A platform called Agentica launched with a simple premise: describe your company in one sentence, and a team of six AI agents will research the market, build a full-stack application, generate a landing page, and deploy it live. The entire workflow runs from a single dashboard with no credit card required to get started.
The tool sits at the intersection of two trends that have been accelerating throughout 2026. First, AI coding assistants have gotten good enough to generate entire applications from natural language descriptions. Second, autonomous agent frameworks are moving beyond chatbots and into workflows that coordinate multiple specialized systems. Agentica combines both by giving each agent a specific role and letting them collaborate under a hierarchical structure.
How the Agent Team Works
The system runs six agents, each assigned to a business function: CEO, Marketing, Research, Sales, Finance, and Engineering. The CEO agent acts as a coordinator, decomposing the user's initial description into a prioritized task queue distributed across the other five agents. Research analyzes the market. Marketing writes campaigns. Finance builds projections. Engineering ships code.
Users watch this process unfold in real time. The dashboard streams each agent's reasoning in a terminal-style log, showing what is being built and why. Tasks move through states: Working, Needs Input, and Queued. The right side of the dashboard always shows the single next most useful action, which agent will handle it, and an estimated time to completion.
This is not a chatbot interface where you type messages back and forth. It is a task management system where agents propose work, execute it, and present results. Users can approve, dismiss, or modify proposed tasks. Dismissing a task with an explanation trains the agents to stop suggesting similar work.
From Brief to Live Product
The input is a single text field. You describe what the company does, who it is for, and how it charges. Agentica generates a company name from the description if you do not provide one. From that brief, the platform creates an isolated workspace and database, kicks off the landing page build, and spins up all six specialist agents.
The engineering agent generates a complete React frontend using Vite and a Python FastAPI backend. The application includes authentication, a dashboard that fetches real data from the backend, and a database schema isolated to the company. Dashboards do not display fake numbers. The generated app is embedded in the dashboard for testing and also deployed to a public address at the company's subdomain on ai-biz.dev.
The marketing agent creates a conversion-optimized landing page with pricing, FAQ, and calls to action. The entire process from one sentence to a live, deployed product takes minutes according to the platform's documentation.
Edits work through natural language. You describe a change in plain English, like "change the button color to blue" or "add a phone field to the signup form," and the engineering agent applies it surgically. Only the lines matching the instruction are touched. A build history feature keeps previous versions and lets you restore any of them with one click.
Autonomous Execution
The autopilot feature is where Agentica moves beyond a one-shot generation tool. Once enabled, agents propose and run new tasks on a recurring schedule without manual intervention. A brand-new company starts with just a landing page, and autopilot will plan and build toward a full product over time.
Every autonomous task appears in the activity history with full results. You can review what the agents did, why they did it, and whether the output is acceptable. Autopilot can be switched off at any time for manual control.
The communication reports feature lets you set how often you receive email summaries: daily, weekly, monthly, quarterly, or annual. Daily reports are always recorded regardless of your chosen frequency. Higher frequencies roll up the daily data, summing signups, traffic, revenue, and shipped work while preserving the granular history.
External Actions and Approvals
When an agent needs to interact with an external service like Gmail, LinkedIn, Slack, or GitHub, the platform tells you which app it needs and why. You authenticate directly on the service's own website. Agentica never sees or stores your password.
The critical detail is the approval layer. Connecting an external app only lets agents prepare actions. Anything that would post, send, or change something in your real account is queued and runs only after you approve that specific action. Approving one LinkedIn post does not approve the next one. Each action requires individual confirmation.
An integrations panel lists every connection, when it was established, and a revoke button for each. Tokens are encrypted and used only for actions you have approved. The platform also supports custom Model Context Protocol servers with optional Bearer authentication, letting you assign specific tools to specific departments.
Deployment and Data Control
Code can be pushed directly to a connected GitHub repository from the dashboard. Deployment to Railway or Vercel is available with a single click. Custom domains are supported through DNS configuration with step-by-step guidance.
Data handling is transparent. The platform stores data in the EU and documents GDPR and CCAMPA compliance including data location, sub-processors, and retention policies. You can export everything including tasks, results, notes, leads, brand kit, code, and the app's database. Company deletion removes database rows immediately, site artifacts within minutes, and backup copies within 90 days.
Agentica is available on a free plan with no credit card required. The free tier includes a monthly credit allowance covering tasks, images, and emails. Usage is tracked per action and per company in a full usage log accessible from the dashboard.
The platform is clearly aimed at non-technical founders who want to validate an idea quickly, or at small teams that need internal tools built fast without hiring a developer. The six-agent structure is a marketing choice as much as a technical one, but the underlying generation pipeline produces real code on real infrastructure. Whether the agents consistently produce production-quality work at scale remains to be seen, but the ambition is clear: make the distance between a business idea and a running product as short as a single paragraph.