Technology Intelligence

See their entire tech stack from the outside

Identify what cloud, AI models, databases, and vendors competitors use — extracted from job posts, GitHub, engineering blogs, and website analysis.

5 live sources

8 tracked signals

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What we track

Every signal in this category, monitored automatically on your behalf.

Cloud provider (AWS / GCP / Azure)

AI models in use (Claude, GPT-4, Gemini)

Database choices (Postgres, Pinecone, etc.)

Frontend / backend frameworks

Analytics and monitoring tools

CDN and infrastructure vendors

Security certifications

Tech stack from Wappalyzer

Example signal

This is the type of finding Zelos surfaces — with significance score, context, and strategic implication.

4/5 significance

Tech Stack Signal

Competitor G's job posts mention "Anthropic Claude + LangGraph + Pinecone" for the first time

Previous JDs referenced OpenAI only. New posts clearly describe a multi-agent AI architecture using Claude.

Strategic Implication

→ They're rebuilding their AI core. Monitor their GitHub for new repos and time your own AI launch accordingly.

Why it matters

Technology choices reveal architectural direction — often 12 months before a product ships. If a competitor switches to a vector database, they're building semantic search. If they start using Claude, they're going agentic.

Sources monitored

Wappalyzer (self-hosted)

GitHub repos

Engineering blog

Job descriptions NLP

USPTO patents

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