AI purpose-built for the contact center, arriving ready to prove ROI inside the exact workflow the buyer already runs, not a platform they have to finish building. Having sold both models from the inside, I think that's the correct bet. Vertical AI is where enterprise budget is actually moving right now, and Cresta has one of the sharpest product-market fits I've seen in the category.
This chat is the same conviction in practice: I build hands-on with AI, I don't just talk about it in interviews. Ask it something, grounded on my résumé, this plan, and how I'd approach the accounts below. It answers as me, in first person, and says “I'd want to validate that” when it doesn't have grounding, the same way I would.
04 · Cross-Functional Deal Leadership
Leading teams through major deal processes, not just carrying a number solo.
The innovation engine
A mid-tier partner ecosystem that became the land-and-expand lever.
Built out an entire mid-tier partner co-sell motion in education that became an innovation engine for the wider market: enterprise accounts landed and expanded by leveraging the tech solutions those partners built, not by Salesforce selling direct.
For this role
Maps directly to how a founding APAC AE would activate specialist implementation and industry partners early: recruit and enable a bench of partners so their built solutions create the wedge into F1000 accounts.
Cross-functional deal leadership
Leading teams through major deal processes, not just carrying the deal solo.
Partnered cross-functionally with engineering and product to shape roadmap around customer needs, and recruited and developed a network of systems-integrator partners to support a brand-new market, coordinating marketing, product, and delivery around a single deal outcome.
For this role
This is close to a literal match for the role: collaborating cross-functionally with Product, Marketing, Customer Success, and Engineering to run complex enterprise sales cycles from prospecting through close.
Partner-to-partner matchmaking
Filling capability gaps by pairing partners together, not just with the vendor.
Connected a smaller partner with deep technical credibility but a limited network to a larger partner with a broader relationship into one of the largest Catholic dioceses in the ANZ region, pairing the smaller partner's innovation with the larger partner's account access to open a deeper enterprise conversation.
For this role
A differentiated, ecosystem-orchestration skill most AEs don't claim: not just selling with a partner, but building the connective tissue between partners so the account gets served better than any single partner could manage alone.
05 · Point of View: Target Accounts
Three accounts mapped to Cresta's own named customers, built the way I'd actually build a territory plan.
United Airlines, Cox Communications, and Marriott are Cresta's own reference customers. These three are the APAC analog, one per vertical, plus two more accounts on my radar below.
Qantas
Travel / airlineAustralia's flag carrier, massive contact center volume across bookings, loyalty, and disruption recovery, already publicly building group-wide AI capability. A direct analog to Cresta's own United Airlines relationship.
- Likely trigger
- Any public statement on group-wide AI capability, a customer-service complaint cycle around delays or cancellations, or a new digital transformation leadership hire.
- Entry point
- Position real-time agent augmentation and conversation intelligence as the fastest path to prove AI ROI in the highest-volume, highest-emotion queue (irregular operations and disruption recovery), where a horizontal AI build would take too long to reach workflow-specific value.
- Land & expand
- Land with a single high-volume queue (disruption rebooking) with a measurable handle-time and CSAT lift, then expand into the Frequent Flyer and broader international contact center footprint.
- Cresta capability
- AI Agent and real-time agent augmentation for the disruption-recovery queue, conversation intelligence for QA and compliance across the wider center.
What I'd validate first: Current contact center platform and vendor stack, and whether the group-wide AI capability is being built in-house or is open to a specialist partner.
Telstra
TelecommunicationsAustralia's largest telco, already piloting generative AI on a cloud-native contact center platform, proving both AI appetite and real budget, but general-purpose tooling built in-house rather than a purpose-built vertical layer.
- Likely trigger
- A new AI pilot announcement, an earnings call mention of customer-service cost-to-serve, or a leadership change in customer experience.
- Entry point
- Reframe the conversation from "another AI pilot" to the vertical-specialization gap: their in-house tools summarize and assist, but Cresta's real-time augmentation and conversation intelligence are purpose-built for the contact center workflow end to end, a faster path to the next step change, not a competing pilot.
- Land & expand
- Start with one specialized queue (billing disputes or a fault queue) proving deeper ROI than the general tooling already in place, then expand across broader retail and enterprise support.
- Cresta capability
- Real-time agent augmentation for authentication and intent-heavy queues, conversation intelligence for QA and coaching at scale.
What I'd validate first: Exactly which queues their existing AI tooling already covers, so the pitch is additive rather than a rip-and-replace, and who owns the CX AI roadmap internally.
Accor Pacific
HospitalityThe region's largest hotel operator by footprint (Sofitel, Novotel, Mercure, Pullman, ibis and more across APAC), with Pacific headquarters in Sydney and reservations/guest-service call center volume at genuine enterprise scale. The direct hospitality analog to Cresta's own Marriott relationship.
- Likely trigger
- A new brand launch or portfolio expansion in the region, a public statement on guest-experience investment, or a leadership change in Accor Pacific's digital or CX function.
- Entry point
- Lead with conversation intelligence and real-time agent augmentation across the central reservations and guest-service lines that sit behind every brand in the portfolio, where a single specialized deployment touches volume across many properties at once.
- Land & expand
- Prove it on one brand's reservations line (a high-volume, lower-risk starting point like ibis or Novotel), then expand across the wider Pacific portfolio and into loyalty (ALL) servicing.
- Cresta capability
- Real-time agent augmentation for reservations and guest-service queues, conversation intelligence for QA and coaching across a multi-brand contact center.
What I'd validate first: Whether reservations/guest-service is centralized at the Pacific level or run brand-by-brand, and the current contact center vendor stack.
On my radar
Accounts I'd prioritize next, same vertical-fit logic, not yet worked to the same depth as the three above.
Commonwealth Bank of Australia
Financial servicesAustralia's largest bank by market cap, with enormous contact center footprint across retail banking and fraud/dispute queues, an adjacent vertical to Cresta's named customer base worth tracking.
Next step: Map the current vendor stack for contact center AI and how centralized the AI/CX buying decision is before proposing a regulated-queue entry point.
Australia Post
Logistics / retailNational-scale delivery and retail contact center with huge seasonal spikes, a reasonable analog to Cresta's high-volume home-services customers.
Next step: Benchmark seasonal peak-volume handling today and whether cost-to-serve during peak delivery periods is the sharpest wedge for a real-time augmentation pitch.
Built from public signals only: company scale, contact-center volume, and vertical fit to Cresta's actual named customer base (United Airlines, Cox Communications, Marriott, and others in travel, telecom, and hospitality). None of these five are confirmed Cresta accounts. Before presenting this live, each should be sanity-checked with a quick conversation with the Cresta AE or SE team on existing account ownership and any live pilots.
06 · 30-60-90
What I'd actually do with the first quarter as a founding AE.
Days 1-30
Map the territory
- Map F1000 APAC accounts against public AI-investment signals: earnings-call mentions, pilot announcements, CX leadership changes.
- Map the competitive landscape: who else is already selling AI CX tooling into these accounts, and where the vertical-versus-horizontal gap actually shows up.
- Build the first 3-5 account plans using the same why/trigger/entry/expand structure as this site's Target Accounts section.
- Partner with Product, Marketing, and Customer Success to understand what's already working in other regions before assuming APAC needs something different.
Days 31-60
Build pipeline
- Convert the top account plans into active outreach: multi-threaded, targeting both the CX/contact-center technical buyer and the CFO/COO economic buyer.
- Run the first proof-of-value conversations scoped to a single specialized queue rather than a full-center pitch.
- Start codifying what a founding APAC playbook looks like, since whoever comes next inherits whatever gets proven here first.
Days 61-90
Prove the model
- First deals in late-stage evaluation with named economic buyers and validated technical champions.
- Refine the regional go-to-market motion based on what actually worked in the first 60 days.
- Feed learnings back into the broader APAC expansion strategy, since defining that process is as much the mandate as any single deal.
Let's talk about the APAC book.