Elata Intelligence
Project Overview
The Elata Intelligence platform gives Elata two distinct strategic advantages:
It activates instant situational awareness. Automated monitoring of science, patents, regulation, and DeSci activity is enabled such that tokenholders can respond in real time.
It feeds Elata's broader EOP technology portfolio needs in that it contributes to Elata's model-training pipeline. A continuously labelled corpus that seeds bespoke AI models for diagnosing and treating mental-health conditions is more imminent with Elata Intelligence.
With Elata Intelligence, every scraped article, patent, or clinical trial update that flows through is simultaneously a signal for cybernetic governance (e.g. "open this bounty; vote on that study") as well as a data point for precision psychiatry models (e.g. predictive modeling algorithms, risk-scoring nets, etc.).
As of right now, Elata Intelligence is in its very early days, and is geared towards fulfilling the former of the two distinct strategic advantages mentioned above.
Over the next few sprints the Elata community will continue refreshing the platform to match Elata’s new design system, wire the scraper into additional data streams (non-English journals, FDA filings, ClinicalTrials.gov entries, and global patent dockets) and syndicate the highest-value items to Discord, Warpcast/Farcaster, Reddit, X, and an email digest.
Current Platform: Elata VSM System 4 Reader
The platform acts as the DAO's environmental scanner, using GPT to process information about scientific papers, industry developments, consumer trends, developments in decentralized science, etc. This systematic monitoring allows the DAO to detect emerging opportunities, potential threats, and shifting paradigms that could impact its strategic direction. By transforming this environmental data into actionable intelligence, the system enables informed decision-making by token holders and helps maintain the organization's viability in a complex, fast-moving landscape.
The broader intent of this project is to automate as much of Elata's System 4 processes as possible using Artificial Intelligence.
Scraping engine
Hourly harvests of PubMed, arXiv, patents, grant feeds, and DeSci forums.
Node/TS, NewsAPI, custom RSS
AI tagger
GPT-4o labels topic, sentiment, molecule/device, ICD-10 tags
OpenAI functions, Zod schemas
Knowledge store
Typed JSON → Neo4j graph (R&D) with GraphQL endpoint
Neo4j
Web UI
Public feed (news.elata.bio)
Next.js 15 SSR
Agent layer (beta)
CrewAI workers broadcast alerts or draft bounties
CrewAI, Discord/X/Farcaster webhooks
Elata Intelligence Roadmap
Domain LLM (7 B)
Local Q&A, richer tagging, zero API cost implementation.
Q1, '26
Multimodal Clustering
Identify MDD/PTSD subpopulations from mutli-modal dataset: EEG (neuroimaging) and Psychometric (patient-administered test/assessment)
H1, '26
Risk-Scoring Classifier
Initiate predictive modeling algorithm development - predict treatment-response probability; triage patients.
H2, '26
Links & Resources
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