EN
Engineering
Software Engineer
Investigate failures, prepare a tested patch, and hand the diff to a human reviewer.
A review-ready fix, with the evidence attached
ResourcesBuilt into Genosyn
Ingest once. Every employee studies it.
URLs, PDFs, ebooks, and transcripts your AI can search and cite.
Resources is the knowledge-ingestion surface: external material your team didn't write — articles, ebooks, PDFs, transcripts — ingested once, extracted to searchable plain text, and served to AI employees on demand. It replaces the copy-paste-into-the-prompt ritual and the shared-drive folder no AI can actually read.
Resources · Live product storyRunning
- 01URL, PDF, EPUB, text, and markdown
- 02Full-text search over extracted bodies
- 03read < edit < delete Grant levels
- 04Attach to outgoing Gmail by slug
Resources in practice
Built around outcomes, not demos.
Start with a real role and a real handoff. Genosyn gives the AI Employee the context, access, and review path to finish the work inside your company.
CS
Support
Customer Support Specialist
Triage the inbox, gather customer context, and draft answers grounded in your docs.
A clean support queue and faster, consistent replies
OP
Operations
Operations Lead
Turn recurring company work into dependable Routines with visible handoffs.
Repeatable operations without a spreadsheet of reminders
What ships
Resources, end to end.
Every capability is built into the same operating model, with company identity, access, activity, and AI Employees already connected.
Paste a URL, get clean text
The server fetches the page and extracts readable text — scripts, nav, and footers stripped — with no browser or scraping stack required. Failed fetches keep the row with the error so a human can fix it.
Real document formats
PDFs extract via pdf-parse, EPUBs unzip chapter by chapter, and TXT, Markdown, and HTML upload directly — 25 MB per file, with up to 1 MiB of extracted text each.
One search across it all
Full-text search over titles, summaries, tags, and extracted bodies — search-as-you-type for humans, the same query surface as a tool for AI employees.
Readable in place
Type-aware detail pages: editable markdown for text, the native viewer for PDFs, an in-app EPUB reader with table of contents and progress, and an open-original card for URLs.
Exports that look right
Export any Resource as PDF, HTML, Markdown, or plain text. PDFs render through Chromium, so headings, tables, and code blocks come out styled — ready for a chat reply or a Base record.
Attach to real email
Gmail send and draft tools accept attachments by Resource slug — the server checks the Grant and resolves the bytes, so no base64 ever crosses the model's context window.
With AI Employees
Study before answering
AI employees reach the library through built-in tools gated by three Grant levels — read, edit, delete. The tool descriptions coach them to check whether the team already ingested a primer before improvising.
01
They curate it too
An employee can file a URL or a pasted transcript itself with create_resource — it gets full control of rows it authored, while teammates start at read.
02
Levels, not switches
read covers list, search, and get; edit adds re-titling, tagging, and body updates; delete allows permanent removal. Humans promote employees between levels from the share modal.
03
New material is instantly usable
Every new Resource is automatically granted read to all AI employees, so the primer you drop in at 9:00 informs the Routine that runs at 9:05.
Questions
Frequently asked.
How is a Resource different from a Note or a Memory?
A Resource is content the team did not write — an article, ebook, or transcript ingested once and queried on demand. A Note is a page the team authors together, and a Memory is a durable fact auto-injected into an AI employee's prompt.
What formats can I ingest?
Web pages by URL (fetched and extracted to plain text), PDF, EPUB, TXT, Markdown, and HTML uploads up to 25 MB per file, and pasted raw text. Video files are accepted but transcripts aren't extracted yet — upload the transcript as text in the meantime.
Can AI employees add their own Resources?
Yes. The create_resource tool lets an employee index a URL or file a pasted transcript or research summary. The authoring employee automatically gets full control of its own row; teammates start at read-only. File uploads stay human-only.
Can an AI employee email a Resource to someone?
Yes. The Gmail send and draft tools accept attachments by Resource slug and format — the server checks the employee's Grant, resolves the bytes, and attaches the original file or the text rendered as PDF, HTML, Markdown, or plain text.
Does it use embeddings or RAG?
v1 retrieval is deliberately simple: case-insensitive substring matching over titles, summaries, tags, and the full extracted text. Embeddings and vector search are planned once real query patterns are known.
Explore more products
View allBases
Multi-table workspaces with typed fields, saved views, comments, and attachments — and 21 built-in tools for granted AI employees.
Notes
Notion-style markdown pages in nested notebooks — read, written, and searched by humans and AI employees under cascading Grants.
AI Employees
Persistent AI teammates with a written constitution, markdown playbooks, and cron-scheduled work — every execution captured as a readable Run.
Workspace
Slack-style channels and DMs where AI employees are real members — @mention one and it joins, replies, and reports back from its Routines.
Put your first AI Employee to work.
Install Genosyn, choose an AI Model, define the role, and schedule the first Routine. The rest of the company can grow from there.