Strides Build adds in-app AI to your product that proactively helps users, reduces support tickets, and flags churn risk — giving your CS team superhuman leverage.
Give Your CS Team Superhuman Leverage.
Instant User Support
Every user gets instant, accurate answers about their account, their data, and their workflows — without waiting for your CS team to respond.
Churn Risk Detection
Strides monitors usage patterns and flags accounts showing churn signals — low logins, declining API usage, feature drop-off — before they cancel.
Proactive Outreach
When a user hasn't logged in for 14 days or their usage drops, Strides proactively reaches out with a helpful, personalized check-in — not a generic email.
One-Script-Tag Install
Paste one line of code and walk away. Strides auto-discovers every page, route, and API endpoint in your app without any configuration.
Autonomous Actions
The AI doesn't just answer questions — it executes tasks. Draft an invoice, reassign a ticket, send a report — using your real APIs, in your real product.
100% White-Labeled
Your branding. Your product name. Your colors. Strides is permanently invisible. No "powered by" badge, no Strides mention anywhere in the UI.
How In-App AI Changes the Economics of Customer Success
Customer success is fundamentally a capacity problem. Every CS manager has a ratio: accounts per CSM. As the company grows, you either hire more CSMs or accept that some accounts get less attention. The accounts that get less attention churn more. Churn is expensive. So you hire more CSMs. The unit economics of CS don't improve with scale — they stay constant at best.
In-app AI changes this dynamic by providing every user with immediate, accurate, account-specific support — without any CSM involvement. When a user has a question about their data, the AI answers it correctly using their actual live data. When they want to do something complex in the product, the AI executes it for them. When they can't figure out a workflow, the AI walks them through it in real time. The volume of questions that reach your CS team drops significantly.
The churn prevention layer is where the economics get most interesting. Strides monitors usage patterns at the user and account level, flagging accounts that are showing churn risk signals — declining login frequency, feature adoption drop-off, reducing API usage, or a pattern of failed task attempts. These signals reach your CS team as prioritized alerts, so they can intervene proactively before the user has already mentally checked out.
Proactive outreach is the other side of this. When a user hasn't logged in for 14 days, Strides sends a personalized check-in — referencing the specific features they were using and offering to help them get value from the product again. This outreach happens automatically, at scale, for every user — including the long tail of accounts that a CSM would never have time to proactively reach out to.
CS teams that deploy Strides Build typically report two outcomes: support ticket volume drops 40–60% within the first month, and the CSMs who remain can focus on high-value relationship work — strategic business reviews, expansion conversations, escalation management — rather than answering repetitive "how do I do X?" questions all day.
Frequently Asked Questions
How does the AI detect churn risk?
Strides monitors behavioral signals at the user and account level — login frequency trends, feature usage breadth and depth, API call patterns, error rates, and support contact frequency. Accounts crossing configured thresholds are flagged in the CS dashboard.
Can the AI proactively reach out to users who are at risk?
Yes. You can configure automated outreach triggers — for example, "send a check-in to any user who hasn't logged in for 14 days" — and Strides sends personalized, contextual messages automatically. The message references the user's specific usage history, not a generic template.
How does the AI know each user's specific account data?
Strides queries your product's APIs in real time for each authenticated user. Every response is grounded in that user's actual live data — their records, their settings, their activity history. The AI gives account-specific answers, not generic ones.
What does the CS team see in the dashboard?
The CS dashboard shows health scores for all accounts, flagged accounts with churn risk signals, AI interaction summaries by account, support deflection metrics, and usage trend data. CSMs can filter by risk level and prioritize their outreach accordingly.
Can the AI escalate to a human CS rep when needed?
Yes. You can configure escalation triggers — for example, "if a user expresses frustration or mentions cancellation, notify the assigned CSM immediately." The CSM gets an alert with the full conversation context so they can pick up the conversation immediately.
How quickly do companies typically see ticket volume reduction?
Most customers see meaningful ticket reduction within the first 2–4 weeks of deployment, as users discover they can get instant answers from the AI. The full impact — typically 40–60% reduction — is usually visible within 30 days.
Does the AI support multiple languages for international user bases?
Yes. Strides supports interactions in the user's language — if they message in French or German, the AI responds in kind. Language detection is automatic, and all responses remain grounded in the user's real account data regardless of language.