IBM Watson Discovery
Find specific answers and trends from documents and websites using search powered by AI. Watson Discovery is AI-powered search and text-analytics that uses innovative, market-leading natural language processing to understand your industry’s unique language. It finds answers in your content fast and uncovers meaningful business insights from your documents, webpages and big data, cutting research time by more than 75%. Semantic search is much more than keyword search. Unlike traditional search engines, when you ask a question, Watson Discovery adds context to the answer. It quickly combs through content in your connected data sources, pinpoints the most relevant passage and provides the source documents or webpage. A next-level search experience with natural language processing that makes all necessary information easily accessible. Use machine learning to visually label text, tables and images, while surfacing the most relevant results.
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Agent Bayes
Agent Bayes is an AI research assistant for graduate students, postdoctoral researchers and other academics. Users add papers as PDFs or sync them from Zotero, then ask questions about their library. The agent searches those sources and builds a mindmap of claims, each linked to the passage and page supporting it. Users can open a citation to inspect the passage or PDF page, and competing findings can remain on the map as separately sourced positions. AI Verification assesses whether cited passages support a claim; the feature is included in paid plans. An MCP server lets compatible tools such as Claude Code, Codex and Cursor search the user's library and work with its cited answers and mindmaps. The free plan includes 50 credits per month, and paid subscriptions start at $11/month, billed annually.
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ScholarIQ
ScholarIQ is a web-based AI research assistant for searching and reviewing scientific literature. Researchers can pose a question, search records from OpenAlex, ORCID and PubMed, or upload search results and source documents. The platform ranks articles against review criteria, supports citation-based snowball discovery, and helps users screen records, highlight relevant passages, and extract specified information from uploaded texts. Answers and suggested values link to cited sources, while reviewers retain control of inclusion decisions, risk-of-bias judgments, and conclusions. ScholarIQ records reviewer identity, decision rationale, and supporting passages to make review work traceable. It also provides a public research metadata atlas linking papers, researchers, journals, institutions, and topics. It serves individual researchers and review teams doing literature searches, evidence screening, and systematic reviews.
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Charlie
Charlie is a sovereign AI scientific agent for researchers and laboratories, specialized in biomedical research and built to accelerate scientific work with precise, sourced answers. It helps users conduct literature reviews, analyze scientific documents, organize research information, and move faster through R&D workflows while keeping traceability at the center of every response. Researchers can ask questions in natural language and get answers extracted directly from scientific documents, with page-level citations that make each source verifiable. Charlie can search simultaneously through hundreds of PDFs, synthesize information, compare articles, understand scientific context, and help users focus on discoveries instead of manual document review. Its research workspace includes libraries, projects, notes, shared collections, PDF reading, highlighting, annotation, and team collaboration, so important passages, references, and insights stay organized across devices.
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