Aonxi.Tech™ – New Revenue, Engineered.
Investment Summary / Opportunity
Executive Summary: Aonxi converts sales conversations into self-learning marketing systems. Every call becomes training data for a private AI that automatically rewrites ads, landing pages, and campaigns—creating a compounding intelligence loop that expands ROI monthly without additional spend.
Live Intelligence Demo
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Marketing Intelligence
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AI Analysis Layer
Memory Brain (Layer 3)
Investment Snapshot
| Metric | Value | Note |
|---|---|---|
| ARR (first 20 days) | $200,000 | Live sales, Oct 1–20 2025 |
| CAC payback | < 30 days | Cash-neutral acquisition |
| LTV : CAC (revenue) | ≈ 12 : 1 | Per-logo compounding |
| Average Plan | $5,997 / month | Paid only; no freemium |
| Retention model | ≥ 95% | Verified + upsell |
Problem / Market Friction
Where we saw it: Working directly with 1,500+ SMBs over 2 years, generating $24M ARR.
Your marketing team guesses.
Your sales team knows.
These insights never connect.
$1.08T spent on digital advertising in 2025
Zero feedback from what actually closes deals
Distribution
Runs Google Ads, Meta campaigns. Spends your budget. Never hears the calls.
CRM
Tracks leads, logs notes. Doesn't extract intelligence or create action lists.
Analytics
Builds dashboards, tracks metrics. Sees numbers, not voices.
70% of customer insights from sales calls are never shared with marketing
Gartner Research
You pay for attention.
Not intelligence.
36.2 million U.S. small businesses face this problem daily.
Solution / Product
Every Sales Call Becomes An Algorithm
Sales → AI → Marketing → Revenue. One closed loop.
Record & Transcribe
Works with ANY phone system. Every word transcribed in real-time. 150–300 calls/month per client.
Dual Rating System
Rep rates. Owner rates. AI rates. Only 8+ calls (all three agree) become permanent truth. Quality compounds.
Extract Intelligence & Build Private GPT
Transformer-based attention finds winning phrases: "insurance approved," "timeline urgent," "3 bids."
The Moat:
These patterns become permanent memory in YOUR private GPT. No cross-pollination. Infinite switching cost.
Auto-Update 15+ Channels
One 8+ call updates: Google & Meta ads, landing pages, sales scripts, email sequences, CRM action lists, training docs.
Everything gets smarter automatically.
Compound Forever
Better ads → Better leads → More 8+ calls → Smarter AI → Better ads. The loop compounds daily.
Distribution + CRM + Analytics = One AI-Powered Nervous System
What Fortune 500 companies pay millions for—now available to every SMB.
Team / Execution Capability
The same operating team previously delivered $24M ARR selling to SMBs.
That cycle exposed the breakpoints between human calls and digital marketing.
Aonxi is the rebuilt system—same people, same GTM discipline, but re-architected so learning compounds without new spend.
No previous capital raised.
Everything to date has been bootstrapped and executed by this team.
Customer Validation (Before Rebuilding as Aonxi)
477
SMB Owners
4.91★
Average Rating
93.5%
5-Star Reviews
446 out of 477 SMB owners (managing $10B+ in collective revenue) gave us 5-star ratings on our previous execution.
Rating Distribution
477 Total Responses
Investor translation: This team has executed at scale, earned trust from operators managing $10B in revenue, and maintained 95%+ satisfaction. Aonxi is that same execution discipline—now automated and compounding.
Traction / Go-to-Market
What We've Achieved So Far
Launch
Oct 1, 2025
Results
$200K ARR in 20 days
(≈ $30K ARR/day)
Run Rate
>$3M ARR projected
Status
All paying customers
This is not theoretical. We're closing Month 1 at ~$500K ARR.
The Engine: Proven Funnel & Conversion
We have a working lead→sale→delivery engine that has been running for 1 year, is fully audited, and is operated by the team that previously generated $24M ARR selling to SMBs. This engine produces 200 qualified leads per day (scalable to 1,000/day with capital).
Unit economics: CAC is 1× first month revenue, making acquisitions cash-neutral with profit realized by ~Day 60. At a 3% lead-to-sale conversion:
Path to Scale:
- • 200 leads/day → $100M ARR in ~12 months
- • 1,000 leads/day → $1B ARR in ~24 months
Every component is auditable. You can meet the operators (Brandon Rodriguez, Levi Epps), review dashboards, inspect call recordings, and verify every KPI to the dollar.
Operational Infrastructure (Auditable)
TEAM COMPOSITION
Lead Generator → Qualifiers → Closers → Delivery
TRACK RECORD
$24M ARR, 1 year operating together
CURRENT CAPACITY
200 qualified leads/day (1,000/day with capital)
CAC POLICY
1× MRR (payback <30d, profit ~60d)
1) Auditable Funnel (From Real Operations)
Meet the Closers: Brandon Rodriguez & Levi Epps
Both available to meet. Call recordings, calendars, pipeline sheets, and conversion logs—every KPI auditable to the dollar.
Proven Performance
| Closer | Sales Revenue | No. of Sales | No. of Meetings | No. of Leads | Lead - Meeting | Meeting - Sales | Lead - Sales |
|---|---|---|---|---|---|---|---|
| Brandon Rodriguez | $30,850 | 28 | 122 | 407 | 30% | 23% | 7% |
| Levi Epps | $26,100 | 19 | 104 | 337 | 31% | 18% | 6% |
Sale Revenue
Meeting to Sale Ratio
Lead to Sale Ratio
Observed Conversion Rates
Lead → Meeting
Best: 30% | Current: 15%
Base: 21%
Meeting → Sale
Best: 20% | Current: 13%
Base: 16%
Lead → Sale
Best: 6-7% | Current: 2%
Base: 3%
Unit Economics
Average Price: $5,997/month
ARR per Logo: $71,964
Monthly Retention: 95%
CAC: 1× first-month fee (cash-neutral)
Everything is Auditable: These conversion rates come from real operations. Every lead, meeting, and sale can be verified. You can meet the team, check the engine health, review call recordings, and inspect every KPI down to the dollar.
2) 200-Leads/Day Engine (Ready; Needs Fuel)
Mechanical conversion from leads → meetings → sales using observed regimes:
| Scenario | Lead→Meeting | Meetings/Day | Meeting→Sale | Lead→Sale | Sales/Day |
|---|---|---|---|---|---|
| Conservative (current) | 12% | 24 | 13% | ~1.6–2.0% | 3–4 |
| Base (midpoint) | 21% | 42 | 13.5% | ~2.9% | ~6 |
| Upside (best month) | 30% | 60 | 20.5% | ~6.1–7.0% | 12–14 |
Note: "Lead→Sale" in each scenario is the product of the first two ratios, validated against observed 2% (current) and 6–7% (best) from the performance data above. This is auditable—the exact calculations come straight from real operations.
3) Base Engine: 200 Leads/Day (Ready Now)
Lead Flow
200 leads/day × 20 working days = 4,000 leads/month
| Metric | Formula | Result |
|---|---|---|
| Lead → Sale (3%) | 4,000 × 3% | 120 new logos/month |
| ARR per logo | $5,997 × 12 | $71,964 |
| ARR Created/Month | 120 × $71,964 | $8.64M ARR/month |
Compounding ARR (95% Monthly Retention)
| Year | Starting ARR | New ARR Added | Retained @ 95% | Year-End ARR |
|---|---|---|---|---|
| Year 1 | – | $103.7M | – | $103.7M |
| Year 2 | $103.7M | +$103.7M | $98.5M retained | $202.2M |
| Year 5 | – | Steady compounding | 95% monthly | ≈$420-450M ARR |
The Math: With 95% monthly retention, the compounding effect creates 1.22× ARR growth even with no new sales beyond the initial 12 months. This engine produces $8.64M in new ARR every month—sustained over a year, that's $103.7M ARR.
4) Upside Engine: 1,000 Leads/Day (With Capital)
Lead Flow
1,000 leads/day × 20 working days = 20,000 leads/month
We can achieve this with capital because lead generation is a solved problem in this market—Yelp, A Place for Mom, Angie, Google Maps, BBB all sell leads at scale.
| Metric | Formula | Result |
|---|---|---|
| Lead → Sale (3%) | 20,000 × 3% | 600 new logos/month |
| ARR per logo | $5,997 × 12 | $71,964 |
| ARR Created/Month | 600 × $71,964 | $43.18M ARR/month |
| Annual ARR | 12 × $43.18M | ≈$518M ARR/year |
Compounding at Scale
With 95% monthly retention and $43.18M in new ARR every month:
12 months: ≈$518M ARR
24 months: ≈$1.0B ARR
The Aonxi Difference
Unlike Yelp, Angie, and other lead aggregators who sell one lead to multiple buyers, Aonxi turns every conversation into self-learning sales intelligence.
We don't just sell leads—we make every customer a better salesperson AND a better marketer. Marketing becomes cheap for those who know how to sell, and Aonxi makes you better at both.
4) CAC → Logos → ARR (Mechanical)
Policy: CAC = 1× first month (cash-neutral acquisition)
What $1,000,000 of CAC Buys
| Plan (CAC rule) | Logos from $1M CAC | ARR Created Day-1 | Year-1 Contribution – CAC |
|---|---|---|---|
| Core ($3,000) | 333 | $11,988,000 | ≈ $4,995,000 |
| Growth ($5,000) | 200 | $12,000,000 | ≈ $5,000,000 |
| Scale ($9,997, CAC fixed $5,000) | 200 | $23,992,800 | ≈ $10,996,400 |
| Representative mix ($5,997) | ~167 | ~$12,017,988 | ≈ $5,008,994 |
Plain English:
Every $1M of CAC buys ≈$12M of ARR at the $5,997 mix (more if the mix tilts to $9,997 because CAC remains $5k).
Month-1 receipts repay CAC; per-logo profit typically appears by ~Day-60.
Example: $3M Seed Round (50% to CAC)
$1.5M to CAC → ~250 logos → ~$18.0M ARR created immediately
Year-1 contribution after repaying CAC: ≈ $7.5M
Year-2 retained ARR @95%: ≈ $17.1M
5) Economics — The Math Investors Care About
Unit Economics (Proven)
CAC: 1× month-1 → cash-neutral acquisition
Profit payback: ≈60 days
Each $1M in CAC → ~$12M ARR created Day-1
LTV/CAC (revenue): ≈8.5×
LTV/CAC (contribution): ≈4×
If We Fuel the 200-Lead Engine for 12 Months:
CAC spend: ≈$12M
ARR created: ≈$103M
LTV/CAC (revenue): ≈8.5×
LTV/CAC (contribution): ≈4×
Payback <30 days, profit ≈60 days
Valuation Lens (2025 Benchmarks)
| Peer Type | ARR Multiple | EV @ $100M ARR |
|---|---|---|
| Public SaaS (6–8×) | 6–8× | $600–800M |
| Cloud 100 Private (20×) | 20× | $2B |
| AI Infra Premium (25–30×) | 25–30× | $2.5–3B |
Therefore: The 200-lead engine sustained for one year → $100M ARR, which even at 8× ARR = $800M EV, and at AI-infra multiple 25× = $2.5B EV.
The Intelligence Flywheel
Every new logo adds verified calls that train the next logo's AI → lower future CAC, higher conversion rates, and exponentially better intelligence.
Each conversation makes the system smarter. Each customer makes the next customer's onboarding faster and more effective.
The Investment Thesis
Every lead, meeting, and sale in these charts is real and auditable.
We already have the operators, the scripts, and the technology that can generate 200 qualified leads/day today — and 1,000 with capital.
Aonxi doesn't sell leads to many buyers like Yelp or Angie.
Aonxi turns every buyer conversation into self-learning sales intelligence — making the business owner smarter, not poorer.
Marketing becomes cheap for those who know how to sell — and Aonxi makes every customer both a better salesperson and a better marketer.
The Paradigm Shift: English Is The New Coding Language
The coding language is now ENGLISH. We can code what customers are actually asking—in real-time, from live conversations—and apply actions pre-approved and audited by human experts.
Every sales conversation becomes executable code. Every objection becomes a training dataset. Every winning phrase becomes a permanent algorithm.
This is not theoretical. We're closing Month 1 at ~$500K ARR.
Everything is Auditable
This whole lead engine → meeting → sales flow — you can meet everyone, check the engine health, and verify everything.
The machine is ready to scale — we just need fuel.
This is an opportunity to make this whole sector intelligent with Aonxi.
Reverse-Engineered Milestones
What it takes to reach $100M ARR in 12 months and $1B ARR in 24 months:
Path to $100M ARR (12 months)
ARR per logo: $71,964
Logos required: 1,390
With 200 leads/day (3% L→S): ~120 logos/month → ~12 months to $100M ARR
CAC needed: ~$8.34M total ($5,997/logo)
Cash dynamics: Month-1 receipts cover CAC (1×), profit by ~Day 60 per logo
Path to $1B ARR (24 months with scale)
Logos required: ~13,896
With 1,000 leads/day (3% L→S): ~600 logos/month → ~24 months to $1B ARR
CAC needed: ~$83.33M total ($5,997/logo)
Note: Mix-shift to $9,997 plan (CAC still $5k) lowers CAC/ARR and accelerates timeline
Sensitivity Analysis: Daily Engine → Daily ARR
| Leads / Day | Lead→Sale | Sales / Day | ARR / Day (booked) |
|---|---|---|---|
| 200 | 3% | ~6 | ~$431,784 |
| 1,000 | 3% | ~30 | ~$2,158,920 |
ARR per logo = $71,964; sales/day × ARR/logo → ARR/day
Defensibility & Moat
Per-client private brain: Every 8+ rated call trains that tenant only → rising switching cost
Closed loop: We don't just analyze; we rewrite ads/pages/emails/scripts automatically
Audit layer: Cryptographic logs for ratings, model changes, actions → investors can verify CAC, retention, contribution
Same GTM operators, better product: Proven team + refined delivery
Market Size (TAM-SAM-SOM)
SMBs are the economy: SMEs represent ~99% of firms and ~50–60% of value added in OECD economies.
Digital ad spend: ~$1.08T in 2025, with ~73% of all ads now digital—and SMBs over-index on performance channels where better copy/targeting matters most.
Calls contain the truth; campaigns spend the money. Aonxi is the missing loop that makes ad dollars obey sales reality.
| Metric | Value | Note |
|---|---|---|
| US small businesses | 36.2M | SBA Office of Advocacy |
| Call-rich segments (15% filter) | ~5.5M | Home services, healthcare, pro services, etc. |
| Weighted ARPU (observed mix) | ~$5,997/mo | Live customer data |
| TAM (US call-rich) | ~$396B | 5.5M × $5,997 × 12 |
| SAM (near-term, 10% of TAM) | ~$39.6B | Serviceable addressable |
| SOM (5-year, 1% of SAM) | ~$396M ARR | Current GTM capacity |
Note: International expansion and channel partnerships (telephony/CRM networks) expand SAM significantly. Conversational AI and sales intelligence markets already showing double-digit CAGRs.
Unit Economics & Growth Engine
| Plan | MRR | CAC | Payback (cash) | Breakeven (profit) | LTV:CAC (rev) | LTV:CAC (contrib) |
|---|---|---|---|---|---|---|
| Core | $3,000 | $3,000 | < 30 d | ≈ 60 d | 12 : 1 | 6 : 1 |
| Growth | $5,000 | $5,000 | < 30 d | ≈ 60 d | 12 : 1 | 6 : 1 |
| Scale | $9,997 | $5,000 | ≈ 15 d | ≈ 45 d | 24 : 1 | 12 : 1 |
Implications an analyst would model:
- Month-1 receipts fund CAC → no negative working capital.
- Breakeven inside 60 days → twice-per-quarter cash turn.
- Every upsell ($3K → $9.9K) requires zero incremental CAC.
- Retention ≥ 95% → ARR per cohort compounds ~1.9× over 12 months.
- $1 deployed to CAC returns ≈ $6 contribution within Year 1.
Use of Funds / Capital Raise
Allocation Discipline
| Bucket | % | Function | Output |
|---|---|---|---|
| CAC Facility | 50% | Finance ~250 clients (1× CAC model) | ≈ $18M ARR Day-1 |
| Product / Engineering / R&D | 35% | Hire Whisper-lineage speech-to-intelligence engineers + deploy NVIDIA Blackwell GPUs | ↑ accuracy / ↓ unit cost |
| Ops / Delivery / Legal / G&A | 15% | Fulfillment & compliance scale | Series A-ready infrastructure |
Cohort Economics (Base Case, no upsells)
Each $1 of external funding behaves as a recurring-yield instrument rather than a burn line.
Financial Projections / Milestones
Lead-Based Revenue Model
Base Model: 200 Leads/Day
Daily Leads: 200
Conversion Rate: 3%
Daily Sales: 6 clients/day
Monthly Sales: ~180 clients
Avg Contract Value: $5,997/mo
Monthly Revenue: $1.08M
Annual Run-Rate: $12.96M
Scale Model: 1,000 Leads/Day
Daily Leads: 1,000
Conversion Rate: 3%
Daily Sales: 30 clients/day
Monthly Sales: ~900 clients
Avg Contract Value: $5,997/mo
Monthly Revenue: $5.4M
Annual Run-Rate: $64.8M
3-Year Financial Projections
| Metric | Q4 2025 | Year 2 (2026) | Year 3 (2027) |
|---|---|---|---|
| Daily Leads | 200 | 500 | 1,000 |
| Conversion Rate | 3% | 3.5% | 4% |
| ARR | $18M | $50M | $120M |
| Active Customers | ~250 | ~800 | ~2,000 |
| Net Revenue Retention | 95%+ | 110% | 120% |
| Free Cash Flow | $7.5M | $25M | $65M |
| CAC Payback Period | <30 days | <25 days | <20 days |
Key Milestones
Path to Unicorn Status: $50M ARR (2026) × 20× multiple = $1B valuation. Path to $2.5B+: $120M ARR (2027) × 25× multiple = $3B valuation.
Operational Execution Plan: 0 → $100M ARR in 12 Months
From Numbers to Action
You've seen the funnel math. Now here's exactly how we'll execute it: the team structure, quarterly milestones, role-specific OKRs, and budget allocation that turns 254 leads/day into $100M ARR.
1. Team Capacity Model
To process 254 leads/day → 70 meetings/day → 7 sales/day, here's the exact headcount needed:
| Role | Throughput Assumption | Needed Headcount | Function |
|---|---|---|---|
| Lead Generator | 3 qualified leads/rep/day | ≈ 85 | Top-funnel sourcing |
| Meeting Setter | 20 leads → 5–6 meetings/day | ≈ 13 | Scheduling + qualification |
| Closer | 5 demos/day @ 11% win | ≈ 14 | Conversion |
| Onboarding Specialist | 30 go-lives/month | ≈ 8 | Implementation |
| Success Partner | 150 accounts/partner | ≈ 19 | Retention + NRR |
Result:
254 leads/day → 70 meetings/day → 7 sales/day → $630K new MRR/month = $100M ARR run-rate
2. Quarterly Ramp Timeline
| Quarter | Leads/Day | Hiring Milestone | Focus |
|---|---|---|---|
| Q1 | 150 | 60% HC online | Tune Meeting→Sale |
| Q2 | 254 | Full HC | Stabilize metrics |
| Q3 | 254 + optimize | Maintain | Lift win-rate to 12–13% |
| Q4 | Efficiency | Steady state | CAC ≤ 2 mo; churn ≤ 2%/mo |
3. Role-Specific OKRs
Each executive owns specific metrics that ladder up to the $100M goal:
CEO — Build the $100M Engine
O1: Hit $100M ARR run-rate by Month 12
• KR1: 254 leads/day by Q2; ≥95% SLA
• KR2: 2,778 customers EOY; ≤2% monthly churn
• KR3: CAC payback ≤2 months
O2: Org Readiness
• KR4: Hire/ramp 85 LG, 13 MS, 14 Closer, 8 OB, 19 CS ≥80% pass
• KR5: eNPS ≥+40 | Offer-accept ≥60%
CRO — Predictable New Revenue
• KR1: ≥70 meetings/day by Q2; show-rate ≥70%
• KR2: Lead→Sale ≥3% | Meeting→Sale ≥10%
• KR3: New MRR ≥$8.5M/mo by Month 12
• KR4: Sales cycle ≤21 days (lead→payment)
CSO / RevOps
• SLA <5 min, data accuracy ≥98%
• Playbooks v2 by Q2; adoption ≥90%
• Real-time dashboards: Leads, Meetings, Wins, CAC, Payback
CFO
• Blended CAC ≤$1,200 (media ≤$667, comp/tools ≤$533)
• Gross margin ≥70%; Operating burn ≤plan
• Collections ≥98% on time
CHRO
• Fill plan (85/13/14/8/19) by Q2; ramp ≥80%
• OKRs issued ≤7 days from hire
• 10 of 12 months ≥100% role OKR attainment
CMO / Demand
• 92.6K qualified leads/year @ ≤$20 CPL
• ≥4 productive channels, no channel >40% dependence
• SQL rate ≥35%; brand search +300%
VP Success
• Logo churn ≤2%/mo; NRR ≥110%
• Time-to-value ≤14 days; first insight ≤7 days
• NPS ≥60; 100 case studies EOY
4. Budget Discipline
Media Spend
$1.85M/yr
@ $20 CPL
Blended CAC Target
≤ $1,200
Payback Goal
≤ 60 days
Gross Margin
≥ 70%
Competition / Positioning
Who Else is in the Market & Why We're Different
The Competitive Landscape
CallRail, Gong, Chorus.ai
What they do: Call tracking and transcription
What they don't do: Execute actions from insights. They record and report—they don't close the loop.
HubSpot, Salesforce Marketing Cloud
What they do: Campaign management and CRM
What they don't do: Learn from sales calls or autonomously rewrite campaigns based on conversation data.
Google Ads, Meta Ads Platforms
What they do: Distribution and targeting
What they don't do: Connect sales call intelligence back to ad copy, landing pages, and audience selection.
Why Aonxi Wins
1. Closed-Loop Intelligence: We don't just listen—we act. Every call automatically updates campaigns.
2. Private AI Per Customer: Each client has their own evolving AI brain. Competitors can't replicate years of compounded learning.
3. Infinite Switching Cost: Leave us = lose your private intelligence history. That's our moat.
4. Speed to Value: Customers see ROI improvements within days, not quarters.
We're not a call analytics tool. We're a revenue operating system.
Technology & Moat
What Differentiates Our Technology
The Intelligence Fusion Architecture
Real-time Speech-to-Intelligence: Whisper-lineage models convert every call into structured, actionable data within seconds.
Private AI Per Tenant: Each customer gets an isolated, continuously-learning AI brain. No shared models, no data leakage.
Closed-Loop Execution: AI doesn't just recommend—it executes. Campaigns update automatically based on conversation insights.
Reinforcement Learning: Every campaign result feeds back into the model, creating compound intelligence over time.
The Moat: Infinite Switching Cost
Compounded History: Month 1 = smart. Month 12 = genius. Your AI learns from every call, every campaign, every objection.
Private Training Data: Competitors can copy features. They cannot copy 12 months of your customer's private conversation history.
Network Effects: The more calls, the smarter the system. The smarter the system, the better the ROI. The better the ROI, the higher the retention.
Switching = Starting Over: Leave Aonxi = lose your accumulated intelligence. Start from zero with a competitor.
Technical Infrastructure
• Hardware: NVIDIA Blackwell GPUs for inference (staged deployment)
• Auditability: Every conversation, rating, and AI update recorded immutably
• Scalability: Proven at 1,500+ SMB clients generating $24M ARR
• Security: SOC 2 Type II in progress, enterprise-grade encryption
This isn't a software product. It's an intelligence asset that appreciates monthly.
Risks & Mitigations
Transparent Assessment of Major Risks
Risk #1: Hardware & Inference Cost Timing
The Risk: NVIDIA Blackwell GPU availability and inference costs could impact margins or require more capital than projected.
Mitigation: Staged Blackwell deployment with interim Hopper/H200 capacity already secured. Portable tenancy across cloud providers. Tournament-gated model deployment with safe rollbacks. Cost per inference trending down 40% YoY.
Risk #2: Competitive Response
The Risk: Large incumbents (HubSpot, Salesforce, Gong) could build similar closed-loop features and leverage existing customer bases.
Mitigation: Our moat is per-tenant learning history, not features. Competitors can't replicate 12+ months of compounded customer-specific intelligence. Switching cost increases monthly. First-mover advantage in closed-loop execution creates data flywheel competitors can't match.
Risk #3: SMB Retention Reality Check
The Risk: 95% retention seems unrealistic for SMB SaaS, which typically sees 70-80% annual retention.
Mitigation: Our 95% figure includes upsells (net retention). We target call-rich, high-intent SMBs (home services, healthcare, professional services) with proven payment behavior. The intelligence loop makes them smarter monthly—switching destroys their private AI history. Cohort tables available for diligence showing actual retention curves.
Risk #4: Go-to-Market Execution at Scale
The Risk: Scaling from 200 to 1,000 leads/day requires operational maturity, quality control, and sales team expansion.
Mitigation: Team already scaled a similar engine to $24M ARR with 1,500+ SMBs. Lead generation infrastructure proven. CAC model is cash-neutral (1× Month-1), so no burn risk. Playbook documented, hiring pipeline active, Series A investors can audit execution metrics in real-time.
Risk #5: Regulatory & Privacy Concerns
The Risk: Call recording, AI analysis, and automated campaign changes could face GDPR, CCPA, or TCPA compliance issues.
Mitigation: SOC 2 Type II in progress. Enterprise-grade encryption. Explicit consent workflows built-in. Legal review of all automation actions. Customers own their data; we're the processor, not the controller. Compliance team expanding with Series A capital.
Contact / Call to Action
Raise: $3,000,000 Seed
Use: CAC + Tech (50 / 35 / 15 rule)
Close Target: Before December 31st, 2025
Company: Aonxi Inc. — Delaware C Corp | 51% Employee-Owned
Questions are welcome; each perspective helps us refine the model.
Exit / Valuation Potential
What Kind of Multiple or Outcome Investors Might Expect
Valuation Framework & Comparable Companies
| Category | Multiple Range | Source / Rationale |
|---|---|---|
| Public SaaS (Standard) | 6–8× ARR | SaaS Capital Index (median public SaaS) |
| Cloud-Tier Private SaaS | 15–20× ARR | Bessemer Cloud 100 (high-growth, category leaders) |
| AI-Enabled SaaS with Moat | 25–30× ARR | Premium for defensible AI, data rights, compounding intelligence |
| Aonxi Position | 20–30× ARR | AI moat + per-tenant learning + infinite switching cost |
Exit Scenarios
At $50M ARR: 20× multiple = $1B valuation (unicorn threshold)
At $100M ARR: 25× multiple = $2.5B valuation
At $200M ARR: 30× multiple = $6B+ valuation (category leader)
Comparable Acquisitions & IPOs
Gong (Private, 2021 valuation): $7.25B at ~$200M ARR ≈ 36× multiple
HubSpot IPO (2014): ~20× ARR multiple at IPO, now trades at 10-15×
Salesforce Marketing Cloud: Acquired ExactTarget for $2.5B at 8-10× ARR
Recent AI-SaaS Trend: Companies with proprietary data loops command 2-3× traditional SaaS multiples
Path to $2.5-3B Valuation
~16,700 logos at $5,997/mo average = $100M ARR × 25-30× multiple
Realistic timeline: 36-48 months with proper capital deployment
Final Word
Aonxi is a verified revenue engine. The system is rebuilt to compound autonomously.
CAC payback < 30 days.
Profit in 60.
Every dollar invested becomes ARR inside the same quarter — then compounds on its own trajectory.
Aonxi.Tech™ — Conversations become code. Code becomes revenue. Revenue compounds.