CognetivyCognetivy is an open-source state layer for AI coding assistants that adds workflows, run tracking, and persistent collections - all local.
Academic Deep Research
Conduct systematic literature reviews and synthesis at speed.
Academic research demands rigorous sourcing, structured synthesis, and reproducible methodology. Cognetivy gives your agent a workflow that accumulates paper summaries, extracts findings by theme, and builds a structured literature collection - ready for citation and analysis.
What you'll achieve
Reproducible methodology
The same inclusion criteria and extraction schema are applied consistently across all papers.
Cumulative literature base
Each research session adds to the same collection - your review compounds without manual merging.
Citation-ready output
Every finding in your synthesis links back to the specific paper and section it came from.
How it works
A repeatable workflow you define once and run any time.
Define research scope
Store your research question, inclusion/exclusion criteria, and target time range as structured reference records.
Gather and screen literature
Your agent reads paper abstracts and full texts, applying inclusion criteria and storing qualified papers as structured records.
Extract and tag findings
Key findings, methods, sample sizes, and limitations are extracted and tagged by theme for each paper.
Synthesize review
A final step produces a structured literature review with theme summaries, evidence strength ratings, and gap identification.
Cognetivy features you'll use
Everything you need is already in Cognetivy.
Versioned, reusable step-by-step processes for your agent
Schema-backed data stores that persist and accumulate across runs
Structured outputs saved from any run - downloadable and linkable
Local browser UI to inspect runs, events, and artifacts
Related use cases
Ready to try?
Set up your first structured workflow in under a minute.