Rebyte

Rebyte is a multi-agent platform built by ReByte, Inc. that lets teams deploy AI agents as named, scoped digital employees — each with its own cloud computer, role, and access controls. Rather than a single chatbot, Rebyte lets you assemble a team of specialized agents (researcher, engineer, analyst, on-call SRE) that run independently and in parallel, coordinated through natural conversation in Slack or via API.

What It Is

Rebyte positions itself in the "agentic workforce" category: instead of a chat interface or autocomplete tool, it provisions persistent cloud VMs for each agent, giving them a real file system, shell, browser, and network. Agents are set up the way you'd onboard a human hire — with an identity (username/password or private key), a role defined in plain language, a computer, tools, and access permissions granted exactly as they would be for a teammate.

How the Agent Model Works

Each agent on Rebyte is a first-class security principal that can be authenticated, audited, and revoked. The core building blocks are:

• Agent Computer: A persistent long-lived VM that retains state across tasks — file system, installed packages, and context all carry over.
• Agent Harness: The runtime that connects the model to the computer and tools.
• Skills: Capabilities like web search, coding agents (Claude Code, Codex), image/video generation, and connector integrations.
• Agent Context: A data layer that connects agents to structured sources — Snowflake, PostgreSQL, MySQL, S3, GCS, Azure Blob, Databricks — with support for CSV, JSON/JSONL, and Parquet formats.
• Agent Shield: Security controls including access control and prompt-level guardrails.

Integrations and Connectors

Rebyte connects agents to the tools teams already use. The connector library includes Slack, Gmail, Google Drive, Google Sheets, Google Calendar, Notion, Jira, Confluence, Salesforce, HubSpot, Zendesk, Microsoft Teams, Outlook, Excel, SharePoint, Snowflake, Monday.com, Gong, Salesloft, Productboard, Ashby, Freshservice, Statuspage, Vanta, Slab, Luma, Fathom, and UKG — with hundreds more listed as available.

Use Cases Across the Org

Rebyte targets cross-functional deployment rather than a single team. The platform highlights use cases including:

• Engineering: Picking up Linear/Jira tickets, writing fixes, opening PRs, getting builds green
• Customer support: Working the support inbox — answering, troubleshooting, refunding, escalating
• On-call/SRE: Watching logs, triaging alerts, opening incidents, paging humans when needed
• Sales: Enriching inbound leads, drafting outbound, prepping reps before calls
• Finance: Reconciling transactions, chasing invoices, flagging anomalies
• Recruiting: Screening applicants, scheduling interviews, drafting follow-ups
• Content/marketing: Drafting posts, SEO pages, decks, and newsletters

Transparency and Billing Model

Rebyte's pricing page emphasizes per-task receipts over rate cards. Every completed task shows an itemized bill: compute hours (billed at $0.10/hr while active, $0 when idle), individual model calls with token counts, proprietary skill calls (image/video generation, etc.), and a total in credits and dollars. The platform supports three model spend paths: bring your own API key (Anthropic, OpenAI, Google — Rebyte takes no margin), bring your own subscription (Claude Max or Gemini), or use Rebyte-hosted models billed in credits at at-cost rates.

API and Developer Access

Rebyte exposes a REST API for programmatic agent management. Developers can create Agent Computers, list and inspect them, run tasks against persistent workspaces, and wire up inbound and outbound webhooks. The API uses API key authentication and returns structured JSON. Three lines of curl are sufficient to spin up an agent, per the docs.