One workspace for the whole research lifecycle
SapienAI is the workspace to unite agentic AI research, real-time collaborative LaTeX, Typst & Markdown writing, compute and data analysis with Python, R & Jupyter notebooks, and a knowledge base of everything you read — all grounded in your sources.
The idea
One workspace for the paper, the sources, and the knowledge that grows in between.
Before Sapien, a single paper is scattered across a writing app, a shared doc, a reference manager, a search tool, a notebook, a chatbot, and a folder of PDFs — none of which share context. SapienAI replaces that stack with one project where writing, sources, code, colleagues, and AI work from the same place.
For researchers, labs, universities, and research organizations that need faster work without giving up control over hosting, models, or data.
What only SapienAI does
Each of these exists somewhere. Researchers stitch them together across half a dozen apps that never share a source, a citation, or a thought. SapienAI is designed to bring those capabilities into one project, sharing the same context and AI.
Point an agent at your library and it searches, reads, synthesises, drafts, and writes the analysis code — every step grounded in real sources, fully reviewable, and yours to approve.
Co-author a thesis in LaTeX, a preprint in Typst, and notes in Markdown without switching tools or breaking the cursor.
Execute your analysis code right beside your draft. Figures, tables, and outputs save back to the project and stay citable.
SapienAI combines a living knowledge graph with an evidence-native research wiki. Explore connections across sources, claims, datasets, notes, and outputs, then build linked, versioned wiki pages that preserve citations, history, and disagreement as your research evolves.
You hold the dial
SapienAI is a complete research workspace before a single token is generated. Turn AI up when it earns its place, down when human thought is required, or off entirely.
The complete system
Around those capabilities sits the connective tissue of a real workspace — so a literature review or a paper moves from first source to final draft without ever leaving the project.
Keep project files, collections, graph views, agent sessions, collaborators, shared documents, and layouts together so a literature review or paper stays organized over time.
Write collaboratively in Markdown, Typst, LaTeX, Python, R Markdown, and Jupyter, with shared context for the whole research space.
Find relevant passages across files, collections, spaces, your Zotero library, and prior sessions.
Explore connections between entities, claims, topics, files, and source segments in graph and card views.
Turn each research collection into an editable, linked, versioned Wiki that connect synthesis to exact source evidence, preserve history and disagreement, and support human-reviewed agent contributions.
Use agents to draft, revise, critique, summarize, and extend writing with approvals, configurable skills, definable MCP connections, file mentions, forks, and exportable records.
Read PDFs, Word documents, spreadsheets, text files, and extracted segments. Run Python, R Markdown, and notebooks in the browser with support for all the most common research and data analysis packages.
Three working modes
Markdown, Typst, LaTeX, Python, R Markdown, and Jupyter live in one surface — so drafting, discovery, and executable analysis share the same sources, citations, and AI instead of living in separate apps.
Flexible formats
Swap between prose, typeset manuscripts, scripts, and data notebooks without separating the work from the research space.
Draft in different formats while files, notes, citations, and project context remain close to the manuscript.
Search across papers, notes, references, sessions, and extracted source segments without leaving the project.
Use writing agents, run code, and route selected tasks to approved model providers or local endpoints.
Agentic work
Hand the agent a bounded task and the right context, and it does the work: summarise sources, pressure-test claims, revise prose, prepare analysis code, and return artifacts you can review, approve, and trace back to their evidence.
Choose the files, notes, source segments, draft section, or notebook cells the agent can use.
Ask for a grounded synthesis of papers, interviews, policies, or source collections.
Generate structured revisions, flag weak claims, or propose a tighter argument.
Create Python, R Markdown, or notebook cells for analysis tasks and checks.
Keep humans accountable with saved records, exports, approvals, and follow-up tasks.
Deployment flexibility
Use public cloud, private cloud, on-premises infrastructure, and bare metal, with model and storage choices designed to match your requirements or institutional policies.
Configure model providers, storage, and deployment patterns around your institution's policies instead of forcing every researcher into the same hosted stack.
Deployment
Three paths: self-hosted, a hosted workspace, and institution-supported deployments.
Gives individual researchers control over infrastructure, data, models, and connected tools on their devices.
The quickest way to get started with Sapien.
Deploy SapienAI with AcademicID support for organizations that need governance, rollout planning, and account controls.
Compare options
| Capability | Self-hosted | academicid.io | Enterprise |
|---|---|---|---|
| Status | Coming soonFor individuals that want to operate Sapien themselves. | Coming soonHosted by AcademicID for researchers and teams. | Coming soonSupported deployments for institutions and research organizations. |
| Best for | Individuals that want full control. | Researchers and teams that want SapienAI without managing infrastructure. | Universities, libraries, labs, and organizations with strict governance requirements. |
| Operations | You deploy, update, monitor, and back up the system. | AcademicID operates the hosted service. | AcademicID supports deployment planning, onboarding, operations, and rollout. |
| Data and storage | Your infrastructure, databases, vector index, graph database, and storage policies. | AcademicID-managed hosted storage and service configuration. | Institution-aligned storage, data locality, retention, and security configuration. |
| Models and AI providers | Bring approved cloud, direct, or local model endpoints, and configure MCP servers for agent tool access. | Use hosted defaults and supported provider options. | Configure provider access around institutional model governance and procurement. |
| Admin and account control | Local control for your own deployment. | Standard account controls for individual researchers. | Advanced admin and account controls over usage.Manage users, workspaces, permissions, usage visibility, and organizational policies. |
| Support level | Community documentation and release notes. | Hosted service support. | Deployment, onboarding, configuration, and operational support for organizations. |
| How to start | Join the waitlist for updates. | Join the waitlist for academicid.io. | Contact AcademicID to discuss institutional requirements. |
For academic organizations
Research AI needs sources, permissions, and a record of the work.
SapienAI is for settings where data locality, model governance, source transparency, reproducible analysis, and auditability matter as much as convenience.
Deploy SapienAI on the infrastructure your organization already trusts: public cloud, private cloud, on-premises clusters, or bare metal. Keep research workflows aligned with your security, storage, and governance requirements. Strict network controls, no data leaks, and no hidden model access.
Join the waitlist
Get updates on hosted access, self-hosted releases, and enterprise-supported deployments for universities, labs, libraries, and research organizations.
Waitlist
Join the list for hosted access, self-hosted releases, and enterprise pilots.
