Introducing the first AI Agent built for Reviews Management

AI agents now handle over 50% of customer service volume. Support tickets, chat conversations, text messages, social media interactions - all automated with AI that understands context and integrates with business systems to deliver human-like resolutions.

Reviews drive modern commerce, with consumers overwhelmingly turning to them before making purchases. Perplexity serves over 780 million searches monthly - many including product reviews content. Google's AI overviews pull review snippets into billions of searches. Yet most brands are still managing reviews manually.

Until now, there was no AI agent built specifically for the end-to-end reviews workflow.

What we discovered talking to customers

Over the past year, we've been talking to customer service leaders and marketing teams across our customer base. A pattern emerged.

Every scaled brand has a small team - sometimes just one person - whose entire job is managing reviews. They read each submission. Check if the reviewer is a real customer or someone trying to game the system. Decide whether to publish it. Craft an empathic response. Flag anything interesting to management.

One head of customer experience at a major beauty brand told us her team spends 20 hours weekly just on review management. "It's a lot of manual work, but we can't ignore our customer’s voice."

Another brand hired two full-time people just to handle reviews. Thousands come in monthly. Each needs human judgment about brand safety, response tone, and customer context.

The more we learned about this workflow, the more obvious the opportunity became. Highly repetitive work that requires understanding brand guidelines, customer context, and business policies. Exactly what AI agents excel at, but nobody had built one specifically for reviews.

So we decided to solve it.

The scale problem nobody talks about

Let’s say you're running a growing brand. You get about 500 reviews monthly and have an active posture towards engaging customers through reviews. Each review needs human judgment - is this genuine? Does it follow brand guidelines? Should we respond? If so, how?

At 5 minutes per review (reading, deciding, crafting a response), that's 42 hours monthly. That's over a full work week just managing 500 reviews.

Scale to 1,000 reviews? That's 83 hours monthly - two full work weeks.

Scale to 2,000 reviews? That's 167 hours monthly - over four work weeks.

Scale to 5,000 reviews? That's 417 hours monthly. You need 2.5 full-time people doing nothing but review management.

This is mission-critical. You need to protect your brand reputation while making customers feel heard. You need context about what they purchased, their history, whether they're a VIP customer, or a first-time buyer. Generic replies are robotic. Personalized responses take forever.

For the first time, there's an AI purpose-built for exactly this problem.

How Siena Reviews Agent works

Connect your Yotpo account to Siena. The agent starts ingesting reviews. Setup takes minutes if you're on Shopify with Yotpo. Install the Siena integration, and enter your API keys. The agent syncs existing reviews and starts processing new ones according to your configuration.

From there:

Intelligent moderation with your brand guidelines

Tell the agent your review policy in natural language. "Don't publish reviews with profanity or competitor mentions. Flag anything defamatory." The agent screens every incoming review 24/7. Bad content never goes live. Legitimate feedback gets published immediately.

Personalized responses that know your customers

Choose which reviews get responses - negatives only, detailed positives, all of them. The agent crafts replies using your exact brand voice plus complete customer context. It knows their purchase history, previous reviews, and support interactions. So instead of "Thanks for the feedback!" it might say "So glad the serum is working for your sensitive skin routine - and we haven't forgotten you mentioned loving our vitamin C moisturizer too!"

Selective engagement for authentic interactions

Some reviews don't warrant responses. A simple "Great!" with 5 stars doesn't always need a reply. But a detailed review like "This vitamin helped my energy levels throughout my workouts, especially during my long weekend runs" gets a thoughtful response referencing their specific experience. The agent knows the difference and only engages where it adds real value.

Every response happens in minutes. Using Siena’s Thinking Time feature you can also set a delay from review to response, making the engagement feel natural.

Customer reviews as customer intelligence

Reviews Agent doesn't just handle feedback - it remembers everything.

Every review feeds into Siena Memory, our customer intelligence system. When that customer contacts support later or asks for product recommendations, the agent recalls their review alongside their complete purchase history.

Customer mentions needing a jacket. The agent remembers they left a review saying your large runs tight in the shoulders. It suggests styles with looser fits or recommends sizing up. The customer feels understood in a way that's impossible with traditional systems.

At scale, this transforms entire operations. Siena identifies patterns across thousands of reviews. "50% of customers this month mentioned this shoe runs small." "Quality complaints spiked in March." "Customers love battery life but want more colors." This intelligence flows to your product team without anyone manually reading through review databases.

Siena isn't just an AI agent for support. It's an intelligence layer for your brand. Reviews Agent makes that layer dramatically deeper.

Building review automation the right way

Building a reliable review management agent requires infrastructure and deep business context integration. You can't just let AI respond to angry customers without tight controls. One bad response destroys trust instantly.

Every response needs to respect brand guidelines, follow business SOPs, and sound human. When someone says "runs small," the right response depends on their purchase history, what they typically order, and their past reviews. Template responses feel robotic because they ignore this context.

Review platforms focus on collection and display. Building reliable AI agents requires different expertise - agentic infrastructure, choosing the right language models, memory systems, and a testing suite. That's what we've spent the past few years building at Siena.

Most importantly, reviews automation isn't like email marketing where generic works. It requires understanding nuanced customer feedback and crafting responses that feel personal at scale. The agent needs to know if this is their first purchase or if they're a longtime customer. Whether they mentioned specific concerns in past reviews. What products they typically buy.

That level of personalization demands an intelligence layer that most platforms simply don't have.

Generative Search Optimization on autopilot

Almost 1 billion users use ChatGPT weekly. Perplexity serves hundreds of millions of queries monthly. This is the new paradigm for shoppers - they're making buying decisions through generative engines like ChatGPT, Perplexity, and Gemini.

These engines train on web data. Your reviews data matters more than you think. Brands that publish reviews consistently and engage with customers have a higher propensity to show up in search results.

When customers ask Perplexity "what are the best products for dry skin?", it pulls from review content to answer. It creates pros and cons lists based on actual customer feedback. Brands with active review engagement get recommended more often. Your responses become indexed content that AI search engines use.

It's always a good idea to have a review strategy because that's going to influence how your product is perceived in AI-powered search results.

It's self-reinforcing. Customers see you respond thoughtfully to reviews, so they leave more detailed feedback. More engagement creates more indexed content. More content means better search visibility. Better visibility drives more customers who leave more reviews.

Siena Reviews Agent puts this entire flywheel on autopilot.

Enterprise-grade testing and safety

Bad AI responses kill trust and brand reputation. That's why Reviews Agent includes a complete testing infrastructure before you go live.

Use Siena's Testing Suite and Playground to simulate how the agent handles different scenarios. You can test exactly how the agent will moderate and respond in various scenarios before those actions go live. Feed a sample 1-star review laced with profanity and watch how the moderation policy handles it. Toggle "reply privately" mode during setup so you can review suggested replies before they go public.

The agent follows SOPs you define. You set the process and Siena executes them consistently. Every response gets logged for proof of work. You maintain complete oversight while automating the actual work.

Think of it as a training area for your AI. You can refine the SOPs and persona until you're confident in the output. Once you're satisfied the agent handles reviews like your best-trained human would, go live in just a few clicks.

Ready to scale your reviews and build intelligence?

While your competitors are still copying and pasting "Thanks for the 5-star review!" hundreds of times, you start building customer intelligence while driving your GEO flywheel. Every review becomes a data point. Every response strengthens the customer relationship. Every interaction makes your entire customer.

If you're not putting your reviews on autopilot yet, you're missing revenue from every review. Your customers are talking. With Siena, you're finally ready to listen, respond, and learn at scale.

Ready to turn review management from time sink to competitive advantage? Let's talk.