Frigade Assist API

The Frigade Assist API adds product expertise to an AI agent you have already built. In one tool call — importing frigade from '@frigade/ai' and running frigade.assist({ query }) — your existing agent can answer product questions and guide users through any workflow, right inside the agent you already built. It is made for product and engineering teams who own an in-app agent and want it to show users where to click instead of replying with a wall of text, and for support and CX teams who need those answers to be accurate and controllable without engineering work. The problem it addresses is simple: most in-app AI agents cannot see the screen. When a user asks 'how do I do this?', the agent answers with a wall of text. Your agent has read your docs, but it has never used your product. That matters because written documentation is accurate exactly once — the day it is written. Docs go stale the day you ship, and an agent that links a help article from two releases ago sends users down paths that no longer exist. Frigade instead gives your agent the same product your user is looking at, so it can walk them through the workflow rather than pointing at a document. At the center of the product is a living model of your product that Frigade builds by using it. Frigade deploys agents that take a seat like any user — you invite Frigade the way you would invite a person, with nothing to document or configure first. Those agents work through your real workflows, clicking the same paths your users click and mapping how your features actually connect. Frigade also takes in your existing knowledge base. Then, because your product changes, it re-learns on every release: you ship, the map updates itself, and your agent is never a version behind. Ship a new feature and it is picked up; move a button and the guidance follows. Answers are grounded in the product rather than the documentation. Every answer comes from how your product behaves right now, so it holds up even when the help center is two releases behind. Your team stays in control of that content: anyone can rate any answer and write the behavior they want instead — no code — and that guidance holds from the next conversation on. Every reply your agent gives through Frigade is logged, and you can see every conversation in the dashboard, in Slack, or over the API. This is deliberately not only work for engineers: support, CS, and CX own the answers, rating replies and stating what they wanted instead, with no ticket to engineering. Beyond answers, Frigade provides guidance: the real steps, rendered inside your own UI. When a user needs to manage SSO, for example, the agent can show a step-by-step card such as 'Step 1 / 3 — Open Security to manage SSO. Follow the highlight.' Insights then show where users get stuck, where the agent helps, and where it hands off. When Frigade cannot help, it knows its limits and hands off cleanly, saying so right away and passing the conversation to your team. Steering lets your team tune the system over time — the more your team puts in, the better it gets. And alongside answering and guiding in the moment, Frigade can proactively surface the right feature to a user right when they would benefit from it, using the same idea as Frigade's Suggestions product to help drive feature adoption and expansion revenue. Underneath the single tool call sits an entire engine that relearns your product, plus a platform for your team to manage with no code. Frigade is a lightweight SDK and two primitives: register it as a tool your agent can call, in a few lines, and your agent can now run a live product tour or return a grounded product answer. Your agent stays in control — it decides when to call Frigade and what to do with the result — and keeps its own reasoning and voice. Frigade adds product expertise to your agent; it never takes over the conversation. Every call returns fast with a clear answer, and when Frigade cannot help it says so immediately so your agent never stalls or burns latency waiting. The four layers are a product model built by using your product and rebuilt every release, grounded answers written from your actual product, guidance rendered inside your own UI, and steering that improves with your team's input. The outcome is an agent that answers about the version that shipped rather than the version someone last documented. Because Frigade relearns automatically, nobody on your team has to retrain the agent or rewrite prompts when you ship. Support and CX can fix a bad answer themselves instead of filing engineering work. Teams also see measurable deflection: one customer reported that Frigade solved over 400 queries a month that would otherwise have gone to support, equivalent to two hires they did not have to make, and said it paid for itself within the first two months. Retell AI, which builds agents for a living, gave Frigade access to its product and reported that it learned the product on its own, allowing the agent to take someone through a workflow without manual documentation. Concrete workflows include answering plan and permission questions — for example, whether the Growth plan includes SSO, where the agent can answer yes, note that it is turned on under Settings and Security, and mention that SAML is Enterprise-only. It guides setup tasks such as adding a webhook, showing the user where to paste an endpoint URL and confirming the test event. It resolves billing questions, walks users through connecting integrations like Slack, and handles access questions. When a request is beyond it — deleting a workspace and all data, for example — it hands the conversation to a human. It also proactively surfaces the right feature at the right time to drive adoption and expansion revenue. Frigade Assist API is built for product and engineering teams that already run an in-app agent, and for the support, CS, and CX teams that own the answers. It is framework-agnostic: it integrates cleanly with the Vercel AI SDK today, and any agent that can call a tool can call Frigade, regardless of how the agent was built or which models it runs. On security, Frigade is SOC 2 Type II certified and fully GDPR compliant, encrypts data in transit with TLS 1.2+ and at rest with AES-256, offers EU data residency, a zero-retention LLM policy, and automatic PII scrubbing, and runs guidance with the user's own permissions. Teams needing full data control can self-host Frigade with their own LLM keys. Pricing starts at $1,000 per month with usage-based scaling, and enterprise plans with custom pricing are available. If you have not built an agent yet, Frigade ships a full in-product assistant that learns your product and guides users in real time, no code required. Frigade Assist API's primary promise is that your agent stops pointing at documentation and starts showing users exactly where to click. By adding one tool call to the agent you already built, you give it a product model that learns by using your product, re-learns on every release, and is tuned by your own team — with grounded answers, in-app guidance, clean handoffs, and full visibility into every conversation.