Help & Support

Most users deploy their first agent within 10 minutes. Connect your tools, describe what you want in plain English, and you're ready to go. No coding required.

Auteryn is powered by Google's Gemini 3 Flash with a 1 million token context window, plus Gemini Computer Use for vision-based UI automation. This enables agents to understand complex documents, maintain long conversations, and interact with any screen.

ChatGPT and Claude are chat interfaces — they answer questions but can't take action. Auteryn agents connect to your real tools (GitHub, Jira, WhatsApp), execute multi-step workflows, and carry tasks that span days — runs are checkpointed after every step and sessions persist between them. They plan before acting and get your approval for sensitive operations.

Yes — continuing work is built in. Agents run on schedules and event triggers (a webhook, a customer message, a build finishing), book their own follow-ups (serial chains, three pending at most), and work toward goals where a separate check — not the agent grading itself — decides when it's done. Background jobs wake the agent when they complete, and interrupted runs resume with plan, notes, and tool history intact. Every pass is a normal run you can watch live and step into.

Loop engineering is the industry's June-2026 name for designing the system around an agent — triggers, verification, budgets, and stop rules — instead of prompting it by hand. Our take: loops are only trustworthy when they're bounded and visible. Auteryn loops carry run budgets, checkpoint near the limit, stream every step to a live timeline, and keep a human seat — you can step into any pass.

Yes — structurally. After qualifying runs, a reflection pass stores what worked and what didn't, and the next similar task starts with those lessons. Agents also keep self-evolving long-term memory: they write and consolidate their own notes, searchable in natural language — and you can read and edit every entry. When an agent notices a workflow it keeps repeating, it can draft that workflow as a new Skill; every self-drafted Skill waits in a proposed rail for your approval before it can run anywhere.

Yes. An agent can spawn a swarm — up to four focused agents working in parallel, each with its own task and its own isolated machine, streamed live in the workspace and merged when they finish. Within a single run, sub-agents handle research, code review, and computer-use delegations alongside the main agent.

Yes. Describe what you want and Studio researches your own catalog and drafts the agent or Skill, streaming its progress as it works. You can also hand it a chat thread where the workflow already happened, a screen recording of the task, or a YouTube link. Drafts always land in the editor for your review — never straight to production.

Budgets are structural, not advisory. Every run carries hard time and model-call limits; near the budget the run checkpoints its state cleanly instead of overrunning. Credits are transparent — 1 credit = $0.001, forever — every action is metered and visible, and free-plan runs are additionally capped at 150 credits per run.

Agents only access what you explicitly connect. We use temporary, scoped tokens that are revoked after each task. All data is encrypted at rest and in transit with AES-256.

You're always in control. Enable Human-in-the-Loop mode to review and approve sensitive actions before they execute. Plus, full audit logs let you see exactly what happened.

No. Your data is never used to train AI models. All interactions are private to your organization and encrypted with AES-256 encryption.

Auteryn uses an adaptive multi-agent framework. Based on task complexity, specialized sub-agents dynamically collaborate — handling planning, execution, verification, and reporting as needed. Simple queries get fast responses; complex tasks trigger multiple agents working in coordination.

Computer Use is our vision-based UI automation capability powered by Gemini. Agents can see, click, type, and navigate any screen just like a human — enabling automation of any web application without APIs.

A single run lasts up to two hours, checkpointed after every step. Tasks span days because the loop continues — schedules, events, follow-ups the agent books, and goal passes — with sessions, files, and context persisting between runs. Interrupted runs resume with full state.

Auteryn uses a unified credit system — one credit balance covers everything: AI conversations, tool calls, media generation, voice, and sandbox compute beyond your included hours. 1,000 credits = $1, always. Start free with 1,000 credits/month. Paid tiers add more of everything — Pro $29 with 15,000 credits and 25 sandbox hours, Business $99 with 60,000 pooled credits and 100 hours — plus top-up credit packs that never expire.

The Free tier includes 1,000 credits, 1 hour of sandbox compute, and 100 MB of storage per month — enough to build and test your first agents. Upgrade any time when you need more capacity.

Credits cover everything: conversations (about 20 for a quick chat, up to a few hundred for a deep multi-step run), image generation (60), video (200/second, Pro & up), voice (10–30/min), speech (150 per 1,000 characters), and sandbox compute beyond your included hours (1.5/min). Knowledge queries and flow triggers are free. Your monthly allocation covers most use cases, and top-up packs never expire.

Yes — two ways. On any paid plan you can bind an agent to a Linux machine you own: one command installs a signed runner, the agent's shell and files run on your hardware, and those runs use none of your sandbox-compute minutes. Separately, Enterprise plans add dedicated AWS account deployment with customer audit role access, VPC peering, and BYOK (bring your own keys). Contact us for custom infrastructure requirements.