Twin: Plain English Builds Autonomous AI Business Agents
Twin lets you describe business automations in plain English—no code needed—and it creates, runs, and manages full AI agent systems for content repurposing, lead gen, and operations, handling APIs, UIs, and scheduling autonomously.
Plain English Instructions Trigger Full Agent Systems
Twin's orchestrator acts as a chat-based control hub where you describe desired outcomes in natural language, and it autonomously builds interconnected agents, handles API integrations like Supabase for data storage, and sets up back-end pipelines. For instance, instruct it to "create an autonomous content repurposing agent that takes YouTube videos or podcasts and turns them into clips," and Twin generates transcripts, extracts key ideas/quotes, stores them in a database, and feeds them to downstream agents for TikTok/Instagram video creation. This eliminates manual coding or tools like Zapier/n8n, which overwhelm with technical workflows—agents run end-to-end, tracking history and state across workspaces that organize projects like folders for clients or departments.
Workspaces enable parallel operations: run multiple agents asynchronously, monitor via a feed showing real-time tasks (e.g., "asking for UI setup"), and visualize runs. Twin interactively refines setups by asking clarifying questions, such as API keys or target specs, then auto-authenticates and configures. Outcomes include responsive UI dashboards for input (e.g., paste YouTube URL) and output previews, plus triggers like scheduled runs or email approvals for full autonomy.
Content Repurposing Pipeline Delivers Viral Clips
Twin builds a two-agent chain: a repurposer extracts transcripts/quotes from video URLs using built-in tools, outputs to Supabase, then a Reels/TikTok creator generates 3+ clips per input (e.g., from a NotebookLM video on Gemini integration). Paste a URL into the auto-generated UI dashboard, submit, and receive emailed clips with downloadable files—quality rivals manual edits, as seen in demos producing engaging snippets like "Google has officially integrated NotebookLM into Gemini."
Scale by adding recursive triggers: scrape new channel videos, email for approval, auto-post. This pipeline runs on demand or schedules, providing sources, key ideas, and quotes directly in the interface. Test via orchestrator commands like "test the content repurposer," confirming functionality before deployment—handles full recursion without intervention, turning one video into deployable social content in minutes.
B2B Lead Gen Agency Runs End-to-End Sales
Describe a full agency—"build an autonomous B2B lead generation agency that finds web design/marketing/automation prospects, collects contacts, sends personalized cold emails, follows up, tracks in spreadsheets, books calendar meetings on interest, and sends daily reports"—and Twin scaffolds it: uses Appify Lead Finder for 20 daily public leads (websites/contacts), crafts emails based on your specs (e.g., targets, pitch style), automates follow-ups/replies, and post-processes into dashboards showing metrics like "2 interested, 18 no reply."
Daily 9 a.m. trigger contacts 20 leads, emails reports with contacted lists/responses/booked calls, and books meetings directly. UI tracks pipeline health (total leads, replies), letting you tweak pitches iteratively. Before 24/7 deployment, verify components: test triggers/schedules via orchestrator ("test sales agent"), upload files/context for precision, ensure integrations work—yields a no-sales-team agency handling outreach-to-close without your input.
Maximize Results with Testing and Context
Provide detailed instructions plus files/data for accuracy; Twin outperforms vague prompts by incorporating context (e.g., email templates, lead criteria). Always pre-deploy test: invoke agents, check UIs/triggers/schedules. Clone featured agents (CRM sync, web scraper, email sender) as starters, preview functions before customizing. Free signup at twin.so yields mission control dashboard—handles ops/marketing/sales/finance autonomously, scaling from tasks to full businesses in <1 day.