PolyAI

Starting today, we're opening our Agentic Dialog Platform to every enterprise builder. Our dialog agents have resolved 1 billion+ customer conversations for clients like FedEx, Unicredit, PG&E, Marriott, Foot Locker, and many more. These aren't easy conversations. They solve problems like: > A patient booking medical transport who needs insurance verified on the spot. > A homeowner calling their utility company about a gas leak. > A cardholder figuring out why their must-have purchase was declined. Standard conversational AI was never built for this. It was designed for chat, adapted for voice later. It generates responses, but can't do what dialog requires: hold context under pressure, navigate ambiguity in real time, and actually resolve problems. So we built a better model. Our proprietary model Raven was built from the ground up specifically for dialog. Agent harness in the weights, not bolted on through prompts that drift under pressure. And in our platform, you can deploy Raven as your default or bring in GPT-5, Claude, Gemini, whatever model fits your use case or regulatory requirement. Now that the Agentic Dialog Platform is open, any team can create, test, and deploy dialog agents on the same model and infrastructure the world’s top brands trust on their hardest days. This opens up the pool of builders across your entire enterprise. The person who knows customers best, who runs operations, who owns the customer journey: they're all builders now. Two ways to build: > Poly Agent Builder: Describe your use case in natural language, and it configures your agent, knowledge base, and conversation flows automatically. Production-ready in ten minutes. > Agent Development Kit (ADK): Developers use this to build dialog agents the same way they build everything else. Use your own IDE, a coding assistant like Claude, version with Git, deploy from your terminal. Get started now: studio.poly.ai

@bally_kehal We're excited to hear what you build with it: studio.poly.ai

@polyaivoice Voice AI has been demos for too long. This is the first platform I've seen where the model is actually built for dialog, not adapted for it. Big launch.

Starting today, we're opening our Agentic Dialog Platform to every enterprise builder. Our dialog agents have resolved 1 billion+ customer conversations for clients like FedEx, Unicredit, PG&E, Marriott, Foot Locker, and many more. These aren't easy conversations. They solve problems like: > A patient booking medical transport who needs insurance verified on the spot. > A homeowner calling their utility company about a gas leak. > A cardholder figuring out why their must-have purchase was declined. Standard conversational AI was never built for this. It was designed for chat, adapted for voice later. It generates responses, but can't do what dialog requires: hold context under pressure, navigate ambiguity in real time, and actually resolve problems. So we built a better model. Our proprietary model Raven was built from the ground up specifically for dialog. Agent harness in the weights, not bolted on through prompts that drift under pressure. And in our platform, you can deploy Raven as your default or bring in GPT-5, Claude, Gemini, whatever model fits your use case or regulatory requirement. Now that the Agentic Dialog Platform is open, any team can create, test, and deploy dialog agents on the same model and infrastructure the world’s top brands trust on their hardest days. This opens up the pool of builders across your entire enterprise. The person who knows customers best, who runs operations, who owns the customer journey: they're all builders now. Two ways to build: > Poly Agent Builder: Describe your use case in natural language, and it configures your agent, knowledge base, and conversation flows automatically. Production-ready in ten minutes. > Agent Development Kit (ADK): Developers use this to build dialog agents the same way they build everything else. Use your own IDE, a coding assistant like Claude, version with Git, deploy from your terminal. Get started now: studio.poly.ai

@saidul_dev That's exactly the distinction that matters. Generating a response and actually resolving a problem are very different things.

@polyaivoice The interesting shift here is moving from simple conversational AI to systems built for real-time problem resolution.

@AhsanJaveriya Those conversations are exactly what shaped how we built Raven.

@polyaivoice The shift from “chat AI” to “dialog AI” is the next big leap. You nailed the problem statement perfectly. The patient transport and utility examples hit home, those are nightmare scenarios for generic LLMs.

@trikcode A lot of hard work went into getting here! We're excited for you to try it: studio.poly.ai

@polyaivoice This team is doing amazing work and pushing boundaries

@JafarNajafov Exactly! The people who understand the problem best should have access to the solution 🙌

@polyaivoice The real unlock here is giving the “customer expert” builder access. Most enterprises don’t lack AI tools. They lack a way for the people closest to the customer to turn their knowledge into working systems. That’s where this gets interesting.

@floriandarroman Hospitality is one of our strongest use cases. High volume, repetitive queries, and customers who just want a quick answer. Excited for you to try it 🙌

@polyaivoice I need to try that for my brother’s restaurant 👀

@AIbyMaryam The goal was to get the people who know the customer problems best building solutions themselves, without needing an engineering team behind them.

@polyaivoice Poly Agent Builder in ten minutes is wild.

@itsolelehmann That was the goal. Get something production-ready in minutes, not months.

@polyaivoice agent builder is a no-brainer

@JamesonCamp We'd love to hear how it goes as you build it out!

@polyaivoice the agent builder stuff is so cool also we are working on a chat agent for a mental health clinic, and intake for insurance complex with HIPAA so i love the idea of a voice agent that does that as well!

@sukh_saroy That's exactly it. Built for dialog from the ground up, not retrofitted!

@polyaivoice This is the kind of infrastructure conversational AI has been missing. Building dialog-first systems instead of chat-first adaptations is a major shift forward.

@systemdesignone Excited for you to try it. Let us know how you get on!

@polyaivoice Excellent, can't wait to try this!

@Igor_Buinevici Lots more where this came from!

@polyaivoice This is just amazing, team, this will change how many companies build relevant agents! And I am sure this is just the beginning!

@pankajkumar_dev We can't wait for you to try it 🙌

@polyaivoice gonna make something with this. looks good.

Please join us in welcoming all four on board!

Danielle Waknine joins our Canadian operations to lead GTM expansion into new verticals. She comes from Shopify, where she scaled the B2B vertical from zero to $100M in under a year.

PolyAI is growing fast, and we're bringing in a bench of incredible leaders to keep building. Read more about the hires, our new Toronto hub, and where we're headed next: poly.ai/en/blog/PolyAI…