TELOS TELOS F1
AUS GP | 00D : 00H : 00M : 00S
Connexa Studios — Case Study

TELOS: an accountable AI product, built lean and shipped fast.

TELOS is a live Formula 1 intelligence platform: an AI prediction engine that publishes its picks before every race and grades itself in public, a chatbot grounded on real timing data, and a programmatic SEO machine. This page documents how we build — because we build the same way for clients.

2,000+Indexable pages, generated programmatically
~€0/moMarginal AI & data cost via aggressive caching
100%Predictions timestamped & publicly graded
WeeksIdea → production, not quarters

01The problem we set ourselves

AI products usually fail in one of two ways: they hallucinate (confident nonsense, zero grounding) or they hide (no track record, no accountability). We wanted to prove an AI product can do the opposite of both — make verifiable claims from live data, publish predictions before the event, and keep the receipts forever.

The proving ground: Formula 1, a domain with brutal ground truth. Every two weeks reality grades your model in front of millions.

02The architecture — deliberately boring

No Kubernetes, no vector database, no framework-of-the-month. TELOS runs on a standard PHP host with a MySQL database. The sophistication is in the data layer, not the infrastructure bill:

Grounding over guessing

Every AI answer is assembled from a live context pack — standings, full race classifications, race-control incidents, fresh press headlines — fetched per question and cached. The model summarises evidence; it doesn't invent.

Cache-first economics

Every upstream call (timing API, standings, news, LLM) flows through a caching layer with sensible TTLs. Result: thousands of page views cost cents, and rate limits never become outages.

Graceful degradation

Model fallback chains, retry with backoff, best-effort context blocks. Any single upstream can fail and the product stays up — it just gets slightly less clever.

SEO as architecture

Every GP, driver, season, recap and even every chatbot question is a server-rendered, canonical, structured-data-rich URL. Distribution is built into the data model, not bolted on.

03The accountability loop

Before every Grand Prix, the TELOS model writes its podium prediction to the database with a timestamp. After the race, an autopilot fills in what actually happened. The result is a growing, irreproducible dataset of AI predictions versus reality — published in full on the accuracy page. No human tipster exposes themselves like this; that asymmetry is the product's moat.

The same philosophy runs through the Race Engineer chatbot (every answer cites clickable sources), the title-race calculator (pure math, no vibes) and the Strategy Sandbox (your pit calls, simulated against the real race).

04What shipped

Prediction engine

Pre-race podium picks with a public, season-long track record.

Race Engineer AI

Grounded F1 chatbot with live web search, cited sources and conversation memory.

Beat TELOS

Users pick podiums against the AI; a leaderboard keeps score.

Strategy Sandbox

Interactive pit-stop simulator built on real stint and degradation data.

Embeddable widgets

Standings and prediction widgets any site can embed — distribution as a feature.

Full SaaS plumbing

Auth, Stripe billing, plan gates, push alerts, GDPR consent, observability.

Want this build discipline on your product?

Connexa Studios designs and ships AI products end-to-end: grounding pipelines, accountable models, programmatic SEO, lean infrastructure. TELOS is the live demo — your industry is next.

Talk to Connexa Studios Typical engagement: prototype in weeks · fixed scope · you keep the IP