> For the complete documentation index, see [llms.txt](https://docs.helvia.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.helvia.ai/resources/release-notes/helvia.ai-release-2026.07.16.md).
# Helvia.ai Release 2026.07.16
## 1. Redesigned Create Agent Experience With Blueprints
Creating a new agent now follows a single, guided wizard built around Blueprints. You pick a Blueprint, connect the plugins it needs to your Workspace integrations, and name your agent. What was previously called Templates is now called Blueprints.
**Why it matters:** A single, guided path makes it clear what you are creating and which integrations your agent will use before it goes live.
**Example use case:** You want to spin up a customer-support agent that uses your organization's LLM provider. You choose a Blueprint, connect the required plugin to an integration your Workspace already has, set a name and language, and your agent is ready.
**How it works:** When you create a new agent, the wizard walks you through picking a Blueprint, mapping its plugins to your Workspace integrations, and entering the agent details.
## 2. Guide and Tag Content From SharePoint and Azure Blob Integrations
AI-Powered Knowledge Base integrations for SharePoint and Azure Blob gain two controls: You can now add per-integration instructions that shape how files are processed, and any tags set on the integration are applied to every article it generates.
**Why it matters:** You get more control over how synced content is structured and an easy way to filter it later, applied consistently across every file an integration brings in.
**Example use case:** You connect a SharePoint library of HR policy documents. You add an instruction telling the system how to split those documents, and you tag the integration with "hr". Every article synced from that library follows your instruction and carries the "hr" tag, so you can later restrict an agent's answers to HR content.
**How it works:** Open the SharePoint or Azure Blob integration and select AI-Powered segmentation mode. The **Additional Instructions** field appears in the segmentation settings, and it is hidden in Standard mode. Instructions and tags apply to files synced after you save. Existing articles pick up changes on their next manual full sync. Editing tags replaces the previous set on regenerated articles rather than adding to it.
## 3. Updated Language Detection Plugin
An updated Language Detection plugin runs on the Helvia.ai Platform's current LLM path and supports OpenAI, Azure, and Google Gemini. The previous plugin is renamed 'Legacy' and keeps working, so existing setups are untouched until you choose to switch.
**Why it matters:** Updating language detection brings it in line with the rest of the platform, allows more customization per model and adds Gemini support on that path.
**Example use case:** You run a multilingual agent and want language detection handled through Gemini. You activate the provider on the new plugin, configure the model properties, and detection starts. Your existing legacy configuration stays exactly as it was in case you need it.
**How it works:** In the Plugins screen you will find a single **Language Detection** card. The current providers, OpenAI, Azure, and Gemini, appear at the top, and a Legacy section below holds the older providers. Only one provider can be active for Language Detection at a time across both sections, so activating a provider in one turns off any active provider in the other. Existing legacy activations keep running on the legacy path until you explicitly re-activate on the new plugin.
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# Agent Instructions
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