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Business Case

AAMP Onsite

One engine. Every brand, every market, every match.
The case for scaling AI-driven, on-brand, compliant betting content & personalisation — through the CEO, CFO and founder's lens.
Structured on the Sequoia business-plan framework
CONFIDENTIAL
What we are
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✦Company Purpose
One live feed in.
A complete betting experience out.
AAMP Onsite turns one live data feed into a complete, on-brand, compliant betting experience — content, odds, insight and personalised offers — for every brand, market and league, from a single engine.
Build once
Serve everyone
Update everywhere
Why it hurts
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✦Problem
Teams already use AI.
The process is still slow and manual.
Today's workflow Request→ Produce→ Hand off→ Publish→ Report — every step a request, a wait, a handover. Repeated per brand.
01✕

Slow and sequential

Each step waits on the one before, across several teams. A new league or market still takes weeks.

02✕

Flat & late

One-size content, no personalisation, no real-time. The same five insights on every brand.

03✕

Paid for N times

3–100 brands × markets each fund the same work, with no shared leverage.

04✕

Hooked on bonuses

With no relevant, timely content in the bettor's own language, we lean on costly welcome bonuses to win and keep players — instead of the right bet at the right moment.

What we built
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✦Solution
One governed standard.
Differentiation is a config, not a rebuild.
01✦

Data → everywhere

Sportradar + Kambi + AAMP mining in; on-site, video, radio, social, DOOH, push, CRM out — plus a real-time Recommendations API.

02✦

Brand = CSS + DAM + prompts

Everything else is shared. A new brand or market is configuration, not engineering.

03✦

Compliant by construction

OBG-only odds, banned-phrase guards, jurisdiction- and locale-aware output.

04✦

One update → all tenants

Improve the engine once; every brand, market and language gets it instantly.

The timing
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✦Why Now
The technology crossed the line in 2024–25.
01

AI is production-grade — and cheap

LLMs, text-to-speech and avatar video are now good enough and low-cost enough to run real betting content at scale.

02

The window is tiny

The hour before kickoff plus in-play carry >70% of activity — a few hours per match, then it’s gone. Miss the moment, miss the bet.

03

Regulation rewards a standard

Governed, auditable, locale-correct content is a compliance advantage — not just an efficiency play.

04

Margins are under pressure

Content cost and speed-to-market are now a competitive battleground for operators.

The prize
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✦What changes for us
From a cost centre to a multiplier.
Time to market
Weeks and months
→
Seconds and minutes
Cost
A team + agency per market
→
Build once. Adding one is almost free
Headcount
A squad per brand
→
One small team runs them all
Output
Capped by who we hire
→
Unlimited — every match, market & language
Control & risk
Scattered, hard to check
→
One standard, compliant everywhere
The alternatives
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✦Competition
Everyone has a piece. No one has the graph.

In-house, per brand

Slow, costly, flat. Rebuilt market by market. No personalisation, no shared leverage.

Generic CMS / agencies

Not real-time, not data-bound, not compliant-by-design. Humans in the loop for every asset.

Point AI copy tools

Words without the data, odds, governance, omnichannel or decisioning underneath.

✦AAMP's moat
The governed binding graph (data ↔ odds ↔ content) + one standard across all tenants + omnichannel from one source + a real-time decision layer. No competitor has the combination.
How it works
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✦Product
Channels ask. AAMP answers — in real time.
→Request
A surface asks for the ideal content — and can name the product to feature.
brand × market × surface × audience × moment × product
→
◆ AAMP core
  • Look updata · odds · gems · intelligence
  • Deciderank the ideal · OBG · jurisdiction · locale
  • Compile & produceLLM · TTS · images · avatar video · pre-warmed + just-in-time
  • Delivercompliant · localized
→
Delivered →
The ideal, compliant, localized content lands on the requesting surface — instantly.
↩Engagement & outcomes → analytic trends → sharpen the next request
Fed by Sportradar · Opta · Kambi (OBG) · KSP (OBG) · AAMP mining · DAM · competitor-odds & trend intelligence · compliance
Delivered to Product Pages · Onsite Reels · Social · Display · Online Video · DOOH · TVC/Live · Radio & Spotify · Push · CRM · Affiliate | × markets × brands · real-time
The economics
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✦What it costs us
One cost base for everything —
and it gets cheaper per output as we grow.
01
One bill, not many — a small team and some servers run every brand, market and channel. We don't pay again for each new output.
02
Almost free to add one — a new brand, market, league or channel is just settings. No new team, no rebuild. A few cents of AI per match.
03
Cheaper as we grow — the more outputs on the engine, the lower the cost of each. Scale lowers unit cost — the opposite of normal content.

"The more we grow, the less each output costs."

Operating leverage
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✦Team
3 → 100
tenants without a bigger team. One small, expert team runs the whole portfolio — because the governed standard does the heavy lifting.
01

Platform & technical guardianship

Owns the standard, architecture and the air-tight governance that lets one change flow safely to every tenant.

02

Automation replaces squads

Generation + compliance + localisation are automated — no per-brand editorial, design or dev teams.

03

Headcount flat as tenants grow

3 → 100 tenants without scaling the team. That is the operating-leverage story.

The model
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✦Financials
Cost to serve is a rounding error.
The prize is the handle.
€1–3
all-in AI + compute per match
€1–2k
servers per year — shared across all tenants
<0.5%
turnover lift funds the whole platform*
01 — Content-cost displacement

Collapse the spend

Editorial + agency per market, collapsed into one engine.

02 — Speed-to-market

Days, not weeks

A new league or market live in days, not weeks.

03 — Turnover uplift  ·  the big lever

Where it pays back

Break-even = platform cost ÷ (handle × GGR margin) — a fraction of one percent of turnover. Every point above that is profit. Finance to confirm the inputs.

*Break-even uplift, not a forecast — no invented revenue. Insert the group's real handle and GGR margin and the model returns the exact figure. Content + headcount savings are upside on top.
The ask
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✦The Ask
Turn a prototype into a proven business.
1

Measurement & optimisation loop

Track what each piece of content and offer actually drives. Prove the turnover uplift — and unlock v2 AI decisioning.

2

Compliance engine + legal owner

Per-jurisdiction ad rules, encoded and auditable. The gate that lets us scale across markets safely.

Then scale from 3 to 100 — on one standard, one team, one update at a time.