Build no-code AI employees for inbox, meetings and CRM updates.
AIAGENTSLocal services, retail, professional services, 1-50 employee businesses.
Small businesses have a constraint enterprise teams don't: every dollar of AI spend has to pay back within 2-3 months or it's cut. That filter pushes you toward the freemium tools with generous limits and away from $500/month enterprise plans.
The right stack is small and ruthless: one customer-facing agent (voice or chat), one operations agent (email + scheduling), one marketing tool. About $50-150/month total. Avoid the 12-tool stack the enterprise vendors will pitch.
Build no-code AI employees for inbox, meetings and CRM updates.
AIAGENTSBackground agent that drives the Cursor editor across multi-file changes.
Your personal AI chief of staff for inbox, calendar and life admin.
AGENTS15Brand-aware agents that draft and schedule campaigns across channels.
AGENTS25Multi-step GTM agents that wire research → outreach → reporting.
Sticker price is the start. Token spend, seat counts, and per-task overages move the real number meaningfully. Our calculator does the math.
For local services, retail, professional services, 1-50 employee businesses. our top pick is Lindy. The full shortlist of 5 agents below is ranked by editorial Agent Rank score and curated specifically for this vertical.
Score candidates on three axes: catalog fit (does the agent target your industry's workflows?), pricing (does the math work at your transaction volume?), and integration depth (does it plug into the tools you already run?). The shortlist below pre-filters for catalog fit — TCO and integration depth need your own analysis.
The shortlist includes a mix of freemium (free tier with usage limits), subscription, and per-task pricing. Open-source options exist for several workflows — see each agent's pricing page for the latest terms. Total cost depends heavily on volume; use the TCO calculator linked below.
Start with the lowest-risk, highest-leverage workflow your team runs. For small businesses that usually means the workflows listed below this section — they're the ones where AI agents have crossed from interesting demo to durable deployment.