Interactive step-by-step guides plus AI knowledge base for customer support deflection and employee onboarding.
The strongest interactive-guide platform for support deflection in 2026 — pick it when complex multi-step issues dominate your ticket queue, skip it when most issues resolve with a one-screen FAQ.
Last verified: April 2026
Sweet spot: a B2B SaaS or fintech / healthtech company with 50K–5M end-users where the support queue is dominated by complex multi-step issues — account setup, integration failures, password / SSO troubleshooting, billing — that static articles can't resolve in one read. Stonly's interactive guides are genuinely the right tool for that job, and the 30–60% deflection rates customers report are realistic on the right use cases. Internal use (agent decision trees, SOP guides) is a strong secondary value prop that often pays for the platform alone. Failure modes. First, Stonly works only when someone owns guide authoring and maintenance — guides drift out of date faster than articles because they encode UI flows, and stale guides actively hurt CSAT. Budget for 0.5–1 FTE on docs ownership at scale. Second, the AI Resolution Bot needs broad guide coverage to perform well; deploying it on top of a 20-guide library produces confident hallucinations. Third, the price tier jumps are aggressive; model MAU growth carefully before signing annual. What to pilot. Pick the top 3 most-painful multi-step ticket categories from your last 90 days of CX data. Build branching Stonly guides for each, embed them in the corresponding contact-form deflection paths, and measure ticket-volume change over 60 days. If deflection on those categories lifts 25%+ and the saved support hours exceed the platform cost, scale to your top 10. If deflection is flat, the issue isn't the format — it's root-cause friction in the product itself, and Stonly won't fix that.
Stonly is a Paris-based customer-support platform built around a distinctive primitive: interactive, branching step-by-step guides that walk users through troubleshooting, onboarding, or product workflows one decision at a time, replacing the wall-of-text help article with a guided experience. The 2024–2026 product expanded into a full self-service stack: AI-powered knowledge base search, AI-generated guide drafting from existing docs or videos, in-app embedded checklists and tooltips for product onboarding, and an AI Resolution Bot that combines guide content with LLM reasoning to answer customer questions in chat surfaces (Intercom, Zendesk, Salesforce Service Cloud). The platform handles both customer-facing self-service (help centers, in-app help widgets, contact forms with deflection logic) and internal use cases (agent-side decision trees for support reps handling complex tickets, employee onboarding flows, SOP guides for ops teams). Authoring is no-code with a visual flow editor, branching logic, embedded videos and forms, completion tracking, and analytics that show where users abandon a guide. The AI layer can ingest existing PDFs, help articles, or recorded screen-share videos and convert them into interactive guides automatically. Stonly's position in 2026 is the interactive-guide specialist — Document360 owns AI knowledge bases, Intercom owns chat, but Stonly is uniquely strong on the guided-flow experience that converts a passive doc into an active troubleshooter. Customers report 30–60% support-ticket deflection on the right use cases (complex multi-step issues where a static article fails). The in-house affiliate program pays recurring commission and converts well from CX, support-leader, and ops audiences.
Pricing is steep — the entry tier at $199/month is tight on MAU allowance and the Growth tier at $499 is where most real deployments land, which puts Stonly out of reach for SMBs with under $5M ARR. AI Resolution Bot is impressive but quality depends heavily on guide coverage; gaps produce confidently wrong answers. Authoring branching guides is more time-intensive than writing static articles — first-time customers underestimate the build effort by 2–3x. Analytics are good but lack the depth of dedicated product-analytics tools (Amplitude, Pendo) for advanced cohort analysis. Mobile widget rendering occasionally has CSS conflicts with custom-themed customer apps.
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