What is Agentlas?
Agentlas is an AI automation tool that helps small teams build, review, and run multi-agent workflows for recurring business tasks without needing to code. Rather than producing a one-off chatbot demo, Agentlas packages agent work into reusable, reviewable bundles that run repeatedly from a desktop app using the AI accounts and local tools teams already own.
The platform separates two distinct environments: the web portal acts as a review office where agent packages and teams are assembled, security-checked, and published, while the desktop app is where downloaded packages execute on a recurring schedule. Before any agent runs, Agentlas performs a security audit that scans for secrets, unsafe code, and prompt-injection risks — a step that applies to external ZIPs and GitHub-sourced agents as well.
For teams working across multiple AI providers, Agentlas supports multi-agent configurations that coordinate Claude, Codex, and Gemini as a single operating unit. A built-in memory curator enforces schema, safety, evidence, scope, deduplication, and conflict checks before any memory is written, which the company's internal simulation shows reduces hallucination rates to 17.7% — compared to 98.6% in uncurated global memory setups.
Ready-to-use templates cover common recurring work patterns including weekly content planning, customer support triage, consulting research proposals, and code review automation. Each template is free and editable, giving teams a starting point that reflects actual workflow structures rather than generic prompt examples.
Agentlas targets solo operators, consultants, small agencies, and local service businesses that need recurring AI work done consistently, with human review checkpoints built in rather than bolted on afterward.
What is Agentlas used for?
Agentlas is used by small teams, solo operators, and consultants to automate recurring business tasks — content planning, customer support triage, research proposals, and code review — through reusable AI agent packages. It is aimed at business owners who need consistent, reviewed AI output week after week rather than one-time chatbot interactions.
How much does Agentlas cost?
Enterprise
Custom pricing — custom credit volume, SSO, audit logs, review gates, internal distribution
Pros and cons
Pros
- Multi-agent coordination across Claude, Codex, and Gemini in a single workflow
- Built-in security audit scans agent packages for secrets, unsafe code, and prompt-injection before publish
- Memory curator enforces schema and deduplication checks, cutting hallucination rates to 17.7% vs 98.6% uncurated
- Reusable portable ZIP export lets agents run in external developer toolchains
- Free tier unlocks every feature with 150 credits on signup — no card required
Cons
- Credit-based usage model means recurring heavy workflows can exhaust monthly allowances quickly
- Desktop app required for repeated production runs — web portal is review-only, not execution
- Enterprise pricing and SSO are custom-quoted with no published rate
- Limited to teams already holding their own AI provider accounts (OpenAI, Anthropic, Google)
Questions about Agentlas
What is Agentlas used for?
Agentlas is used to build and run AI agent teams that handle recurring business tasks like weekly content drafting, customer support triage, research proposals, and code review. Teams describe their workflow, and the platform proposes the agent roles, shared standards, and review checkpoints needed to run that work repeatedly. It targets small businesses, agencies, and consultants who need consistent AI output rather than one-off prompts.
Is Agentlas free?
Yes, Agentlas offers a free plan at $0/month that includes 150 credits on signup and unlocks every feature on the platform — no credit card required. Paid plans start at $39/month per creator (Pro, 15,000 credits) and $99/month per power user (Max, 40,000 credits). Credit top-ups are available separately, and Enterprise pricing is custom-quoted.
How does Agentlas work?
Agentlas works in two environments: the web portal is where you describe recurring work, review the proposed agent structure, and run a security audit on the package before publishing. The desktop app is where you download or import that package and execute it on a recurring schedule using your own AI provider accounts. Every memory write goes through schema, safety, deduplication, and conflict checks before being stored.
Agentlas vs Make (Integromat) — what is the difference?
Make is a general-purpose workflow automation tool built around connecting APIs and services with a visual flowchart editor. Agentlas is specifically designed for multi-agent AI workflows where multiple large language models (Claude, Codex, Gemini) coordinate as a team, with built-in security audits, memory curation, and review gates before execution. Agentlas is aimed at teams delegating recurring knowledge work to AI agents rather than connecting SaaS triggers and actions.
Does Agentlas support multiple AI models?
Yes. Agentlas supports multi-agent configurations that treat Claude, Codex, and Gemini as one coordinated team. Each agent in a workflow can be assigned to a different AI provider, and all agents operate under shared standards, tone rules, and review gates set during the package-build step in the web portal.
What are the best alternatives to Agentlas?
Make (Integromat), n8n, Zapier, Relevance AI
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