Frigade
Frigade is an AI-native digital adoption platform for product onboarding, in-app guidance, and customer support deflection. Where legacy digital adoption tools require teams to script tours, build decision trees, and rewrite docs every time the product changes, Frigade ships an AI assistant that learns the product itself and guides users through real workflows. The result is in-app help that stays accurate as your product ships, with no scheduled audits and no maintenance backlog. Frigade ships as two products that work independently or together: Frigade Assistant and Frigade Engage. Frigade Assistant is an AI agent for in-app user onboarding, customer onboarding, and product adoption. Rather than ingesting documentation and answering questions in a chat sidebar, Assistant deploys agents that use your product the way real users do. Setup is no different from adding a new user account: provide credentials and a URL, and the agent starts mapping the product. It learns your app end to end by navigating it, documenting workflows step-by-step, and reconciling that experience against your existing knowledge base. When the live product diverges from the docs, the agent prefers the live behavior, because that is what your users will actually encounter. Once live, Assistant runs inside your product as an in-app overlay. It answers user questions in context, walks multi-step setups, fills forms with the user, navigates the UI on the user's behalf, and takes actions across your product instead of just describing the steps. When a question genuinely needs a human, Assistant hands off to your support team with full session context: what the user was trying to do, what they had already tried, and where they got stuck. The hand-off includes far more than a chat transcript, so the receiving rep can pick up immediately. Assistant also shows up proactively. Suggestions are AI-generated product tours and magic links that surface for the specific user who needs them at the right moment, rather than blasting the same flow at every new signup. Anyone on the team can write a Suggestion in plain language: when a customer success lead notices a pattern, they describe the desired help in a sentence, and the Assistant runs the walkthrough at the right moment for the right account. There are no decision trees to configure and no triggers to hand-build. The targeting holds up because the agent reads the actual product state, not a recorded flow. Common Assistant use cases include in-app customer support, support deflection, user activation, customer onboarding, feature adoption, product adoption, in-app surveys, virtual CSM coverage, and expansion or upsell flows. Product teams use Assistant to get new users to first value faster. Support teams use it to absorb the long tail of repetitive how-do-I questions before they hit the inbox. Growth teams use it to surface the next relevant feature at the moment a user takes a related action. The same in-app assistant handles every audience without re-configuration, because the agent is reading the live product and adapting to what the user is doing. The dashboard that ships with Assistant gives teams visibility into what users are actually asking about, how the AI is responding, and whether those responses resolve their issues. Insights are auto-categorized themes from every conversation, so you can see why users get stuck and where the product itself needs work. Everything can be exported to existing analytics tools, connecting AI insights with broader user data. Most teams install Assistant in hours and go live with their customers within a day or two. As the product changes, the agent re-learns automatically. Ship a new feature: it gets discovered. Move a button: the agent updates its mental model. There are no flow files to maintain and no help docs to keep in sync. Teams replacing legacy DAPs like Pendo, WalkMe, Appcues, Userpilot, and Whatfix come to Frigade specifically because the maintenance burden that broke their previous tool disappears: the agent stays current on its own. Frigade Engage is the deterministic, code-first side of Frigade. It is a drop-in React component library for engineering teams that want code-level control over guided onboarding, feature adoption, interactive walkthroughs, and onboarding tooltips. Engage ships polished defaults for checklists, product tours, banners, announcements, and in-app surveys. The defaults (animation curves, empty states, the way a checklist collapses on the last step) are sweat-tested, so teams can install on a Friday and ship something polished by Monday. Every component, animation, and copy line is overridable in code. Install in 15 minutes. Engage fits teams who want customer onboarding that is deterministic, version-controlled, and lives in their own codebase. It is the right pick when engineering needs explicit guarantees about exactly when a checklist shows up, what step the user is on, and how the flow integrates with the rest of their app state. Some teams pair Engage with Assistant: Engage handles the strict, version-controlled flows (the first checklist on day one, the regulated banners), and Assistant handles everything conversational, contextual, and emergent (the long tail of how-do-I questions, the proactive Suggestions, and the action-taking on the user's behalf). Frigade integrates with the tools customer-facing teams already use. On analytics, that is PostHog, Amplitude, Segment, Mixpanel, Heap, RudderStack, and Google Analytics. On CRM and help desk, that is HubSpot, Salesforce, Intercom, Zendesk, Pylon, Freshdesk, Front, and Help Scout. On communication, Slack, Microsoft Teams, and Discord. On developer documentation, Frigade can ingest help center content from Mintlify, ReadMe, GitBook, and Notion to inform agent behavior. There is a REST API, a JavaScript SDK, a React SDK, a Mobile SDK on Enterprise plans, and webhooks for custom work. The goal is not to replace your support stack. It is to handle routine cases inside the product so your team can focus on the questions that genuinely need a human. Security and compliance: Frigade is SOC 2 Type II certified and GDPR compliant. Data is encrypted in transit with TLS 1.2+ and at rest with AES-256. EU data residency is available for teams that need it. There is a zero-retention policy on LLM providers, so customer data is never used for model training. Personally identifiable information is automatically scrubbed on inputs and outputs. Enterprise customers can self-host Frigade on their own infrastructure with their own LLM keys for
Average Rating: 4.8/5.0
Total Reviews: 24
How Do G2 Users Rate Frigade?
- User Segmentation: 9.8/10 (Category avg: 8.8/10)
- Ease of Use: 9.5/10 (Category avg: 9.0/10)
- Text Bubble Walkthroughs: 9.4/10 (Category avg: 9.1/10)
Who Is the Company Behind Frigade?
- Seller: Frigade
- Year Founded: 2022
- HQ Location: San Francisco, US
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LinkedIn® Page: www.linkedin.com
5 employees on LinkedIn®
Who Uses This Product?
- Top Industries: Computer Software, Information Technology and Services
- Company Size: 71% Small, 29% Medium
What Are Recent G2 Reviews of Frigade?
"Role-Aware In-Product AI Help That Guides Users Right on Screen"
Rating: 5.0/5.0 stars
— levente o.
"The assistant answers before our team has to"
Rating: 5.0/5.0 stars
— Matteo B.
