The Wire

Real-time updates from ANZ tech sales

2 months ago
News

SaaStr cuts sales team from 20 to 3, adds AI agents, revenue up 47%

## The Numbers SaaStr went from 20+ sales employees to 3 humans plus 20+ AI agents across Artisan, Qualified, AgentForce, Monaco, Momentum, and custom builds. Revenue: -19% YoY to +47% YoY over 10 months. Pipeline closed-won: $2.4M. Pipeline generated: $4.8M. ## What Changed Jason Lemkin, SaaStr founder and CEO, ran the numbers with a public company CRO. Every AI agent deployment had one thing in common: no lead left behind. The agents handle: - Instant answers to website visitors (no form fills) - Immediate meeting booking (no queue) - Follow-up on every lead in the database (including six-month-old cold leads) - Re-engagement of closed-lost deals, expired trials, churned customers One AI SDR booked a six-figure sponsorship deal on a Saturday at 6:02 PM. No human was working. That one deal covered months of AI agent cost. ## Why It Works Not the models. Not the platforms. Coverage. Human sales teams prioritise. They work A leads, touch B leads if time allows, ignore C leads entirely. AI agents touch everything. They do not sleep, take weekends off, or deprioritise leads based on score. Lemkin's playbook: 1. Answer every question instantly (no knowledge base links) 2. Book meetings instantly (no forms) 3. Follow up every lead (including old ones) 4. Re-engage closed-lost and churned accounts ## The Market Context AI lead scoring automation and AI email lead generators are trending hard. Tools like HubSpot AI lead scoring, Salesforce lead scoring, and predictive lead scoring software help prioritise. But SaaStr's approach is different: do not prioritise, cover everything. Outbound AI sales agents and AI lead follow-up automation are moving from pilot to production. Sales Closer AI and similar tools are getting reviewed by real sales teams. The best AI sales agents are not replacing AEs, they are handling the volume humans cannot. ## What This Means for Sales Teams If your team ignores leads because of capacity, you are leaving revenue on the table. If your SDRs only work during business hours, you are missing deals. If your closed-lost list sits untouched, you are losing to competitors who redeploy AI agents. SaaStr is events and tickets, sure. But the principle applies: most B2B sales teams do not have a lead quality problem, they have a lead coverage problem. AI agents fix that. No ANZ presence reported yet, but the playbook works anywhere you have more leads than humans can handle.

SaaStr
2 months ago
News

Ideally raises $13.4M Series A, counts Google and Telstra as clients

## Ideally raises $13.4M Series A, counts Google and Telstra as clients Auckland-based consumer insights startup Ideally closed a $13.4M Series A led by Shearwater Capital, with Altered Capital and Icehouse Ventures participating. The round values the company at $83M. The platform uses generative AI to run market research that traditionally took months and six figures. Clients include Google, Telstra, DoorDash, Burger King, and Asahi. The company serves 250+ brands across APAC and US. ### The numbers - Series A: $13.4M at $83M valuation - Previous raises: $2.15M (November 2023), $5.5M (August 2024) - Total raised: approximately $21M - Client count: 250+ brands - US revenue growth: 350% since New York office opened Founded in August 2023 by James Donald, Brendan Cervin, and Joshua Nu'u-Steele out of venture studio TRA Labs. CEO James McDonald joined later. ### What it means for sales teams Ideally is a customer research platform, not a sales intelligence tool. Different category entirely. Think UserTesting or Qualtrics, not ZoomInfo or Apollo. That said: the funding signals ANZ B2B SaaS is still attracting capital. Consumer insights platforms typically sell into marketing teams at enterprise accounts, which means longer sales cycles and higher ACVs. The company recently opened a New York office and is using Series A capital for US expansion. That usually means hiring AEs and SDRs in market. No hiring numbers disclosed yet. Worth noting: the company says it "could not have existed without generative AI." That positioning likely plays well with enterprise buyers evaluating new platforms versus legacy research providers. ### Context Consumer insights is adjacent to sales intelligence but serves different buyers. Sales intelligence platforms (Apollo, ZoomInfo, Cognism) help find and reach prospects. Consumer insights platforms help understand customer behaviour and validate product decisions. Ideally competes with established players like UserTesting and Qualtrics in the research space, not with sales tech stacks. The AI angle differentiates on speed and cost: what took 9 months now takes 90 days, according to the company. Client roster includes major ANZ enterprises (Telstra) and US brands (DoorDash, Burger King), suggesting the platform has product-market fit in both regions. The 350% US revenue growth backs that up, though no absolute revenue numbers disclosed. No word yet on ANZ headcount, sales team size, or hiring plans locally.

Startup Daily
2 months ago
News

750 ANZ startup funding rounds go unreported, Techboard analysis shows

# 750 ANZ startup funding rounds go unreported, Techboard analysis shows Most Australian startup investments never make headlines. Techboard, the WA-based startup data firm, tracked 1,100 companies that raised external investment in 2025. Only 361 announced their deals publicly. That leaves roughly 750 unannounced rounds, potentially more than double the reported funding activity. The announced deals totalled $5.2 billion across 379 raises. The unannounced deals? No dollar figures available, but Techboard estimates they could represent the majority of actual capital flowing into the ecosystem. ## Why this matters for sales If you are prospecting into early-stage tech, the company you are targeting might have raised without telling anyone. That changes qualification. A stealth Series A means different budget authority than a bootstrapped operation. Traditional sales intelligence tools like Crunchbase or CB Insights track announced deals. Techboard digs into ASIC regulatory filings to surface unannounced investment activity. In H1 2025 alone, they identified 682 possible unannounced deals versus 255 announced ones. Founder Peter van Bruchem notes the trends in unannounced deals do not match public announcements. Smaller rounds, less newsworthy sectors, and founders without media access stay quiet. Some companies actively avoid publicity. ## What the data shows Techboard has been tracking Australian startups since 2015, monitoring over 7,500 companies. Their methodology: combine announced deals with ASIC share issuance data to identify likely funding events. The gap between announced and actual funding creates blind spots for competitive intelligence and prospect research. If half the market is raising capital without announcing it, your sales team is working with incomplete information. For AEs targeting funded startups, this means enriching data beyond press releases. ASIC filings, hiring patterns, and direct outreach matter more when companies stay in stealth mode. Full report available at Techboard's site. Worth reading if your patch includes early-stage tech companies in ANZ.

Startup Daily
3 months ago
News

ANZ boards lack tech directors as AI reshapes sales strategy

## The Numbers Over 50% of ASX 500 boards have no directors with science, technology, engineering, or maths backgrounds. This matters for sales teams: boards set AI investment priorities, approve CRM spend, and green-light the AI-native tools your team needs to hit quota. Australia faces a 40,000 AI talent shortage by 2027. That gap extends to the boardroom, where directors lacking tech fluency struggle to evaluate AI governance frameworks or assess whether your sales stack is competitive. ## Why Sales Teams Should Care Boards without tech expertise make slower decisions on AI tooling. When your CRO pitches budget for AI agents or conversation intelligence, boards that do not understand the tech default to risk aversion. The Australian Institute of Company Directors reports 53% of business leaders cite digital transformation as their top 2025 concern, yet board composition lags. This creates friction for sales orgs chasing productivity gains. Gartner tracks new AI roles emerging across GTM teams: AI governance leads, prompt engineers for sales, AI-native SDR managers. Without board understanding, these headcount requests stall. ## The Hiring Angle Restructuring experts say boards need curious, tech-literate directors, not full engineering backgrounds. Apathy is the barrier, not capability. For sales leaders, this means building internal business cases that educate upward: show board-level ROI on AI investments, translate technical capability into pipeline metrics. Bessemer tracks AI agents for sales as a category: 47% of enterprise sales teams pilot AI SDRs in 2025. Your board needs to understand why that matters before approving spend. If they lack STEM fluency, your CRO becomes the translator. ## What This Means Sales orgs at companies with tech-literate boards move faster on AI adoption. They get budget approved, hire specialized roles, and ship tools that improve attainment. Companies stuck with traditional board composition lag on AI-native sales strategies. The skills gap analysis shows up in sales hiring too: director-level roles now require AI competency. Boards that do not prioritize tech expertise will struggle to evaluate whether their sales leadership can scale in an AI-first market. Bottom line: board composition impacts your comp. Faster AI adoption means better tools, clearer territories, and realistic quotas. Slow boards create drag.

Startup Daily
3 months ago
News

Salesforce launches API-first CRM: AI agents skip the browser entirely

## Salesforce launches API-first CRM: AI agents skip the browser entirely Salesforce announced Headless 360 at TDX 2025: the entire CRM platform accessible via APIs, with no browser required. CEO Marc Benioff called it "the API is the UI," positioning it as infrastructure for AI agents. For sales teams already running AI tools in production, this is not news. It is confirmation. Jason Lemkin, founder of SaaStr, said his team has been operating this way for six months. Their AI-powered marketing and customer success agents pull real-time pipeline data, assign tasks, and surface revenue analysis directly from Salesforce APIs. No one logs into the browser. "If you're running a modern B2B + AI stack, you've probably been doing versions of this for months," Lemkin wrote. "You just haven't named it yet." ### What this means for sales ops Headless 360 exposes Salesforce and Agentforce (its AI agent platform) through APIs, MCP protocols, and CLI commands. AI sales agents can now access CRM data, trigger workflows, and execute tasks without human login. Practical applications already in use: - AI SDRs pulling enrichment data and logging activity automatically - Pipeline analysis agents surfacing deal risk without manual reporting - Lead routing and task assignment via API, bypassing manual workflows This shifts Salesforce from "system of record" to "system of execution" for agent-driven sales motions, according to company messaging. ### The AI agent sales stack question Salesforce is positioning Agentforce as the layer between AI agents and CRM data. Alternatives exist: HubSpot Workflows, Outreach AI automation, and custom-built API integrations already handle similar use cases. The question for ANZ sales leaders: does this justify Salesforce's pricing premium, or do lighter-weight tools deliver the same workflow automation at lower cost? Salesforce holds roughly 20-25% CRM market share globally and dominates ANZ enterprise accounts (banks, telcos, large tech). No ANZ-specific pricing for Headless 360 has been disclosed yet. ### What changed Not the technology. Sales teams have been hitting Salesforce APIs for years. What changed is Salesforce officially packaging this as a product strategy and messaging it as the future of CRM. Benioff is betting that as AI agents become standard in sales workflows, the companies that make their data most accessible will win. Headless 360 is that bet, formalised. For teams already running AI agents in production, the takeaway is simple: you are ahead of the announcement cycle. Keep shipping.

SaaStr
3 months ago
News

SaaStr runs 20 AI agents, 3 humans, revenue up 66 points YoY

## The Setup SaaStr is running 20+ AI agents with three humans handling leads and revenue ops. Revenue swing: -19% to +47% YoY. Founder Jason Lemkin and head of AI Amelia Bywater shipped a new podcast breaking down what works, what breaks, and what founders building AI into sales should actually know. No roadmap promises. Just production reality. ## What They Are Seeing **Vibe-coded apps need daily maintenance.** SaaStr has shipped 10+ AI apps with 750,000+ combined uses. Every single one needs a product-savvy human checking on it daily. Models update without warning. Integrations flake. Agents drift. The fun part is building. The work is keeping them running. **Hallucinations are daily maintenance, not solved problems.** Their AI VP of Marketing compared the wrong year in an analysis this week. Made up a data point in another. These are not rare edge cases. They are daily outputs that ship to customers if no one is reviewing. The fix is not a better model. The fix is a process: someone reviews outputs every day. **Model regressions silently break working apps.** Their pitch deck analyzer graded 4,000+ decks without issue. Then the underlying model updated, and outputs went sideways. No changelog. No heads-up. Just broken results you have to catch yourself. **Agents upsell without knowing it.** Clay's agent recommended a model 2 to 5 times more expensive than needed, right around a price increase. Probably not intentional. Effect on the customer is identical: pushed toward premium without knowing cheaper works fine. Every B2B sales tool using AI agents needs to audit this now. Is your agent recommending the right tier, or is it steering customers to the most expensive option because that is what training data rewards? **Agents blame other tools when they break.** Something breaks, the agent points at Stripe, Airtable, OpenAI rate limits. Sometimes true. Often not. You need humans who can call BS and say "check again." ## The Unlock "No Lead Left Behind." AI agents catch what humans miss. Lemkin's thesis: the real value is not replacing SDRs, it is capturing leads that slip through when humans are stretched thin or focused elsewhere. SaaStr is proof of concept. Three humans, 20+ agents, revenue up 66 points. The work is maintenance, oversight, and knowing when the agent is wrong. ## What This Means for Sales Teams If you are running AI SDR agents or lead qualification tools, the honeymoon phase is building the demo. The actual job is daily review, quality baselines, and catching drift before customers do. AI for lead gen works. AI for ops works. But it does not run itself, and providers are figuring out monetisation in real time. Watch your bills. Watch your outputs. And do not automate away the operator instinct that knows when something smells wrong. Comp transparency check: SaaStr has not disclosed headcount details or sales team OTE. This is a media/events/community business running lean, not a traditional SaaS sales org. The lesson is in the ops model, not the comp structure.

SaaStr
3 months ago
News

HubSpot ships incomplete AI tool, charges $50/month for zero recommendations

## The Problem HubSpot launched an AI Engine Optimization tool. It does not work well enough to charge for. Here is what it delivered: - Brand visibility score: 70%. No action items. - Sentiment analysis: 0% for content, 64% for events. Across 7,000+ published posts over 10 years. - Recommendations: "No recommendations just yet." - Price: $50/month for more prompts. That is not a product. That is a dashboard with broken metrics and a paywall. ## The 60% Pattern This is not just HubSpot. B2B vendors are rushing to ship AI features that check the "we have AI" box without solving problems better than dedicated tools already do. Six months ago, buyers gave credit for shipping early. That window closed. AI-native point solutions have compounded improvements: more data, more iterations, deeper integrations. The gap between "60% good enough" and "best in class" has widened, not narrowed. Replit and Lovable for building. Reve for images. Higgsfield and Opus for video. Gamma for presentations. These tools work. When enterprise vendors ship half-finished AI features, users may try them. They will not pay for them. ## What Actually Works One SaaS founder built a better AEO tool in 60 minutes using Replit. The difference: it generates actionable recommendations. "Your Structured Data scores 20/100. You have no JSON-LD markup. Here is the exact prompt to fix it." HubSpot's tool said "no recommendations." The quickly-built alternative gave specific issues, category breakdowns, and ready-to-use prompts for WordPress, Shopify, and AI coding tools. It improved SaaStr's AEO score from F to C+ in minutes. That is the threat now. If a founder can ship a better solution in an hour, your enterprise AI feature needs to deliver more than metrics and a paywall. ## What This Means for Sales Teams If you are evaluating CRM AI features in 2025: - Test them properly. Do they generate actionable output or just dashboards? - Compare to AI-native point solutions. Is the bundled feature actually better, or just convenient? - Watch for "no recommendations yet" signals. That means incomplete. - Check if they are asking you to pay before the product works. The bar for AI features has moved. Buyers were forgiving 6-9 months ago. Not anymore. If your vendor is shipping 60% solutions while charging full price, the dedicated tool probably works better. Worth noting: this applies to sales intelligence, conversation analysis, email sequencing, and every other AI feature getting bolted onto platforms. The LLMs got significantly better in late 2025. The gap between half-finished and production-ready is now obvious to users. Competitive pressure to ship is real. But shipping broken features with paywalls does not build trust. It creates churn opportunities for AI-native competitors who already solved the problem.

SaaStr
3 months ago
News

Canva delays IPO to 2027, shifts pricing to AI usage model

Canva will not IPO in 2026. The design platform is pushing its public listing to 2027 at the earliest, co-founder Cliff Obrecht confirmed to Capital Brief at the company's Los Angeles product launch. The delay centres on business model transition. Canva is overhauling its pricing to usage-based for AI features, and Obrecht wants that shift proven before investor roadshows begin. "We're fully IPO ready," he said, "but we want to make sure the evolution of this business model is really bedded in so we're not having to explain ourselves to the market through a transitional period." Translation: they are reworking how enterprise customers pay, and they want adoption data before the S-1 drops. Last valuation was A$65 billion in secondary sales in August 2025. That puts Canva close to Atlassian's market cap and makes it Australia's second-most valuable tech company. Unless there are more secondary rounds, early employees and investors wait another 9 to 12 months minimum for liquidity. The company has been on an acquisition run: eight startups in two years, including last week's Simtheory and Ortto acquisitions from the Stayz founders, reportedly over $100 million. That build-versus-buy strategy suggests Canva sees faster paths to AI credibility through M&A than internal development. For ANZ sales teams watching this: Canva's delay reflects broader 2025 and 2026 SaaS IPO market conditions. Software multiples compressed hard through 2024. Public SaaS companies that did list saw share prices hammered. Canva is choosing patient capital over public market volatility. What this means: if you are at a late-stage ANZ startup eyeing an IPO, your timeline just got longer. Canva has the luxury of waiting. Most do not. The comp packages built around 2026 liquidity events may need revising. Obrecht's comment about "transitional periods" is telling. Public market investors punish companies still figuring out their revenue model. Canva knows this. They are delaying until the AI pricing works and the numbers prove it.

Startup Daily
3 months ago
News

7 ANZ startups raised $71.8 million mid-April, Phonely leads at $22.3 million

# 7 ANZ startups raised $71.8 million mid-April, Phonely leads at $22.3 million Seven ANZ startups closed funding rounds totalling $71.8 million in mid-April. Most are pre-revenue with no disclosed sales teams, headcount, or comp details. ## Phonely: $22.3 million Series A Phonely, the University of Melbourne spin-out building AI receptionists, raised $22.3 million in a Series A led by Base10 Partners. Y Combinator doubled down after backing the startup with $750,000 in mid-2024. Three enterprise customers co-invested: Etech Global Services, TSA Group, and Engage CX. The round values Phonely at $139 million. Total raised: $26 million. Founded in 2023 by Will Bodewes and Nisal Ranasinghe, Phonely is now based in San Francisco. The AI receptionist answers FAQs, routes calls, and books appointments using a company's website data. Setup takes five minutes. No details on sales team size, AE hiring plans, or go-to-market structure were disclosed. ## The rest of the cohort Pay.com.au, Atomic Tessellator, Caruso, Deteqt, Clean State Clinic, and Earthletica also raised capital. Funding amounts were not disclosed for these six. Separately, Founder Institute Australia/New Zealand graduated seven startups in a recent cohort, including Mareekh Dynamics (space habitation systems), Co-Linic AI (allied health SaaS), and Divergity (ADHD productivity platform). All are pre-seed or seed stage with no disclosed revenue, sales teams, or executive details. ## What this means for sales professionals Series A rounds typically mean hiring plans. Phonely's $22.3 million raise at a $139 million valuation suggests expansion, but no AE or SDR hiring was announced. For sales professionals watching ANZ tech, this is capital flowing into early-stage companies, not yet translating into disclosed sales roles. Most startups in this cohort are pre-revenue or revenue details were not shared. That means no comp transparency, no team size data, and no clarity on what roles might open up. Worth tracking: Phonely's customer base includes three contact centre players. If they scale, enterprise AE roles could follow. Until then, this is funding news without hiring signals.

Startup Daily
3 months ago
News

Canva pushes into sales workflow tools with AI 2.0

## Canva pushes into sales workflow tools with AI 2.0 Canva launched AI 2.0 overnight, expanding beyond design templates into workflow automation and app integration. The Sydney-based company is targeting the productivity tools that sit between your CRM and your deck. The update includes conversational design (describe what you need, AI builds it), automated workflows, and connectors that pull data from emails, meetings, and documents. That positions Canva closer to workspace tools than design platforms. **What this means for sales teams:** Most sales orgs use Canva for one-off collateral: decks, one-pagers, case studies. The AI 2.0 push suggests Canva wants to own more of that workflow. Pull meeting notes, generate a pitch deck, export to PDF, all without leaving the platform. The company hit $4 billion ARR serving 240 million users globally. Recent acquisitions include Ortto (marketing automation) and Simtheory (AI workflows), signalling vertical integration from campaign brief to delivery. Competition context: Canva competes with Adobe and Figma on design, but this update puts it closer to Google Workspace and Microsoft 365 territory. Google acknowledged the overlap last year when Canva launched spreadsheets and charts. **Pricing reality for sales teams:** Canva runs a hybrid model: seat-based subscriptions plus usage-based AI credits. Free tier exists but sales collateral at scale requires paid seats. Enterprise pricing is custom (read: negotiated). Figma runs similar economics but skews more technical. For smaller sales teams, the question becomes: do you need another tool subscription, or can your existing stack handle collateral creation? For enterprise, it's about consolidation. If Canva replaces three point solutions, the math works. **ANZ angle:** Canva is Australian-headquartered (Sydney), employs over 3,000 globally, and continues expanding enterprise integrations. No recent funding rounds reported; focus is profitability and AI scaling after hitting $40 billion valuation in 2021. The company is pushing hard into mid-market and enterprise, targeting teams that want to consolidate their martech stack. Sales orgs running fragmented tools (design here, automation there, analytics somewhere else) fit that profile. **Bottom line:** Canva is moving from "design tool sales teams use sometimes" to "workflow platform sales teams use daily." Whether that sticks depends on execution and whether reps actually want another login between their CRM and their prospects. Watch for enterprise sales hiring. If Canva is serious about displacing workspace tools, they will need AEs who can sell consolidation, not templates.

SmartCompany
3 months ago
News

TestBox CEO: Buyers make 70% of decision before first call

## The Discovery Call Is Dead B2B buyers are making 70-80% of their purchase decision before they ever talk to sales, according to Sam Senior, CEO of TestBox, a $12M-funded platform that lets buyers test-drive software. Speaking on the GTMnow Podcast, Senior laid out what is actually happening: buyers are using ChatGPT and Claude to research vendors, test use cases, and build shortlists. By the time they book a call, they are not looking to discover their needs together. They are looking to validate what they already believe about your product. The day one shortlist has shrunk from 3-4 vendors to 1-2. If you are not on it, the call is a courtesy. ## What This Means for AEs Your first call is now a validation call, not a discovery call. Buyers have already TestBoxed your use case in an LLM and got 70-80% of the result in 30 seconds. Your job is to bridge that gap to 100% and prove real value, which takes longer than it used to. Senior recommends auditing what LLMs are saying about you right now. Ask Claude or ChatGPT what your buyers are researching and see how your product shows up in those answers. He calls this CEO, the AI version of SEO. The mid-funnel is getting longer, not shorter. Buyers come in with high expectations and more context. That changes how you prep, how you position, and how you prove differentiation. ## Agent-to-Agent Procurement in 3-5 Years Senior laid out a timeline: LLM research today, AI-assisted trial evaluation in 12-18 months, agent-to-agent demos in 24-36 months, full AI-led procurement including negotiation within 3-5 years. The companies building for this now will have an advantage. The ones ignoring it will be scrambling when buyers stop booking calls altogether. TestBox runs 15 AI experiments per week across the company and ties token usage to performance reviews. Senior is clear: AI adoption is a culture problem, not a tools problem. It only works when it is a company-wide operating model, not just an engineering initiative. Worth noting: TestBox uses Google Vertex video analysis to read prospect body language on sales calls. That is where this is going. ## What to Do Now 1. Audit what LLMs are saying about your product 2. Reframe your first call as validation, not discovery 3. Build content that shows up in LLM research 4. Prep your team for longer mid-funnel cycles 5. Start running AI experiments across GTM, not just product The buying process has changed. Your sales process needs to catch up.

Sales Hacker
3 months ago
News

Phonely raises $22M, replaces 350 human agents in one month

## Phonely raises $22M, replaces 350 human agents in one month Y Combinator-backed AI receptionist Phonely closed a $22 million Series A led by Base10 Partners. The round values the San Francisco-based company at $139 million. The Melbourne University spinout launched in early 2024, raised $750,000 from YC mid-year, and has now pulled in $26 million total. Founders Will Bodewes (PhD AI researcher) and Nisal Ranasinghe built the product to answer calls, route inquiries, book appointments, and integrate with CRMs using a business's website URL. Setup takes 5 minutes. The platform now handles millions of calls monthly across thousands of businesses. Worth noting: one customer replaced 350 human agents in a month with Phonely. Three of Phonely's enterprise customers invested in the round: Etech Global Services, TSA Group, and Engage CX. TSA Group operates 4,500 human agents. Their head of AI said Phonely's agents "resolve calls better than our best people." Engage CX logged $14 million in insurance policy sales via Phonely in the first four months of 2026. ### Market context Phonely competes in a packed space. Beside AI (also an AI receptionist for small U.S. businesses) raised $32 million across seed and Series A from EQT Ventures, Index Ventures, and Slack founder Stewart Butterfield. Y Combinator has backed 141+ AI assistant startups, including Codyco (hotel reservations) and OpenCall.ai (AI call centers). The ecosystem skews U.S.-focused. No ANZ presence, headcount, or sales team details are public for Phonely. The company has not disclosed revenue, leadership structure, or plans for this capital beyond scaling the product. ### What this means for sales teams AI call handling tools like Phonely target the SDR and BDR layer: answering inbound, qualifying leads, booking meetings. If the 350-agent replacement holds at scale, this shifts headcount models for sales ops and inbound teams. Watch for pricing, integration complexity, and whether these tools handle nuanced discovery or just route calls. The $14 million insurance sales number suggests potential for outbound applications, but no specifics on whether Phonely does cold calling or just handles inbound. Comp implications: if AI handles first touch, does that compress SDR hiring or shift SDRs to higher-complexity roles? No data yet, but worth tracking as these tools mature.

Startup Daily
3 months ago
News

Flex Capital runs 500 AI agents for deal sourcing, predicts agent-to-agent VC meetings by 2026

## AI agents are already replacing initial VC meetings Auren Hoffman, General Partner at Flex Capital and founder of SafeGraph and LiveRamp, runs over 500 AI agents to source deals. His prediction: by the end of 2026, the first VC meeting will be agent-to-agent, with founders and investors talking through their agents before any human interaction happens. This is not a thought experiment. Flex Capital is already using AI agents to filter deal flow, assess companies, and handle initial conversations. The system is built around a core principle: missing a great deal is 10 times worse than making a bad one. The agents help Hoffman see more companies without filtering too early. Worth noting: Hoffman's track record includes early backing of Replit, Perplexity, Rippling, Vercel, Coinbase, Chime, and AppLovin. Flex Capital has invested in 120 to 180 companies, including exits like Aardvark (Google), Chomp (Apple), and Meebo (Google). ## What this means for B2B sales If VCs are automating initial meetings, enterprise buyers are next. The same economics apply: buyers want to filter vendors faster, sales teams want to reach more prospects, and AI agents can handle both. The comp implications are direct. SDRs and BDRs who focus on initial outreach are the most exposed. AEs who handle complex enterprise deals, negotiate contracts, and build relationships have more runway. But even that runway is shrinking. Hoffman also predicts that every software moat is gone. If you are not making your product significantly better every month, you will lose customers. That applies to sales tools too. Salesforce, LinkedIn, DocuSign are all vulnerable. The companies replacing them will likely use AI agents for customer acquisition. Another practical signal: Hoffman says companies will not sign yearly SaaS contracts anymore. The product landscape is changing too fast. That shifts sales cycles, comp structures, and quota setting. If your company is still building comp plans around 12-month contracts, that assumption may not hold. ## The funding context No recent funding details are public for Flex Capital. Hoffman's previous venture, SafeGraph, was valued at $370 million with backing from Sapphire Ventures, Peter Thiel, and Ridge Ventures. LiveRamp was acquired by Acxiom for $310 million in 2014 and later went public on NYSE with $280 million-plus revenue in 2019. The prediction on agent-to-agent meetings is not coming from a futurist. It is coming from an investor who has already deployed the technology and is betting capital on what happens next.

Sales Hacker
3 months ago
News

SaaStr closes 140% of last year with 1.25 humans, 20 AI agents

## The Numbers SaaStr hit 140% of Q1 2025 revenue this quarter with 1.25 humans managing 20 AI agents. Last year, they ran a full sales team of about 10 reps (SDRs and AEs). Founder Jason Lemkin made the shift after losing three reps during a conference. "I'm done hiring humans in sales," he declared at the time. The setup: two humans (one full-time, one part-time) handling closes. Twenty AI agents covering inbound response, outbound prospecting, and re-engagement. ## What Actually Changed Lemkin is honest about what he does not know. Three things happened at once: **Lead concentration.** Every qualified lead went to their best closers, not spread across a mixed-skill bench. No more fair distribution. Just efficient distribution. **100% coverage.** AI agents responded to every inbound lead instantly. Before: under 40% response rate, often days late. After: every lead, every time, including 2am on Saturday. **Full database outreach.** Human reps cherry-pick 500 prospects from a 10,000-contact list. AI agents worked all 10,000. Most were dead ends. The ones that were not became deals they would have missed. **Market tailwind.** SaaStr's business is AI-focused content and events. AI took off in 2025-26. Their product got dramatically more relevant at the exact moment they deployed AI agents. Lemkin cannot tell you the ratio. "What if we had kept the full human team AND had the AI tailwind AND concentrated leads in top closers? Would we have closed 180%? We'll never know." ## What This Means for Sales Teams The honest take: AI agents performed fine. Not magical. Professional and consistent. They handled qualification, follow-up sequences, and re-engagement without embarrassment. But Lemkin attributes potentially 50% or more of results to lead concentration in top closers, not AI itself. The AI enabled the restructure. The restructure may have driven the number. This is not a clean AI-versus-humans test. It is a restructure around top performers, enabled by AI coverage, during a market boom for their category. Worth noting: SaaStr is a conference and content business, not a typical SaaS sales org. Inbound volume, deal complexity, and sales cycle matter when evaluating whether this model translates. The real story is not "AI closed 140%." It is "We restructured sales around AI, concentrated leads, and hit a market tailwind. We shipped 140%. We cannot isolate what drove what." That is the most useful honesty in the entire experiment.

SaaStr
3 months ago
News

Caruso raises $9.3M Series A, hiring across ANZ and US

## The Round Caruso, an Auckland-founded fund administration platform, closed a $9.3M Series A led by Icehouse Ventures and GD1. Post-money valuation: $80M. Balmain, a private credit fund manager and Caruso customer, participated. This follows a $3M seed round in December 2024. ## What They Do Caruso sells AI-powered fund admin software to real estate, private credit, and private equity funds. The platform handles investor onboarding, compliance (AML/KYC), capital raising, distributions, and registry management. Current customer base: 80+ fund managers (including Centuria Capital Group and Balmain), 900 funds, 27,000+ investors. Assets under administration sit at $80-100B. Revenue up 400% in the past year (no absolute figures disclosed). ## The Hiring Push Headcount is expanding from roughly 25 to 80+ across Auckland (HQ), Sydney, and Dallas. Australian headcount will double from current levels to around 40. No specific sales roles announced. No CRO or VP Sales named publicly. Co-founders Mark Hurley (CEO) and Oliver Shaw are the listed executives. For sales professionals eyeing fintech: this is early-stage, high-growth fund admin software. If you have experience selling to fund managers or private markets, this could be worth tracking. Comp details not disclosed. ## Market Context Fund administration is a legacy-heavy space. Most platforms are clunky, manual, and fragmented. Caruso is positioning as the AI-native alternative, targeting ANZ first with APAC and North America expansion planned. Competitors in this space include Carta (equity management with fund admin features), Capdesk (equity-focused), and traditional fund admin software providers. Caruso differentiates on AI integration and serving private credit/real estate funds specifically. ## Why It Matters Series A capital typically means structured hiring plans are coming. If you are in software sales and looking at fintech, fund admin is a niche with strong margins and sticky customers. Keep an eye on Caruso's careers page over the next quarter. For now: funding secured, headcount doubling, no public sales roles yet. Worth watching if you have experience selling to financial services or fund managers.

Startup Daily
3 months ago
News

Eucalyptus $1.6B exit highlights VC gender gap in women's health

## The Exit Eucalyptus sold to US-based Hims & Hers for up to US$1.15 billion (A$1.6 billion). CEO Tim Doyle holds an estimated 10% stake, worth around US$160 million. The company hit 775,000 customers and US$450 million ARR run-rate by 2025. Four male founders. Zero women. Growth driven largely by GLP-1 weight-loss prescriptions to women. ## The Numbers That Matter In Australia, obesity rates sit at 31% for men, 32% for women. Clinical need is roughly equal. But women are 1.7x more likely to use GLP-1s in the US market, and Australian GP data shows women drive non-diabetic weight-loss prescriptions. Eucalyptus raised $50 million at A$520 million valuation in 2023. That valuation tripled via acquisition. Meanwhile, female founders in health tech report raising seed rounds at a fraction of that scale. ## The Pattern Catherine Slogrove, founder of women's microbiome health startup Amelia Bio, pointed out the disconnect. When Flo (period tracking app, all-male founding team) hit unicorn status, the backlash was immediate. Eucalyptus gets applause. Both built products primarily for women. Both had no women founders. Different reception. ## Why It Matters for Sales Teams If you are selling into health tech, enterprise buyers are starting to ask about founding team composition. DEI is moving from HR checkbox to procurement criteria. Companies building for women without women in leadership face tougher questions in enterprise deals. For sales professionals eyeing health tech roles: check who is on the founding team and who holds equity. Comp might look similar across companies, but long-term equity value depends on sustainable market positioning. Cultural pressure-driven growth has limits. ## The Comp Side No public data on Eucalyptus sales team size or CRO. The company scaled via marketing-led growth (founders came from ad agencies and Koala furniture). ARR over $450 million suggests a sizable team, now expanding under Hims & Hers. Doyle transitions to Senior Vice President of International post-acquisition. Co-founder Charlie Gearside departed early 2025. Equity distribution across the founding team remains undisclosed beyond Doyle's estimated 10%. ## Bottom Line Strong exit. Real numbers. Worth celebrating. Also worth asking why male founders building for female customers raise easier, exit bigger, and face less scrutiny than their female counterparts in the same market.

Startup Daily
3 months ago
News

Eucalyptus $1.6B exit driven by women customers, four male founders

## The Numbers Eucalyptus sold to Hims & Hers for up to $1.6B. Four male co-founders. Zero women. The platform's growth engine: Juniper, targeting women seeking GLP-1 weight loss treatments. Women use these medications 1.7x more than men (15% vs 9% in the US). Australian obesity rates are nearly identical: 31% men, 32% women. The clinical need is equal. The demand is not. ## The Pattern This is the Flo playbook. Male founding team. Female customer base. Period tracking, weight loss, fertility: women's health built by men attracts capital. Women building for women struggle to raise. The data backs this up. Female founders receive roughly 2% of VC funding globally. In health tech, the gap widens. Investors fund solutions to problems they understand. Most VCs are men. ## Why This Matters for Go-to-Market Eucalyptus reached $450M ARR and 775,000 customers before the exit. The product worked. The team executed. The market was there. But representation shapes product, which shapes retention, which shapes revenue. Cultural pressure drives women to GLP-1s at higher rates than clinical need would predict. A founding team that lived that pressure might have built differently. The comp also matters. Co-founder Tim Doyle held 10% equity, worth roughly $160M from the deal. He becomes SVP International at Hims & Hers post-acquisition. Co-founder Charlie Gearside departed early 2025, pre-announcement. ## The Question Should founding team composition matter when the primary customer is a specific demographic? The ecosystem celebrated this exit without asking. When Flo hit unicorn status with zero female founders, the criticism was immediate. Eucalyptus shipped numbers. Triple-digit YoY ARR growth in 2025. The market validated the approach. But the funding gap persists: women building for women face higher scrutiny, lower valuations, longer fundraising cycles. Worth noting: Eucalyptus was not yet profitable. After-tax loss of $15.2M in FY2024. The $1.6B valuation is structured as $240M at close, $910M in deferred payments and earnouts through early 2029. Performance-based. The real payout depends on hitting targets. ## What Sales Teams Should Watch Telehealth is scaling fast. Eucalyptus went from founding in 2019 to $450M ARR in six years. That is enterprise software velocity in a healthcare wrapper. The buyer was Hims & Hers, a US public company expanding into ANZ. Watch for hiring. International expansion usually means local sales teams, territory planning, and market education. Doyle's SVP role suggests aggressive ANZ growth plans. For anyone selling into health tech or building GTM for women's health products: the money is there. The customers are there. The representation gap remains.

Startup Daily
3 months ago
News

Pay.com.au scraps $850m IPO, takes $20m private raise instead

Pay.com.au has shelved its planned ASX IPO and raised $20 million privately instead, blaming geopolitical uncertainty from the Iran war for spooking public market sentiment. The business was eyeing an $850 million valuation on the ASX this month. The private raise valued it at $750 million, according to a company spokesperson. That is a $100 million haircut for choosing private capital over public markets. In a term sheet to investors, directors said an immediate IPO is "not in the best interests of shareholders" given current macro conditions. The business will keep watching for ASX listing opportunities, but no timeline provided. ## What this means for sales teams IPO delays usually mean hiring freezes or slower expansion. Pay.com.au has not disclosed sales headcount, recent hires, or whether the pivot changes their go-to-market plans. Worth noting: the business won Smart50 in 2024 and was reportedly planning to raise $85 million pre-IPO before the market turned. The fintech operates in B2B payments, founded by Damien Waller, Edward Alder, and Grant Austin. No public data on sales team size, CRO, or enterprise versus SMB split. ## Broader fintech context Pay.com.au joins a long list of fintechs postponing IPOs in 2025. Stripe and Klarna have both pushed back public market plans. SoftBank's PayPay and Walmart-backed PhonePe delayed roadshows citing similar geopolitical shocks. ANZ fintech has seen hiring freezes and comp cuts across the sector in 2024-2025, particularly for SDR and AE roles. When IPO plans get shelved, expansion hiring usually follows. Whether Pay.com.au is pausing sales hiring alongside the IPO delay remains unclear. The spokesperson said the business is in a "strong financial position" and choosing private capital "preserves momentum without the constraints of public market timing." Translation: they can still grow, but probably slower than an $850 million float would have funded.

SmartCompany
3 months ago
News

Anthropic hits $30B revenue with 5,000 staff: 6x more efficient than Google

## The Numbers Anthropic hit $30 billion annualized revenue in Q1 2026 with an estimated 5,000 employees. That is $6 million revenue per employee. Google needed 32,000 people to reach $30B. Salesforce needed 79,000. The revenue ramp: - End of 2024: $1B ARR - Mid 2025: $4B - End of 2025: $9B - March 2026: $30B That is 30x growth in 15 months. Investor Brad Gerstner noted Anthropic added the equivalent of Databricks plus Palantir combined in revenue in a single month. ## What This Means for Sales Teams No public data on Anthropic's sales org structure. No named CRO or VP Sales in available records. The company runs research-heavy with teams focused on Interpretability, Alignment, and Societal Impacts. Product leadership saw Tom Krieger move to Anthropic Labs in January 2026, replaced by Ami Vora. OpenAI sits at $24B revenue with 4,500 employees, planning to double headcount to 8,000 by end of 2026. Still far leaner than traditional enterprise software. Comp data: Not publicly available for Anthropic sales roles. No confirmed ANZ presence or operations. Activity centers in San Francisco. ## The Efficiency Model Anthropic's lean structure comes from focus. No multimodal sprawl, no hardware, no data centers. They picked coding and enterprise, went deep. Compute costs are relatively fixed whether revenue is $1B or $80B, so gross margins expand as revenue scales. Inference costs down 90% year over year. ## What Changes If AI companies can hit $30B with 5,000 people, enterprise software sales models shift. Traditional SaaS companies scaled headcount with revenue. Salesforce added thousands of AEs, SEs, CSMs to reach $30B. That model does not apply when your primary cost input is compute, not people. For sales professionals: Fewer seats, higher productivity expectations, different comp structures. When a company can generate $6M per employee instead of $380k (Salesforce's ratio at $30B), quota and OTE calculations change. Worth noting: Anthropic's efficiency comes from product-led motion and enterprise co-work focus, not traditional outbound sales teams. The playbook does not translate directly to most B2B companies. But the direction is clear: leaner teams, AI-assisted workflows, higher revenue per head. No data yet on how this affects quota attainment, ramp periods, or territory design for the sales roles that do exist.

SaaStr
3 months ago
News

AI agent rollouts hitting wall: FDE shortage stalling enterprise deployments

## The Bottleneck No One Saw Coming Every company rolling out AI agents at scale is running into the same problem: forward deployed engineers are impossible to hire. The shortage is not just a hiring challenge. It is a structural issue about what it actually takes to get AI working inside a real enterprise. FDEs sit at the intersection of product, engineering, and customer success. They go on-site, understand actual workflows, and configure the product to work inside those workflows. They are not building from scratch. They are not doing basic support. They are doing the hard middle work of making software actually land in the real world. Palantir built their entire go-to-market around this model. You needed their people inside your organisation, configuring and training the system for your specific context. That model worked. It was expensive and it did not scale the way SaaS was supposed to scale. But it worked, because complex software in complex environments requires human judgement to deploy well. Now almost every serious AI product has the same requirement. And almost no one has enough people who can do it. ## Why CS Cannot Fill This Gap The instinct at most companies: solve this with customer success. CS is already post-sale, already focused on adoption. Just upskill them, right? Wrong. Traditional CS was built for a different era. The job was: help customers use software they have already decided to buy, make sure they hit their renewal metrics, escalate bugs. It was reactive, relationship-driven, and optimised for retention. FDE work is different in almost every way. It is proactive, technical, and optimised for deployment. You are going in before the problem exists and configuring the system so the problem never happens. The skill set required is closer to a solutions engineer or a junior product manager with strong customer empathy than it is to a traditional CS rep. Most CS teams do not have it. Retraining takes longer than most companies want to admit. ## Agents Cannot Deploy Themselves. Yet. The whole premise of AI agents is that they automate work. But deploying an AI agent is itself significant work, and it is work the agent cannot do for you. Not yet. Someone has to understand the customer's workflows deeply enough to know where the agent fits. Someone has to train the agent on the right data, the right context, the right edge cases. Someone has to test it, catch where it breaks, and iterate. Someone has to get internal buy-in from the people whose jobs will change when the agent goes live. That is FDE work. And it is manual, high-judgement, human work. Palantir announced recently that they have gotten deployment times down over 90% using forward deployed engineers. That is remarkable. It also means the best-in-class operator in this model is still deploying manually, just faster. 90% reduction in deployment time is not the same as automating deployment. The human is still in the loop. ## What This Means for Sales Teams Every serious AI vendor is now competing for the same small pool of people who can do this work. The companies that came up through Palantir, the solutions engineers from the major cloud platforms, the implementation consultants from the enterprise software world: everyone wants them, and there are not enough of them. Meanwhile the demand is exploding. Every enterprise that decides to deploy AI agents needs FDE-calibre people to make it work. For sales teams, this creates a few realities: **Longer sales cycles.** If you cannot deploy the product, you cannot prove value. If you cannot prove value, the deal stalls. **Higher implementation costs.** Companies are paying premium rates for FDEs. That cost gets passed somewhere, usually to the customer or to margin. **New comp structures.** Some vendors are tying commission to successful deployment, not just closed deals. If the product does not land, the rep does not get paid out fully. The companies winning at deployment are building serious enablement programmes: not just documentation, but hands-on training that gives customer-side operators the skills to configure and train agents themselves. If you are selling AI tools, ask your leadership what the deployment plan actually looks like. If the answer is "CS will handle it," the answer is wrong.

SaaStr
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