> ## Documentation Index > Fetch the complete documentation index at: https://docs.poly.ai/llms.txt > Use this file to discover all available pages before exploring further. # 04.2025 > April 2025 release notes. The **April 2025** PolyAI Agent Studio release includes new tools for call review, debugging, and utility development. Expand the items for details:

We have refined the sidebar layout to better group tools by function and clarify where key capabilities live. Think of this as a smart re-balancing of where things go and a review of section naming. ### What's new, renamed, or moved: **Analyze** renamed to **Manage** * **Agent Analysis** → New feature. See below for more details. **Build** * **Agent** → Renamed from **About**. * **Model Training** → Moved here from **Annotations**, previously under **Conversation Review**. * **Variant Management** → Moved here from the **Configure** menu. **Voice** * **Agent Voice** → Moved here from Configure (combines features previously under **Voice** and **Rules**) * **Cache Management** → Previously the **Audio Management** tab. **Configure** * **Environments** and **Project History** → New sections, previously under **Environment & Versions**. ### Why it matters These adjustments make it easier to find what you need, reduce clutter, and prepare the platform for future capabilities. You can now generate **LLM-powered performance metrics** in the PolyAI Agent Studio using the new **Agent Analysis** flow. Define a custom prompt and category set, then run it across a batch of calls to generate insight-rich evaluations and visual summaries. call-batch-run

**How it works:** * Create a custom evaluation prompt, with categories and descriptions * Select a batch of calls using the Agent Analysis feature. * Automatically assess agent performance across key custom criteria like tone, intent success, or compliance (or any other potential variables) * View results in a dedicated **Agent Analysis UI**, with graphs showing how your calls measure up against each evaluation axis Agent Studio now supports real-time collaboration and edit tracking across your team.

Multi-user refresh view in action

**How it works:** * See who else is editing a draft in real time. * Receive notifications when changes are saved by others. * Copy unsaved edits before refreshing to avoid overwriting. * View full change logs using the **history** panel. You can now use an LLM to review and rate calls. agent-analysis

**What you can do:** * Rate calls for tone, intent success, or compliance * Use project-specific categories * Get automatic summaries You can now filter conversations by workspace on the Conversations page. workspace-filter

**Why it helps:** * Focus on the calls your team is responsible for * Cleaner review experience for large orgs This is an opt-in feature and will not be enabled by default. Contact PolyAI for access. You can now extract structured address data from free-text input using a built-in LLM utility: `extract_address()`. extract-address-util

**What it does:** * Parses the most recent user message for address info * Returns an `Address` object with fields like street, postcode, and country * Raises an `ExtractionError` if parsing fails **Usage:** ```python theme={"theme":{"light":"github-light","dark":"github-dark"}} try: address = conv.utils.extract_address(country="US") conv.state.parsed_address = address except ExtractionError as e: conv.state.address_error = str(e) ``` **Address object:** ```python theme={"theme":{"light":"github-light","dark":"github-dark"}} @dataclass class Address: street_number: Optional[str] street_name: Optional[str] city: Optional[str] state: Optional[str] postcode: Optional[str] country: Optional[str] ``` **Other details:** * Calls an LLM, so may take a few seconds * You can optionally validate against a list of known addresses * Some fields may be missing depending on input quality You can now access earlier conversation turns from within utility functions using `conv.history`. **What it does:** * Returns a list of events: user inputs, agent replies, function calls, etc. * Useful for writing context-aware logic **Usage:** ```python theme={"theme":{"light":"github-light","dark":"github-dark"}} def some_function(conv: Conversation): history = conv.history for event in history: print(event.to_dict()) return { "utterance": "Here's a response that depends on previous turns.", "content": f"Conversation so far: {str(history)}" } ``` **Why it matters:** * Build logic based on what's already happened in the conversation * Avoid passing state manually * Better debugging and flow control You can now export and import variants between agents or environments. **What you can do:** * Export all variant data to CSV * Edit things like contact numbers or opening hours in bulk * Reimport to update the same or a different agent **Why it matters:** * Makes it easy to scale across multiple sites * No need to rebuild variant logic from scratch * Keeps your CSVs in sync with other tools See the full [variant management](/variant-management/introduction) page for advanced use cases like SMS personalization or routing. Reviewed conversations now show the **variant ID** used in each call. variant-id

**Why it matters:** * See exactly which variant was active * Easier to debug and compare different versions * Adds context for QA and bug tracking The built-in handoff now supports **handoff reasons** and **custom utterances**, and you can now use a `handoff()` method directly inside functions. **What you can do:** * Specify a reason for the handoff (e.g. compliance, escalation, etc.) * Set a custom utterance to be spoken at handoff * Use `handoff()` programmatically inside a [function](/tools/introduction). **Example usage:** ```python theme={"theme":{"light":"github-light","dark":"github-dark"}} def escalate(conv: Conversation): return conv.call_handoff( reason="policy_violation", utterance="Let me transfer you to a specialist who can help." ) ``` call-batch-run

You can now configure multiple TTS voices for your agent and distribute them across calls. Use percentage values adding up to 100% to distribute the likelihood of each agent answering a call. **Why it matters:** * A/B test different voices for performance or tone * Assign different voices to different intents or caller types * Create more natural, human-like team dynamics **What you can do:** * Select and assign multiple voices * Preview how your agent sounds across scenarios For help or feedback, reach out to your PolyAI representative.