Yedric.ai

Yedric.ai is an embeddable AI agent that turns a SaaS application into an AI-native product. Rather than adding a chatbot that only answers questions and points users at a help document, Yedric lets users describe what they want in plain language and then carries the request through to completion using the product's own documentation, APIs, and existing tools. It is aimed at SaaS and Shopify app developers who want their users to control the product conversationally, and at the end users themselves, who should not have to learn where every feature lives. According to the Product Hunt listing, developers can make an existing product AI-native in under 30 minutes instead of building and maintaining their own agent experience. The problem Yedric addresses is a familiar one in software: features exist, but users cannot find them or do not know how to combine them. Most AI chat widgets stop at answering a question, which leaves the user to read a guide and perform the steps themselves. Yedric is built on tool calling instead. The product's own team decides which actions the assistant is allowed to take, and the assistant takes them rather than describing them. The site frames this as turning intent into action: users ask for outcomes, and Yedric gets them there. That difference matters because support conversations and onboarding flows often fail not when the answer is missing, but when the user still has to act on it themselves after the answer arrives. The core capability is action, not conversation. Yedric connects to a product's APIs so it can execute real operations inside the application. A demonstration on the site shows a user asking Yedric to create a 20% discount for customers who bought a product in the last 30 days. Yedric reports that it is finding those customers and creating the code, then shows the results: 214 matching customers found and a discount code named SAVE20 created. From that result the user can continue the same conversation, for example by asking Yedric to notify those customers or to extend the offer to 60 days. This illustrates the pattern Yedric is designed around: a natural-language request is resolved into a sequence of concrete actions inside the app, and the user stays in control of what happens next. Yedric is supplied with the product knowledge it needs to understand the application. The site states that you can give Yedric documentation, PDFs, files, and URLs so it knows how the app works. On top of that knowledge, the assistant is context-aware page by page: it understands where users are and what they are doing. The examples given are a user on the new-order screen asking to create a draft order, a user on the products screen asking for a bulk price update, and a user on the billing settings screen asking why they were charged. Matching the assistant's understanding to the page the user is already on means the request does not have to be re-explained and the executed action is relevant to the screen in front of them. Because Yedric can take real actions in a production app, the platform includes several safeguards. The site describes secure-by-default authentication through JWT, API keys, signed sessions, and Shopify-specific flows, and states that secure mode binds sessions to users so no credentials leak to the client. Observability is built in as well: teams can see what users ask, what Yedric does, and where things go wrong. On the model side, Yedric supports bringing your own API keys for OpenAI, Anthropic, Gemini, and any compatible model, with providers paid directly and no platform markup. Together these pieces are intended to make it safe to allow an assistant to operate inside a live application while still giving the owning team visibility and control. The overall method is summarised by the site as intent in, action out. You connect Yedric to your APIs so it can act rather than only explain how. The illustrated flow shows a user asking Yedric to set up a birthday discount, which the assistant resolves into a chain of tool calls: create a discount code, tag the customer's birthday, and trigger a flow through MCP, in this case klaviyo.trigger_flow. This shows how a single sentence can be mapped onto several capabilities the product already has, including third-party tools exposed through MCP. The knowledge sources, the page context, and the permitted tools all feed into that resolution, so the assistant works with your docs, your APIs, and your app's own tools. The site presents two main outcome areas. The first is onboarding: teams using Yedric see users complete setup instead of abandoning it halfway, without support tickets or lost activations. A dashboard figure shown on the page reports 2,430 conversations in a month, up 66% versus the prior month. The second is support: Yedric answers the question and, if there is an action to take, performs it, giving users a 24/7 guru without having to read a guide and do it themselves. The page reports 281 hours 52 minutes saved for a team, with the figure trending from 3 hours in a prior month. Beneath both outcomes is the idea stated in the page headline: better UX for users, better products for you. Concrete use cases appear throughout the site as example user requests. Users have asked Yedric to put something into a spreadsheet, to fix a disconnected integration, to recommend the best billing plan for their usage, to turn off email notifications, to check whether all products are configured correctly, and to change a logo color to a specific hex value. In each case the request is an outcome rather than a navigation instruction. The page-context examples add more: creating a draft order from the new-order screen, performing bulk price updates from the products screen, and answering billing questions from the billing settings screen. The Shopify discount example shows a longer workflow that includes finding matching customers, generating a code, and optionally notifying those customers or extending the offer. Yedric targets SaaS and app developers, particularly those building on Shopify. The site displays logos of Shopify apps already using it: MESA, Infinite Options, Smile, Tracktor, and Uploadery. Integration points described in the content include your APIs and your app's own tools, MCP for third-party flows such as Klaviyo, documentation, PDFs, files and URLs as knowledge sources, and the model providers OpenAI, Anthropic, and Gemini through your own API keys. Security integrations include JWT, API keys, signed sessions, and Shopify-specific flows. Pricing is stated simply on the site: 100% free, with no credit card required to get started. Yedric.ai's value proposition is that it converts a product's existing capabilities into something a user can simply ask for. By combining tool calling against your APIs with your own documentation, page-level context, secure session handling, observability, and bring-your-own-model keys, it lets an app take real actions from a natural-language request instead of stopping at an explanation. For development teams, that means an AI-native experience can be added to an existing product quickly rather than built and maintained from scratch, while users get an assistant that understands what they want and helps them get it done.