Resources
Go deeper on the intelligence layer
The technical detail behind Altitude AI — architecture, capabilities, security, and integration — plus the developer references for building on it.
Whitepapers
The argument and the architecture — start with the comparison, then go deep on the engineering.
Explainer
Computed, Not Predicted
Altitude AI vs. a general-purpose LLM
The eight quantitative questions clients ask every day — beta, Sharpe, what regime are we in, is this strategy any good — with a general-purpose LLM's answer set next to Altitude AI's computed one. Same underlying model, tools off versus on.
- Why a bare LLM predicts the number and Altitude AI computes it
- Eight real question pairs from one live session — tools off vs. on
- The validation & honesty layer: standard errors, confidence intervals, overfitting checks
Explainer · 14 pages · PDF
Technical whitepaper
Altitude AI: Technology Whitepaper
Architecture, methodology, security & reliability
The architecture behind the intelligence layer — why a frontier LLM can reason but can't compute, and how Altitude's purpose-built toolset returns computed, reproducible answers the model only explains.
- The quantitative engine, macro-regime model, and AI advisor agent
- MCP + bring-your-own-data, plus the security and reliability posture
- What's live in production today versus on the roadmap
Technical whitepaper · 17 pages · PDF
Developer references
API documentation
Full REST reference, authentication, rate limits, and error formats — public, no login required.
Read the docsDeveloper portal
Create an account, manage API keys, explore endpoints in the API playground, and track usage.
Open the portalIntegration guides
Connect Altitude AI to the tools you already use — Claude.ai, n8n, the OpenAI SDK, and more.
Browse guidesFAQ
What Altitude AI is, who it's for, how it's secured, and what it costs — answered plainly.
Read the FAQReady to see it?
Book a walkthrough and we'll show you the platform and the API on your own use case.