Run it repeatedly in Desktop
Download or import the agent package you built on the web, then run weekly work from the app with your own AI account.
See DesktopReview first, then run
Web is for review. Desktop is for recurring work.
The owner path leads to Desktop. Developer export stays available without taking over the main funnel.
Security-check before trust
Scan external ZIPs or GitHub agents for secrets, unsafe code, and prompt-injection risks before publish or manual import.
Open AuditPortable ZIP export
Developer toolchains can still use the package files. This is an advanced route, not the main buyer path.
Developer guideSTART FROM A REAL WORKFLOW
Not a chatbot demo. A recurring work package you can review and run.
A single draft is not the hard part anymore. Agentlas is for the next layer: the same work coming back every week, your standards staying intact, and only the decisions that need a human rising to the top.
Chatbot
Paste one product and it can draft a page, caption, or reply.
- One product page
- Caption ideas
- Support reply draft
Typical builder
You can make a bot, but each launch still needs setup, channel splitting, and cleanup.
- Reset every launch
- No shared standards
- No pre-upload review
Agentlas
A coordinator, product copy, ad, review, and support agents prepare one brand-safe launch kit.
- Page + social + ads
- Tone and banned words
- Upload checklist
Agentlas
Research RepoAdvanced under the hood. Business-first on the surface.
The visitor does not design the org chart. They describe recurring work, and Agentlas proposes the roles, shared standards, and review points that make the package usable.
The web portal is the review office. It packages the agent or team and checks risky settings before publishing. Desktop is the local office where downloaded or imported packages can run again with your accounts and tools.
Developer ZIPs, CLI paths, and framework comparisons still exist. They are support routes now, not the main promise to an owner comparing AI transformation quotes.
03 · Hallucination reduction vs. global memory
82% less hallucination
Leave global memory uncurated and after a year, hallucination hits 98.6% per retrieval. Run the same simulation with the Agentlas memory curator on its aggressive setting and it drops to 17.7% — 5.56× lower.
04 · Agentlas memory curation structure
Every memory is checked before it's written
A worker's memory doesn't get written straight away. It has to clear schema, safety, evidence, scope, dedup, and conflict checks first — then it's routed into agent repo, agent team, project, or session memory.
EXPLORE TEMPLATES
Grab an example. Make it yours.
HOW IT WORKS
You don't have to design an org. Just follow along.
Hire one at a time and a company takes shape. The hard setup is the Agent's job, not yours.
1Say it
“I need an Agent to run my Instagram.” One line is enough.
2Answer a few
Nothing technical. Just pick from the options.
3Your first Agent
One worker is ready. Put it to work right away.
4Add one more
Add Agents as you need them. Soon it's a team.
5It becomes a Team
Agents doing similar work group into a department.
6A multi-agent operating team
A coordinator ties the roles together, and the recurring workflow runs.
That Multi Agent setup you saw online and wondered how they built — follow along and it's yours too.
THE COST OF AI TRANSFORMATION
What does an ‘AI transformation’ actually cost?
Everywhere, someone offers to “transform you with AI” — consulting plus an outsourced agent build, usually thousands per project. Agentlas is one monthly subscription.
AX consulting · agent build-out$8,000–40,000 (one-off)
One full-time hire$2,300+/mo
AX agency retainer$1,500–4,000/mo
Agentlas$39–99/mo
Same ‘AI transformation’ — just with a few zeros removed. (Quotes vary by vendor.)
What's expensive is the consulting labor, not the AI. Agentlas takes that out and puts the build in your own hands. It isn't cheap — it's just the real price.
PRICING
Build first,
upgrade later.
upgrade later.
Every plan has every feature. The only thing that changes is how many credits land in your account each month.
AT A GLANCEFree → Pro → Max
Monthly prices. Full comparison lives on the pricing page.
FreeFree
$0no card
Every feature, free
No card needed.
- 150 credits on signup
- Every AI feature
- Unlimited public profiles
RecommendedPro
$39per month
Build and ship weekly
For frequent builders.
- 15,000 monthly credits
- Every AI feature
- Unlimited public profiles
Highest volumeMax
$99per month
Build at company scale
When you're assembling teams all day.
- 40,000 monthly credits
- Every AI feature
- Priority run queue
ABOUT US
An AI company of your own.
Not just for the experts.
Not just for the experts.
We built Agentlas so anyone can have an AI company that takes care of their own work.
Start with one sentence. It asks only what's missing, then hands you files you can actually use.
Narrow the AI gap
Make agents approachable for non-experts.
Build through questions
No perfect prompt required. Answer only what is missing.
Take the files with you
Save, download, and share when ready.
START SMALLOne sentence is enough.
Start my companyFAQ
Questions people ask before choosing Agentlas.
A short answer-engine-friendly guide to scope, security, and runtime questions for owners comparing AI transformation quotes.
BasicsWhat is Agentlas?
Agentlas is an AI agent builder that turns one plain work request into a whole agent team — not a single bot. It asks the missing questions, splits the work across agents, surfaces only what needs a human, and then helps you save, download, and share the finished package.
Multi-agentIs Agentlas a multi-agent framework?
Agentlas is not mainly a code-first orchestration framework. It is a builder and packaging layer for deciding what agents you need, what each one should do, what files should ship, and what should be reviewed before sharing.
OperationsHow is Agentlas different from code-first agent frameworks?
Code-first frameworks are best when a developer wants to design graphs, tasks, deployment, and runtime behavior directly. Agentlas starts earlier: describe the business outcome, answer a few questions, then get a portable agent package with roles, instructions, safety labels, and shareable profile copy.
SetupDoes Agentlas replace my existing business tools?
No. Agentlas does not claim to replace your accounting app, CRM, inbox, spreadsheet, or project board. It helps you define and review the agent team that will prepare work for those systems, then hands you a package you can run in the environment you control.
ChannelsIs Agentlas a messaging gateway for agents?
No. Agentlas focuses on creating, reviewing, packaging, and sharing the agents themselves rather than becoming the messaging gateway. Channel integrations should come later, once the role, safety review, and run environment are clear.
RuntimeDoes Agentlas run work on a hosted server 24/7?
Not today. The web app helps design and review the agent or team. Recurring work belongs in Agentlas Desktop or another local environment you choose, with your own AI accounts and local trust decisions.
BeginnerCan non-coders use Agentlas?
Yes. Agentlas begins with plain language and avoids asking for integration jargon, tokens, or API details before the user understands the job. When technical setup is needed, Agentlas can explain it and let the user defer what they do not know yet.
SecurityIs it safe to publish agents made with Agentlas?
Agentlas reviews sensitive details, risky settings, and public-sharing issues before an agent profile goes live. Public profiles are meant to show the agent structure, purpose, safety labels, and install guidance, not private secrets.
TeamWhat does Agentlas mean by an agent team?
An agent team is a coordinated workflow: one routing role plus several specialist agents. For an e-commerce workflow, that might mean a product copywriter, pricing scout, review analyst, and customer support writer working under one plan.
RuntimeCan Agentlas agents work with the AI tools I already use?
Agentlas is designed to produce portable agent instructions, skills, setup notes, and safety context that users can take into the AI runtime or local tool they already use.