Customer Support Agent

Customer support teams answer the same questions over and over. Password resets, feature explanations, billing inquiries, “how do I do X” – a significant chunk of support volume is tier-1 questions with well-documented answers. An AI support agent handles these instantly and consistently, freeing your team for problems that actually need a human.

The Problem

Support doesn’t scale linearly. Every new customer adds support load. Hiring more agents is expensive. Response times creep up. Quality becomes inconsistent – different agents give different answers to the same question. And your team spends their time on repetitive queries instead of complex issues where they add the most value.

Meanwhile, customers don’t want to wait. They don’t want to search your docs. They want an answer now.

How the Softcery Platform Solves It

Build a support agent that knows your documentation, answers instantly, maintains consistent quality through evaluations, and escalates gracefully when it can’t help.

Grounded in Your Docs

Upload your help center articles, product documentation, FAQ content, and troubleshooting guides. The platform processes everything into a searchable knowledge base. Your support agent answers from actual documentation – not hallucinated responses.

Add text sources for common questions that aren’t well-documented yet. Those questions your team answers in Slack channels? Capture them as knowledge and your agent handles them automatically.

Quality You Can Trust

Built-in evaluations run on every response:

• Factual accuracy (block) – If the agent makes something up, the response is blocked and replaced with a safe fallback. Users never see hallucinated support advice.
• Scope enforcement (warn) – If the agent strays outside its support scope, it’s flagged for review.
• Resolution quality (log) – Track whether responses actually resolve the customer’s issue.
• System safety checks – Prompt injection, content safety, and config extraction detection run automatically.

Your support agent’s quality is measured and enforced on every single response. Not through spot-checking, but systematically.

Graceful Escalation

Not every question has a simple answer. The Customer Support preset includes built-in escalation behavior – when the agent can’t help, it tells the customer exactly who to contact, how to reach them, and what information to have ready. No dead ends.

Configure your escalation paths in the behavior constraints: billing issues go to [email protected], technical issues to the engineering team, account questions to [email protected].

Full Transparency

Every response is inspectable. You can see which documentation was retrieved, what the model processed, which evaluations ran, and exactly why the agent said what it said. When something goes wrong (and it will occasionally), you can trace the exact chain of events and fix the root cause.

What It Looks Like in Practice

Customer: “How do I enable two-factor authentication?”

The agent retrieves your 2FA documentation, provides step-by-step instructions in a clear, concise format, and includes any relevant caveats (e.g., “backup codes are generated during setup – save these somewhere safe”).

Customer: “I was charged twice for my subscription”

The agent recognizes this is a billing issue it can’t resolve directly. Instead of trying to troubleshoot, it directs the customer to [email protected] with clear instructions: “Email [email protected] with your account email and the transaction dates. Our billing team typically responds within one business day.”

Customer: “Your product sucks, [Competitor] is way better”

The agent doesn’t engage with the comparison or get defensive. It acknowledges the frustration, asks what specific issue they’re experiencing, and focuses on helping them get value from the product they’re actually using.

Configuration Breakdown

Component	Setup
Behavior	Customer Support preset with your specific escalation paths and product context
Knowledge	Help center docs (website crawl), FAQ content (text), known issues (text)
Evaluations	Factual accuracy (block), scope enforcement (warn), resolution quality (log), no competitor discussion (block)
Channel	Embed widget on your help center / product, branded to match support experience
Model	Claude Haiku 3.5 for speed + cost efficiency, or Claude Sonnet 4 for complex technical products
Advanced	Temperature 0.3 (consistent answers), context messages 8 (maintain conversation thread)

Who This Is For

• SaaS companies with growing support volume and documented help centers
• E-commerce businesses handling shipping, returns, and product questions
• Any product team where tier-1 support is eating into time for complex issues

The Escalation Model

The AI agent handles tier-1 questions. Everything it can answer from the knowledge base, it answers. Everything it can’t, it escalates with context.

This isn’t about replacing your support team. It’s about letting them focus on problems that need human judgment, creativity, and empathy – while the AI handles “how do I reset my password” for the 50th time today.

Over time, reviewing the conversations the agent can’t handle reveals gaps in your documentation. Each escalation is a signal: either add it to the knowledge base, or it’s genuinely a human-tier problem. The agent gets smarter as you fill gaps.

Getting Started

1. Create an agent and choose the Customer Support preset
2. Add your help center as knowledge – sitemap mode works well for help centers
3. Set up evaluations – factual accuracy is mandatory for support
4. Build a full support bot with the detailed walkthrough