AI EmployeesBuilt into Genosyn

Hire teammates that never log off.

A Soul, a set of Skills, Routines on a schedule.

An AI Employee is not a chatbot persona. It is a persistent teammate attached to your company — with a Soul that says who it is, Skills that say what it knows, Routines that say when it works, and its own sandboxed working directory. Every execution is captured as a Run you can read line by line.

AI Employees · Live product storyRunning
Genosyn running a Operations Lead use case in AI Employees.
  • 0111 role templates or start blank
  • 02Claude, GPT, or a custom endpoint
  • 03API keys encrypted at rest
  • 04Every Run fully transcribed
AI Employees 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.

FO
Finance

Finance Operations

Reconcile daily transactions, surface exceptions, and keep the books ready to close.

41 of 42 charges reconciled without manual data entry
OP
Operations

Operations Lead

Turn recurring company work into dependable Routines with visible handoffs.

Repeatable operations without a spreadsheet of reminders
GM
Leadership

Founder & General Manager

Start the day with one trusted view of customers, revenue, cash, and work in flight.

A daily operating brief built from live company data
What ships

AI Employees, end to end.

Every capability is built into the same operating model, with company identity, access, activity, and AI Employees already connected.

A Soul, not a prompt

One markdown constitution per employee — identity, voice, decision rules, refusals — edited in-app with live preview. Change how they think by editing a document, like a job description.

Skills as playbooks

Named markdown playbooks — trigger, inputs, steps, definition of done — surfaced into the model's context on every run. Browse and reuse them across your team from the company-wide library.

Routines on cron

Pair a markdown brief with a 5-field cron expression and a plain-English preview. Per-routine timeouts, enable/disable toggles, an optional approval gate, and one-click Run now.

Bring any brain

Register Anthropic, OpenAI, or any OpenAI-compatible endpoint — Ollama, vLLM, llama.cpp, LM Studio. Keep several models per employee and pin a Routine to a cheap local one while chat stays on the frontier brain.

Runs you can audit

Every execution streams its full agent transcript live over WebSocket and keeps it afterwards. Retry failures in one click; usage and cost roll up per employee and per Routine.

Approvals and Grants

Access to Connections, repos, notes, Bases, and mailboxes is granted per employee. Sensitive actions — gated Routines, browser form submits, payments over a cap — wait for a human checkmark.

With AI Employees

How the pieces fit

Genosyn owns the model loop and tool registry. API-key and custom models run in-process; eligible OpenAI subscription models use the official Codex app-server on source-managed Linux. Each turn carries the Soul and relevant Skills, while explicit Grants decide what the employee can reach.

01

Real tools, sandboxed

Built-in coding tools (bash, file edits, grep) run inside the employee's own working directory; opt-in browser tools drive a headless Chromium with a host allow-list and human take-over for captchas.

02

Memory that persists

Employees save durable Memory that is auto-injected into future runs, keep an append-only Journal, and hand work to each other along the org chart with AI-to-AI Handoffs.

03

Long runs that survive

Context-window budgeting compacts old tool results with a visible marker instead of failing the run — an hourly digest on a 8k-window local model just keeps working.

Questions

Frequently asked.

What exactly is an AI Employee — is it just a chatbot persona?

No. It is a persistent persona attached to your company with a Soul (constitution), Skills (playbooks), Routines (cron-scheduled work), its own AI Models, a sandboxed working directory on disk, and explicit Grants to company resources. Every scheduled or manual execution is recorded as a Run with a full transcript.

Which models can an employee run on?

Anthropic (Claude), OpenAI (GPT), or Custom — any OpenAI-compatible endpoint such as Ollama, vLLM, llama.cpp, LM Studio, or a gateway. Eligible source-managed Linux deployments can also connect OpenAI through a ChatGPT subscription. An employee can hold several models with exactly one active, and individual Routines can pin a specific model.

Where do model credentials live?

API keys, custom-endpoint credentials, and OpenAI subscription credentials are encrypted with AES-256-GCM on the AIModel row in your database. The supported subscription path materializes managed session state only inside a locked temporary directory for a login or Run, then removes it.

Can an AI Employee take an action I haven't approved?

Not if you gate it. Flip approval-required on a Routine and the run blocks on a human checkmark; browser form submits can require approval per employee; Lightning payments over a per-connection cap queue for approval automatically. An Approvals inbox surfaces everything waiting.

Do I need to install a provider CLI or wrapper per model?

No generic provider CLI is required. API-key and custom models run through Genosyn's in-process loop. The eligible OpenAI subscription path is the narrow exception: Genosyn manages the official pinned Codex app-server and its temporary session boundary for you.

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.