P 2 4 7
Performance
Intelligence
The AI performance analyst for serious athletes
Every serious athlete generates the data. Nobody connects it into a decision. P247 does.
Myles Bruggeling | Founder
March 2026 | Pre-Seed
p247.io
01 — The Problem
Athletes are drowning in data
and still guessing
The gap is not data collection. It's data interpretation.
The average serious endurance athlete (Hyrox, Ironman, marathon, cycling) wears 1.7 devices and uses 3+ apps to track their training, recovery, sleep, and nutrition. Each app reports its own metrics. None of them talk to each other.
The result: an athlete wakes up, sees a green recovery score on Whoop, checks Garmin which says yellow, glances at their sleep score, remembers they did heavy deadlifts yesterday, and has to make a training decision with conflicting, siloed information.
3.2
Average apps used by
serious endurance athletes
$300+
Annual spend on fragmented
point-solution subscriptions
24/30
Athletes in our interviews
ignore readiness scores
P247 discovery research, 2026
Community Discovery Research (Feb–Mar 2026)
30 athletes interviewed across 4 sports, 6 countries. 5 coaches consulted with avg. 12+ years experience. In our interviews, most athletes reported ignoring wearable readiness scores during peak training blocks.
"I wore my Whoop for over 3 years. More negative mental impact than positive. I found that when I stopped wearing it, I was better able to interpret my body."
— Cortland B., Ironman athlete (Facebook)
"I'm in the process of thinking about getting generic sensors to upload data to the cloud and get an LLM to crunch it for me based on my own requirements."
— r/whoop user, March 2026 (attempting to build what P247 does)
Sources: P247 community interviews (Feb–Mar 2026, n=30) · Strava Year in Sport (2025)
02 — The Solution
The tool that turns wearable data
into a daily training decision
P247 reads your Garmin, Whoop, Apple Health, Strava, and nutrition data overnight and sends you one clear signal each morning: what your body is actually saying, and what today should look like.
Wearables = blood tests | P247 = the doctor
Your wearable runs the test. P247 reads it, cross-references your history, and tells you what to do about it.
What P247 Does
Daily Morning Brief
Proactive, personalised, delivered before your session via Telegram/push
Multi-Source Synthesis
HRV + sleep quality + training load + nutrition + subjective feel, cross-referenced
Adaptation Tracking
Monitors how your body responds to the same stimulus over weeks and months
Transparent Reasoning
Every recommendation explains why, not just what. No black-box scores.
What P247 is NOT
Another dashboard or visualisation tool
A training plan generator
A coach replacement
A hardware product
Another black-box recovery score
A generic fitness app
How It Works
🔗
Connect
Link Garmin, Whoop, Apple Health, Strava + nutrition. Takes 2 minutes.
🌙
Sleep
Overnight, P247 ingests biometric data + cross-references training history.
☀️
Wake
Morning brief: readiness score + reasoning + what today should look like.
📈
Learn
Builds a personalised model of your recovery, stress, and adaptation rate.
Why We're Doing This Manually First
The first 50 athletes get a human-AI hybrid analyst: founder-curated briefs using real data. This is a deliberate strategic choice, not a placeholder while we build. You can't automate an interpretation framework you haven't validated. The concierge phase is the product.
02b — The Product
What the morning brief
actually looks like
Delivered via Telegram before the athlete's session. Clear, actionable, transparent.
P247 MORNING BRIEF
Good morning Myles.
WHY
• HRV down 12% from your 7-day baseline
• Sleep quality: 68% (below your avg of 78%)
• Heavy strength session yesterday (deadlifts + squats)
• Cumulative training load is elevated this week
RECOMMENDATION
• Zone 2 aerobic run (30–40 min)
• Skip threshold intervals today
• Prioritise protein intake post-session
• Tomorrow looks better for intensity
ADAPTATION TREND
Your recovery from strength sessions has improved 15% over the last 4 weeks. Your body is adapting well to the current load. Stay the course.
This is what athletes receive every morning. Clear signal. Transparent reasoning. Actionable recommendation.
Who This Is For
Our ideal customer profile
Demographics
30–45 year old serious amateur athlete. Training 6–10 hours per week. 2+ races per year. Already spending $500+/year on gear, apps, and nutrition.
Devices
Garmin + Whoop (or Oura). Uses Strava. May track nutrition via MyFitnessPal or Cronometer. Has done an InBody scan at least once.
Behaviour
Checks recovery score every morning. Sometimes ignores it. Has tried correlating data manually (spreadsheet, journal). Wants to train smarter, not just harder.
Frustration
Conflicting scores across devices. No single source of truth. Knows the data is there but can't turn it into a decision without spending 20 minutes every morning.
03 — Market Opportunity
Bottom-up: $54M–$135M TAM
The athlete performance market is large, growing, and underserved by existing tools.
| Segment |
Size |
Why P247 |
| Hyrox athletes |
~300K registered globally |
Mixed-modality training (run + functional) breaks every existing load model. No wearable handles it. |
| Ironman / triathlon |
~2M active globally |
Swim/bike/run load differently. Recovery is the competitive edge, not more training. |
| Marathon runners |
6.4M finishers/yr (US) |
Overtraining and taper errors cost race results. HRV trend + load context prevents both. |
| Serious gym + endurance |
~12M dual-training |
Strength training fatigue is invisible to every wearable. P247 fills the gap. |
TAM Calculation (Bottom-Up)
Serious amateur endurance athletes globally: ~15M
(Hyrox 300K + Ironman/tri 2M + marathon 6.4M US alone + dual-training ~12M, with overlap)
If 2–5% adopt P247 at $180/year = $54M–$135M TAM
Beachhead Market
Hyrox + Ironman athletes in English-speaking markets (Australia, UK, US, Canada)
These athletes are data-literate, already spend on wearables and apps, and compete in events with clear periodisation windows (which drive subscription retention).
Serviceable Obtainable Market (Year 1)
50,000 athletes at $15/month = $9M ARR potential
Conservative 2% capture rate of addressable Hyrox + Ironman audience in English-speaking markets.
04 — Discovery Research & Early Signals
The market is telling us
what to build
Pre-product validation, February–March 2026. We are deliberately pre-product.
Before writing a single line of code, we ran a structured discovery campaign across Reddit (9 subreddits) and Facebook groups (6 groups) to test whether the problem is real, urgent, and worth paying to solve. This is not traction. It's customer discovery done properly before committing engineering resources.
Pain Theme Breakdown
| Pain Theme | # | Example |
|---|
| Score ≠ how I feel | 8 | "Green recovery, legs destroyed. Ignored the score." |
| Data as noise, not signal | 6 | "Mostly I just get the noise but don't do anything about it." |
| Abandoned device entirely | 4 | "Threw the toys away, listen to my body." |
| Built own system | 3 | "I manually correlate InBody + Strava + Apple HRV in a Google Sheet every Sunday." |
| Overhead too high | 2 | "Too much work for me to do year round" (Ironman athlete) |
Content Traction (Week 1)
p247.io Blog
10 SEO-targeted posts in 7 days. "[Device] + [Frustration]" search queries.
Reddit Engagement
50+ organic replies across 4 subreddits. Users independently describing what P247 builds.
X/Twitter
Daily posting schedule live. 2 threads/week with p247.io CTA.
Market Timing
Competitor (athletedata.health) entered same Reddit threads. Validates the timing.
Key Insight
One Reddit user (r/whoop) described building exactly what P247 does: "getting generic sensors to upload data to the cloud and get an LLM to crunch it." The market isn't just ready. It's trying to build this itself.
05 — Competitive Landscape
Every tool interprets one dataset.
None interpret the whole system.
| Player | What They Do | What They Miss |
|---|
| Whoop ($288/yr) |
Recovery + strain scoring via HRV/RHR |
No training context, no nutrition, no strength load, opaque algorithm |
| Garmin (free) |
Training readiness, body battery, load focus |
Doesn't factor gym work, no nutrition, can't distinguish fatigue types |
| Oura ($72/yr) |
Sleep + readiness scoring |
No training load, no sport-specific context, passive only |
| TrainingPeaks ($120/yr) |
CTL/ATL/TSB load model |
No recovery data, no sleep, no nutrition, conflates load types |
| Athlytic ($36/yr) |
Apple Health visualisation |
Basic recovery scoring, no synthesis, no periodisation |
| Superset Health |
AI-powered training + recovery insights |
Early stage, limited multi-device integration, focused on Apple ecosystem |
| HRV4Training ($10/yr) |
HRV-based readiness + training guidance |
Single-metric focus (HRV only), no multi-source synthesis, no nutrition |
| Garmin Coach (free) |
AI-powered adaptive training plans |
Garmin-only ecosystem, no third-party device data, plan-focused not interpretation-focused |
P247's position: We don't compete with wearables. We sit on top of all of them. The more devices an athlete owns, the more valuable P247 becomes.
Real Moats (Data Advantages)
01
Personal Data History
The longer you use it, the better it gets. Switching means starting over. High switching cost from day one.
02
Individual Response Curves
Session → fatigue → adaptation → next session. Athlete A: HRV drop = 2-day fatigue. Athlete B: same drop = 4 days. We learn personal physiology models. Very hard to copy.
03
Dataset Moat
After 10,000 athletes: sleep vs load vs adaptation patterns at scale. Aggregate intelligence improves every recommendation.
Why Device Companies Won't Win
Device companies optimise for hardware sales. P247 optimises for performance outcomes. Different incentives. Apple entering validates the market and increases wearable adoption. We have 12–18 months to own the niche.
06 — Business Model
SaaS subscription with
event-driven retention
Core
$15/month
- Daily morning brief
- Multi-device sync
- Readiness scoring + reasoning
- Adaptation tracking
- Basic periodisation
Pro
$25/month
- Everything in Core
- Event-specific periodisation
- Nutrition integration
- Advanced sleep analysis
- Exportable reports
- InBody integration
Team (future)
$20/athlete/mo
- Coach dashboard
- Team-wide readiness view
- Group periodisation
- Squad management
Unit Economics (Target Benchmarks — Pre-Revenue)
$18
Blended ARPU
(monthly)
12mo+
Target avg.
retention
$216+
Target lifetime
value
These are target benchmarks based on comparable consumer SaaS (Whoop: ~14mo avg retention, Strava: 12mo+). Actual retention will be validated during the concierge beta.
Retention thesis: Event cycles drive re-engagement. Personalisation deepens over time (leaving means starting over). Daily touchpoint creates habit loop. Post-event churn is the key risk we're validating in beta (see Risks slide).
07 — Go-to-Market
Community-led growth,
founder-driven credibility
Phase 1: Earn Credibility
Now – June 2026
- Founder-led authority content
- Community participation (Reddit, Facebook, forums)
- Athlete stories and case studies
- X/Twitter: daily posts + 2 threads/week
- Waitlist on p247.io
Phase 2: Concierge Beta
July 2026
- 50 athletes get a human-AI hybrid analyst (concierge is the product, not a prototype)
- DM outreach to validated pain-signal athletes from discovery
- Timed with Hyrox season (Jul–Nov) + marathon training cycles
- High-touch feedback: validating interpretation framework before automating
Phase 3: Scale
September 2026+
- Product-led growth: 7-day free trial
- Referral loop (athletes share brief)
- Event partnerships + Hyrox activations
- Coach channel (B2B2C)
Customer Acquisition
| Channel | Expected CAC | Notes |
|---|
| Organic (SEO + social) | $0–5 | Primary channel. Founder-led content. |
| Community referral | $8–12 | Athlete referrals, event-driven virality |
| Paid social (Phase 3) | $25–40 | Targeted Whoop/Garmin owners |
| Coach partnerships | $15–20 | Coach recommends to groups |
Blog and community are the core growth engine, not just marketing.
08 — Technical Approach
LLM = reasoning layer.
Metrics = deterministic signals.
The training model itself is deterministic. LLMs explain the recommendation, not make the decision.
Athlete Data
Garmin · Whoop · Apple Health · Strava · Nutrition · InBody
▼
Multi-Source Ingestion
Overnight batch processing. Normalise data across sources.
▼
Deterministic Scoring Engine
Recovery thresholds · Load ratios · Adaptation curves · Periodisation state
▼
LLM Reasoning Layer
Synthesises context. Generates natural-language explanation. The "why" behind the score.
▼
Morning Brief
Delivered via Telegram / push notification before the athlete's session.
This architecture prevents hallucination risk. The underlying signals (HRV, TSS, sleep stages, nutrition macros) are hard data. The LLM synthesises context and explains why the recommendation makes sense.
Stack
Next.js + Supabase
Lean, fast-to-iterate. Standard modern SaaS stack.
Claude API (Anthropic)
Reasoning layer. Contextual synthesis and natural-language output.
Stripe
Subscriptions, billing, payment processing from day one.
Build Philosophy
Manual concierge first to validate interpretation framework, then automate. No over-engineering before PMF.
10 — Why This Is Inevitable
The interpretation layer is the
next evolution of the wearable stack
2015
Athletes buy wearables
2020
Athletes track everything
2025
Athletes drowning in data
2026
The interpretation layer emerges
P247 = the next layer of the stack
Every technology market follows the same pattern: first hardware, then data collection, then data overload, then an intelligence layer that makes sense of it all. Wearables are at stage three. P247 is stage four.
This Is Not a Feature. It's a Platform.
The morning brief is the entry point. The platform becomes the athlete's central nervous system for performance.
Daily Brief
→
Training Advisor
→
Race Strategy
→
Coach Platform
→
Athlete OS
Addressing the "Feature vs Company" Question
"Isn't this just a feature Whoop could add?" No. Whoop reads one device. P247 reads all of them. The value increases with every data source connected, every week of history accumulated, and every athlete on the platform. This is a data network, not a feature.
11 — Risks & Mitigation
What could go wrong
and how we're thinking about it
Founders who've thought about risks are more credible than those who don't mention them.
API Dependency
Risk: Garmin, Whoop, and Apple Health can change API terms, restrict access, or build competing features at any time. This is existential for a platform that sits on top of their data.
Mitigation: P247 integrates via standard health data APIs (HealthKit, Garmin Connect IQ, Whoop API). These are public developer platforms that companies maintain to grow their ecosystems. We also support manual data entry and CSV import as fallbacks. Long-term, open standards like Apple HealthKit and Google Health Connect reduce single-vendor lock-in. If one API closes, the multi-source model means P247 still works with the remaining sources.
Medical / Liability Exposure
Risk: Telling athletes what their body "should" do today edges into health advice. Regulatory frameworks in AU/US may apply.
Mitigation: P247 provides training context and interpretation, not medical advice. Every brief includes a disclaimer. We do not diagnose conditions or prescribe treatment. The sports science advisor (Month 2 hire) validates the interpretation framework stays within wellness/performance guidance. We've reviewed comparable products (Whoop, Oura) that operate successfully in this space with similar disclaimers.
Competitive Response
Risk: A well-resourced competitor (Whoop, Garmin, or a YC startup) could build multi-source integrations and enter this space.
Mitigation: Device companies have a structural incentive to keep users inside their own ecosystem, not integrate competitors' data. A startup could build integrations, but the individual response curves and training history data (our core moat) take months of per-athlete data to replicate. Speed matters: we have 12–18 months of niche positioning before the space gets crowded. Our concierge model also means we're building relationships, not just software.
Post-Event Churn (Core Business Risk)
The biggest retention question: what happens after an athlete finishes their race? Our hypothesis is that adaptation tracking and off-season base-building make P247 more valuable between events. The concierge beta is specifically designed to test this. If post-event churn is high, we pivot toward coach-to-athlete subscription (Team tier) where the coach maintains the relationship year-round.
12 — Path to Subscribers
How we get from 0 to 1,500
These projections are grounded in specific acquisition mechanisms, not assumptions.
Month 1–3
50 concierge beta athletes recruited via DM outreach to validated pain-signal contacts from discovery research. Conversion target: 30% of qualified leads → beta participant.
Month 4–6
Beta → paid conversion. 50 beta athletes refer 2–3 peers each. Organic content drives waitlist signups. Target: 200 paying subscribers (50 converted + 150 organic/referral).
Month 7–12
Product-led growth kicks in (7-day trial). Hyrox season (Jul–Nov) + marathon training (Aug–Oct) drive seasonal demand. Coach channel opens. Target: 1,500 subscribers.
Key Growth Assumption
The 200 → 1,500 jump requires the product-led growth loop (7-day trial), coach channel, and seasonal event demand to fire simultaneously. The "beta athletes refer 2–3 peers each" assumption does a lot of heavy lifting. This is the growth assumption we'll stress-test hardest during beta. If referral rates are lower, we adjust the timeline, not the model.
Revenue Milestones
| Milestone | Subscribers | MRR | ARR |
|---|
| Month 6 (beta) | 200 | $3,600 | $43K |
| Month 12 | 1,500 | $27,000 | $324K |
| Month 24 | 8,000 | $144,000 | $1.7M |
| Month 36 | 25,000 | $450,000 | $5.4M |
13 — The Ask
$250K AUD
Pre-seed on $3M SAFE · 18 months runway
Use of Funds
48%
Engineering
$120K
Full-stack hire + API integrations + morning brief engine. Product validation.
20%
Growth
$50K
Content production, SEO infrastructure, community management, event activations.
16%
Product Validation
$40K
50-athlete concierge beta, sports science advisory, interpretation framework.
16%
Operations
$40K
Infrastructure (hosting, APIs, LLM costs), legal, accounting.
Why $3M Cap
Comparable AU/NZ pre-seed SaaS rounds (2024–2025) have closed at $2.5M–$4M caps with no product revenue. P247 has validated demand, a clear beachhead market ($54M–$135M TAM), a differentiated technical approach, and strong founder-market fit. $3M reflects the stage while leaving room for meaningful seed-round markup.
Milestones This Capital Achieves
Month 3
Working MVP: Garmin + Strava integration, morning brief delivery via Telegram
Month 6
200 paying subscribers, validated interpretation framework, Whoop + Apple Health live
Month 9
1,000 subscribers, event periodisation shipped, coach tier in beta
Month 12
$27K MRR, ready for seed round
What We've Done With $0
30 athletes interviewed + 5 coaches consulted · 10 SEO blog posts in 7 days · 50+ organic community conversations · $0 spent on paid acquisition
Let's talk.
P247 is building the analyst layer that serious athletes are already trying to build themselves in spreadsheets.
The market is validated. The timing is right. The founder lives the problem every day.
myles@p247.io · p247.io