Paradocs is the local-first AI workspace for research teams.
Paradocs unifies documents, datasets, notebooks, citations and code in one secure workspace. AI runs locally by default, grounded in your team’s knowledge graph.
manuscript.docx
Results
The intervention improved sample stability.
SUGGESTED REVISION
After predefined exclusions, results suggest improved stability and warrant further validation.
Review revision ->Mapping Knowledge
Turn scattered files, notes, and data into a living semantic map your AI can reason over.
Surgically Precise Retrieval
Grounds AI reasoning in your structured knowledge base. Trace every answer back to the exact source, relationship, and context it came from.
Dense Context Compression
Preserve meaning across millions of data points without flooding the context window.
Uncompromising
Data Sovereignty.
Use local-by-default AI models where your data already lives. Nothing sensitive gets sent to public AI tools.
Self-Hosted Enterprise
Deploy the entire Paradocs stack on your internal servers or air-gapped environment. Total isolation.
Bring Your Own Key (BYOK)
Connect your own API keys. Route all traffic through your own endpoints.
Safe AI & Reasoning
Integrations with verified partners providing strict, auditable non-logging guarantees. No model training.
Public AI providers
ChatGPT, Claude, Gemini, public cloud APIs
Why Paradocs
Built for research teams that cannot afford to lose context.
Research work is rarely contained in one clean document. A single project can span PDFs, spreadsheets, Jupyter notebooks, scripts, citations, drafts, figures, meeting notes, and shared folders. Paradocs turns those materials into a connected workspace so teams can move from reading to analysis to writing without breaking the chain of evidence.
The product is designed for labs, R&D groups, computational scientists, medical researchers, and data-intensive teams that need AI help without uploading sensitive or unpublished work to public tools by default. Documents, data, code, citations, and notes can remain close to the user or institution while the knowledge graph preserves how claims, files, and results relate to each other.
That connected memory makes Paradocs useful for literature reviews, reproducible analysis, manuscript drafting, institutional knowledge, and long-running projects where new collaborators need to understand what was done, what supports each conclusion, and what changed over time.
Field Notes
Frequently Asked Questions
What is Paradocs?+
Paradocs is a local-first AI workspace for research and R&D teams working across documents, datasets, code, notebooks, notes, citations, and manuscripts.
Instead of spreading project context across PDFs, folders, Jupyter notebooks, Word documents, Overleaf, Zotero, Slack, and shared drives, Paradocs brings the work into one connected workspace with AI grounded in your own materials.
The goal is not just to help you find files. It is to help you understand how papers, data, analysis, figures, claims, and writing connect.
Who is Paradocs built for?+
Paradocs is built for researchers and R&D teams working with complex, fragmented, or sensitive knowledge.
This includes academic researchers, PhD students, postdocs, PIs, bioinformaticians, computational scientists, medical researchers, and biotech or pharma R&D teams.
We are starting with researchers because they have one of the hardest versions of the problem: literature, data, code, writing, collaboration, and sensitive information in the same workflow.
Is Paradocs just another AI chatbot?+
No.
A chatbot starts with a blank conversation. Paradocs starts with your research workspace.
Paradocs connects your files, papers, datasets, notebooks, citations, notes, figures, and drafts into a project memory that AI can reason over. That means the AI is grounded in your own materials, not just generic model knowledge or isolated document uploads.
What does local-first AI mean?+
Local-first means your project context stays close to you by default.
Paradocs is designed so documents, datasets, embeddings, notebooks, and workspace memory can remain on your machine or inside controlled infrastructure. AI can run locally where possible, and heavier reasoning can be routed to approved infrastructure when needed.
The principle is simple: sensitive research context should not have to leave your environment just to become useful.
Does my data leave my computer?+
By default, Paradocs is built so your data does not need to be uploaded to public AI tools.
Some features may optionally use secure external compute, approved servers, bring-your-own-key models, or institutional infrastructure. But external reasoning should be explicit and controlled, not automatic or hidden.
For sensitive projects, the safest default is that data stays local or inside approved infrastructure.
Which files does Paradocs support?+
Paradocs is designed for the files researchers already use.
This includes PDFs, Markdown, Word documents, LaTeX, CSV and Excel files, code files, Jupyter notebooks, citations, notes, and project folders.
The goal is not to force teams into a new proprietary format. The goal is to connect the materials they already work with.
Does Paradocs replace Zotero, Overleaf, Notion, Jupyter, or Google Drive?+
Not necessarily.
Paradocs is not trying to replace every specialist tool feature-by-feature on day one. The main goal is to become the connected workspace layer between your research materials.
You should be able to work across PDFs, datasets, notes, code, citations, and manuscripts without losing the relationships between them. Over time, some workflows may move fully into Paradocs. Others may remain connected from external tools and storage.
Is Paradocs available now?+
Paradocs is currently in closed beta with early researcher testing.
The beta is for researchers and R&D teams who work across papers, datasets, code, notebooks, citations, figures, notes, and manuscripts, especially when the workflow is fragmented, sensitive, or difficult to reconstruct over time.
Early beta users should expect early software and give honest feedback on what is useful, confusing, missing, or unreliable.
Need details on privacy, file support, deployment, or beta access?
Full FAQClosed beta
Unify your research.
Keep your data local.
We are opening Paradocs to researchers and teams who need AI across real work without surrendering control of their data.