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.

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.