Yedric.ai

Yedric.ai is an embeddable AI agent that turns your SaaS app into an AI-native product. Instead of asking users to learn where every feature lives, Yedric lets them describe what they want to accomplish in plain language, and then it carries out the task using your documentation, your APIs, and your app's own tools. It is built for SaaS and app developers who want their existing product to feel AI-native without having to build and maintain a bespoke agent experience, and the company states that developers can make their product AI-native in under 30 minutes. Rather than a standalone destination, Yedric is embedded directly into the product so that the assistant lives where the work already happens. Most AI chat widgets stop at answering a question. They explain the steps a user should take and then leave the user to go and do the work themselves, effectively pointing at a help doc. That still forces people to learn the interface and navigate to the right screen before anything gets accomplished. Yedric was created to close that gap: its site explicitly distinguishes it from being a chatbot that points at a help doc, presenting it instead as a system that takes real actions on the user's behalf. The core premise is that users should be able to ask for outcomes, not hunt through menus, and that the product should meet them at the moment they express intent. Yedric is built on tool calling. You decide which actions the agent is allowed to take, and it takes them rather than merely describing the steps. For example, when a user asks to 'set up a birthday discount,' the flow can run create_discount_code, tag_customer_birthday, and an MCP action such as klaviyo.trigger_flow in sequence. Because you connect Yedric to your APIs, it can act inside your product instead of only explaining how something is done. The site frames this simply as 'Intent in. Action out.' — meaning natural-language requests are translated into concrete operations that your app already knows how to perform. Knowledge can come from anywhere. Yedric ingests the documentation and product knowledge it needs in order to understand your app, accepting docs, PDFs, files, and URLs as knowledge sources. On top of that, context awareness works page by page: Yedric understands where users are and what they are doing, so its behavior adapts to the screen they are on. Example contexts shown on the site include /orders/new for creating a draft order, /products for bulk updating prices, and /settings/billing for questions about why a user was charged. This combination of configurable knowledge and page-level context is what lets the assistant respond usefully in the specific part of the product a user is working in. Security is designed in by default, using JWT, API keys, signed sessions, and Shopify-specific flows. A secure mode binds sessions to individual users so that no credentials leak to the client. Yedric also includes observability, letting teams see what users ask, what Yedric does, and where things go wrong, which matters when an assistant is taking real actions in a production app. Finally, you can bring your own API keys and use OpenAI, Anthropic, Gemini, or any compatible model, paying providers directly with no platform markup. The site makes the underlying point clearly: letting an assistant take real actions in a production app is a reasonable thing to be nervous about, and Yedric is built to make it safe to say yes. The overall approach is to make your existing product AI-native rather than to bolt on a separate assistant. Yedric is embedded into your SaaS, connected to your APIs and knowledge sources, and constrained by the set of actions you permit. As the site puts it, it becomes your assistant, with your knowledge and your actions. That combination of tool calling, page-level context, and configurable knowledge is what moves a request from plain-language intent to a completed outcome inside the app the user already uses — without the user needing to know where a feature lives or how to reach it. The stated outcomes include better UX for users and better products for developers. Teams using Yedric are described as seeing users complete setup instead of abandoning it halfway, without support tickets or lost activations; a dashboard example shows 2,430 conversations this month, up 66% versus the prior month. Support goes beyond 'here's how to,' because Yedric answers the question and, when there is an action to take, performs it — giving users a 24/7 guru without having to read a guide and then do the work themselves. One example cites 281 hrs 52 mins saved for a team, 3 hrs versus the prior month. Concrete scenarios from the site include creating a 20% discount for customers who bought a product in the last 30 days, where the demo found 214 matching customers, created the code SAVE20, and offered follow-ups such as notifying those customers or extending the offer to 60 days. Other examples include setting up a birthday discount, putting data into a spreadsheet, fixing a disconnected integration, asking which billing plan best fits a user's usage, turning off email notifications, checking whether all products are configured correctly, and changing a logo color to a specific hex value. Yedric is already at work inside Shopify apps including MESA, Infinite Options, Smile, Tracktor, and Uploadery. Yedric targets SaaS and app developers, particularly those building on Shopify, and it emphasizes getting started quickly: the site advertises 100% free access with no credit card required. Integrations and technical elements explicitly mentioned include Shopify-specific flows and sessions, MCP-based actions such as a Klaviyo flow trigger, and bring-your-own model providers OpenAI, Anthropic, and Gemini. Security primitives listed are JWT, API keys, and signed sessions, alongside signed sessions and secure mode that binds sessions to users. The core appeal for builders is that they do not have to build and maintain their own agent experience. In short, Yedric.ai turns a SaaS product into an AI-native experience by adding an embeddable agent that understands natural-language intent, knows the app's context and knowledge, and then takes real actions through tool calling and connected APIs. Its value proposition is straightforward: users simply say what they want done, and Yedric handles the interaction safely, observably, and quickly.