Features
Explore Mode
“Upload a paper, ask a question, get an answer grounded in exactly what the authors wrote.”
Most researchers read papers in a viewer on one screen and take notes in another. Curiescious brings this together: a split-screen environment where every answer references your specific paper, not general AI training data. Hallucination about paper content becomes structurally impossible.
Split-screen viewer
Scrollable, zoomable PDF alongside contextual chat
Text-to-question
Select any passage to auto-populate a grounded query
Auto-summaries
Key claims, methods, and limitations flagged on upload
Database links
Gene names and terms auto-link to NCBI and UniProt
Highlight & note
Annotations save to your chapter and stay queryable
Citation export
DOI resolution and formatted refs with one click
ANALYSIS
p = 0.002
significant
Pathway enrichment?
Analyze Mode
“Upload a CSV and talk to it. Every chart shows the code that made it.”
Curiescious recognizes biology in your data. Gene identifiers trigger enrichment suggestions. Time-series triggers trajectory analysis. Treatment/control triggers differential workflows. Every output is transparent — the code is always visible.
Instant data profile
Column types, distributions, quality flags on upload
Natural language charts
“Plot expression vs. time” generates interactive visuals
Full code transparency
Collapsible code panel for every analysis step
Bio-specific analysis
DE, GO, GSEA suggestions from your data structure
Image analysis
Gel bands, Western blots, microscopy quantification
Figure export
SVG and PNG at publication resolution, labeled
Deep Research
“Upload 5–10 papers and get cross-document reasoning. Where do authors agree? Where do they conflict?”
The output is structured for cognitive clarity: Common Patterns, Conflicts and Gaps, and Next Steps with actionable experiment ideas. Every claim links to a specific document and page. Cross-document reasoning that would take weeks manually happens in minutes.
Bundle upload
Drag-and-drop up to 10 files with auto-deduplication
Cross-doc reasoning
Agreements, conflicts, and gaps across all sources
Structured synthesis
Patterns, Conflicts, Gaps, Experiment Ideas sections
Traceable citations
Every claim linked to specific document and page
Bundle search
Query across all documents simultaneously
Dynamic bundles
Add or remove docs mid-session without losing synthesis
Design Mode
Describe your experiment in plain language. Get a protocol, controls, sample size calculation, reagent list, and failure mode analysis — before you touch the bench.
Protocol generation
Full step-by-step from your natural language description
Control suggestion
Positive, negative, vehicle, and loading controls
Power analysis
Sample size calculators with biology-specific defaults
Failure mode analysis
Most common pitfalls flagged before you start
Develop Mode
Generate Nextflow DSL2, Snakemake, or WDL pipelines that understand NGS workflows — with BQSR, scatter-gather, container definitions, and inline biological rationale for every parameter.
NGS-aware generation
Knows GATK, STAR, samtools, BWA, DESeq2 quirks
Multi-language
Python, R, Bash, Nextflow DSL2, Snakemake, WDL
Container definitions
Conda YAML, Docker and Singularity auto-generated
Code review mode
Paste scripts for optimization and bug detection
Interpret Mode
Upload a figure and get a structured interpretation. Band identification, gating strategies, cell morphology, artifact flagging — in plain language.
Gel analysis
Band ID, MW estimation, intensity quantification
Flow cytometry
Gating strategy and population identification
Pathways Mode
Paste a gene list or pull from Analyze mode. Map to KEGG, Reactome, STRING, and GO with ORA and GSEA enrichment. Interactive networks. Drug-target mapping via PubChem and DrugBank.
Pathway mapping
KEGG, Reactome, WikiPathways, Gene Ontology
Drug-target mapping
PubChem and DrugBank integration for translational work
Write & Review
Write mode knows the difference between a compelling introduction and a vague one. It structures discussions from the inside out — findings, mechanisms, limitations, future directions — and flags claims that need citations before you submit.
Section drafting
Intro, methods, results, discussion with domain structure
Peer review sim
Structured critique of methods and claim support
Knowledge Organization
Chapters, mindmaps, and document generation keep your research organized and growing.
Chapters
Project folders with memory. Every upload, analysis, and insight organized and queryable. Picks up where you left off.
→ Cross-chapter search across all projects · → Collaborative sharing with read/write access · → Templates for lit review, analysis, grant writing
Mindmaps
Living knowledge graphs that grow as your research progresses. Every insight, figure, and citation — connected and colored by type.
→ AI-suggested connections between nodes · → Color-coded by finding type · → Export as PDF, image, or interactive HTML
Document Generation
Select elements from your mindmap or chapter, choose a template, and Curiescious maps your research to a structured document.
→ Thesis sections, research reports, grant aims · → Auto-bibliography in multiple styles · → Export with track changes
Citation Management
Every claim is tracked from the moment it enters the system. Hover citations to see exactly where a claim comes from.
→ Zotero and Mendeley sync · → Missing citation detection · → Export as BibTeX, RIS, or formatted bibliography
Co-Scientist Skills
Co-Scientist Skills are reusable AI agents you build once and run forever. Encode your standard analyses, your lab’s protocols, your specific domain expertise — and share them with your team.
Building a Skill takes minutes. Describe what it should do, what inputs it accepts, and how outputs should be formatted. Curiescious handles the rest.
Lab Protocol Optimizer
Optimize any protocol for your lab’s equipment, reagent suppliers, and time constraints. Flags steps that historically cause issues.
Journal Club Prep
Upload a paper and get summary slides, key figures, methodological critique, discussion questions, and related literature.
Clinical Variant Interpreter
Input a VCF or variant list, apply ACMG/AMP guidelines, pull ClinVar annotations, and generate a structured report.
Grant Reviewer Simulator
Evaluate a draft Specific Aims page from the perspective of an NIH study section reviewer, with specific improvements.
Every mode, every integration, every feature — included. No credit card required.