Labnote Scholar is a bio and chemistry-specific AI research assistant that structures experimental data, predicts experiment outcomes, manages reagent and MSDS records, applies RAG search over internal papers and generates reports automatically. It is sold to R&D organisations with dedicated onboarding, GLP/GMP alignment and enterprise security.
Miro is a collaborative visual workspace where distributed teams diagram, plan, and run workshops on an infinite canvas, now enhanced with AI that can generate diagrams, summaries, and prototypes from board content.
Labnote Scholar is a bio and chemistry-specific AI research assistant that structures experimental data, predicts experiment outcomes, manages reagent and MSDS records, applies RAG search over internal papers and generates reports automatically. It is sold to R&D organisations with dedicated onboarding, GLP/GMP alignment and enterprise security.
Structured experimental data capture
Capture experiments in a structured electronic lab notebook with audit-trail support, so records satisfy regulatory documentation expectations rather than living in scattered files.
AI experiment prediction
The platform applies AI to experimental design and outcome prediction, reducing trial-and-error cycles and cutting down duplicated experiments across a lab.
Reagent and MSDS management
Track reagents and manage MSDS documentation in the same system as the experiment records that consume them.
Literature RAG over internal knowledge
Retrieval-augmented search runs against the organisation's own papers, reports and prior experiments, so answers are grounded in internal knowledge rather than the open web.
优势与优点
+Purpose-built for bio and chemistry R&D rather than adapted from a generic notes product
+GLP/GMP compliance support, enterprise security and audit-traceable records suit regulated environments
AI experiment prediction targets the highest-value saving: fewer unnecessary iterations
+Literature RAG is grounded in internal papers and reports, so answers reflect the organisation's own history
+Automatic report generation directly attacks the documentation backlog researchers complain about
+Migration and setup are handled by the vendor, so research teams don't absorb the implementation load
局限性
–Enterprise-only motion — no self-serve signup or published list price, so evaluation starts with a sales conversation
–Interface and marketing content are primarily Korean, which may slow adoption for non-Korean-speaking research teams
–Value depends on instrument and workflow integrations being in place; a half-connected lab sees less benefit
–Not aimed at non-clinical academic labs or individual researchers — it is priced and packaged for organisations
Miro
Miro is a collaborative visual workspace where distributed teams diagram, plan, and run workshops on an infinite canvas, now enhanced with AI that can generate diagrams, summaries, and prototypes from board content.
Infinite collaborative canvas
An infinite multiplayer board where cursors, comments, and live editing let remote and hybrid teams work in the same space simultaneously.
Structured formats on the canvas
Docs, Tables, Slides, Kanban, and Timelines live alongside freeform drawing so a workshop can turn directly into a structured plan.
AI diagramming and synthesis
Generate diagrams, tables, and summaries, remove image backgrounds, and connect external AI assistants through the MCP server.
Templates and playbooks
6,000-7,000+ templates for brainstorming, workshops, roadmapping, and process mapping give teams a running start.
优势与优点
+Best-in-class infinite canvas that scales from a quick brainstorm to large workshops
+Structured Docs, Tables, Slides, and Kanban reduce tool switching
+Huge integration and template ecosystem including two-way Jira and Linear sync
+Strong enterprise security, SSO, and admin controls for large organizations
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