The Architect Pitch

Stop buying AI software.
Deploy an Intelligence Layer.

Most AI startups are run by engineers guessing at enterprise problems. I am an operational architect. You give me a commercial bottleneck; I deploy a lightning-quick, bespoke intelligence workflow that prints margin.

01. Avoiding the "Doorman Fallacy"

The Standard Tech Trap

Enterprise AI is being sold as a cheap headcount replacement. Fire the hotel doorman, install an automatic door, claim the savings. It optimizes for the wrong metric, destroys customer experience, and ignores the massive opportunity cost of dormant data.

Agentic Workflows

We don't build generic chatbots. We build Agentic Swarms. We ingest unstructured operational data, route it through specialized micro-agents, and push structured, actionable intel back into your ERP via API.

Let me prove it.

What operational process is bleeding the most margin in your portfolio right now?

Enterprise Architecture Deployed Latency: 1.4s
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02. Projected Economics & Scalability

Modeling capital efficiency and the data moat.

Interactive Model

Unit Economics Parameters

Enterprise deployments self-fund our operational runway. Our heavy burn rate (£8.5k/mo) isn't overhead—it's a defensive moat spent on premium data APIs (Live Markets, DATEX II, Companies House) that wrappers cannot afford.

£10k Min. Setup £1.5k/mo MRR Licensing
~£49/mo Avg ARPU Target CAC: £150
Bucket 1: Valuation Metrics
Annual Recurring Revenue (ARR)
£
Gross Margin
~85%
Bucket 2: The Cash Flow Engine
Upfront Build Capital Generated
£
Zero-dilution capital derived purely from Enterprise setup fees.
Bucket 3: Monthly P&L (EBITDA)
Total MRR £
API COGS (Compute @ 15%) - £
Premium Data & OpEx Databases, Live APIs, Base Servers
- £
Marketing Maintenance Replacing 10% SaaS churn @ £150 CAC
- £
Net Monthly Profit
£
Bucket 4: Acquisition Math
Total Marketing Capital Deployed
£
To acquire users @ £150 CAC
LTV : CAC Ratio
x
Based on 24mo retention (£ LTV). Anything over 3.0x is venture scale.