research.do
AI Agents That Research Autonomously
Intelligent research assistants that analyze data, synthesize insights, and discover patterns without human intervention. Automate literature reviews, competitive intelligence, and market research with 100x faster execution and deep semantic understanding.
import { Research } from 'research.do' // Autonomous research agents with daily intelligenceconst analyst = Research({ role: 'MarketAnalyst', sources: ['academic', 'news', 'financial'] }) analyst.every.day($ => { // Analyze competitors and generate reports const insights = $.Research.analyze.Competitors({ companies: ['competitor-a.com', 'competitor-b.com'] }) const report = $.Research.synthesize.Report({ insights, format: 'executive-summary' }) $.Email.send.Report({ to: '[email protected]', body: report })})
One of 48 primitives
research.do sits in Agents: reason, research and act. Every .do shares one grammar, Business-as-Code, and one SDK.
Data
Records, vocabulary and search
Insight
Measure, test and trace
Frequently asked questions
Research.do agents independently search sources, analyze data, synthesize insights, and generate reports without constant supervision. They formulate search strategies, evaluate source credibility, identify patterns, and draw conclusions autonomously. Configure review workflows for sensitive research or let agents operate fully autonomously for routine intelligence gathering. Agents cite sources and provide confidence scores for all findings.
Access to 100M+ academic papers (PubMed, arXiv, IEEE, ACM), news archives (20+ years), financial data (SEC filings, earnings calls), patents (USPTO, EPO), social media trends, GitHub repositories, and custom data sources via API. Agents evaluate source credibility, cross-reference claims, and detect bias. Support for private data sources (internal documents, databases) with access controls. Real-time and historical data available.
Multi-step verification process: source credibility scoring, cross-referencing claims across multiple sources, bias detection, fact-checking against knowledge bases, and confidence scoring for all findings. Agents flag inconsistencies, missing information, and low-confidence areas for human review. Transparent reasoning trails show how conclusions were reached. Customizable quality thresholds per research type.
Yes. Multi-agent research teams where specialists handle their domains—one agent analyzes technical papers, another tracks market data, another monitors social sentiment. Agents share findings, debate conclusions, and synthesize unified insights. Use $.Research.delegate.Analysis patterns to coordinate specialized agents. Full transparency into agent collaboration with decision logs.
All research data encrypted at rest and in transit. Private research projects isolated with role-based access controls. Agents never share findings across organizational boundaries. Optional on-premises deployment for highly sensitive research. Citation management tracks all sources used. Export controls for research subject to trade restrictions. Full audit trails of data access and agent decisions.