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AI AgentsAutomationSaaS

AI Customer Support Agent

Agent for a Subscription SaaS

Client

B2B subscription SaaS (confidential)

Duration

6 weeks (MVP → production)

Team

AI engineer, Full-stack engineer, QA, Product lead

Situation

Support volume had outgrown the team. Response times were slipping, and senior agents were spending too much time answering repeat questions. The client wanted an AI support agent that could resolve common issues safely—without hallucinations, leaking data, or breaking brand voice.

Objectives

  • Deflect repetitive tickets while keeping CSAT stable or improving
  • Keep humans in control for edge cases and billing-sensitive actions
  • Add strong privacy and security boundaries (PII-aware handling)
  • Provide measurable visibility: what the agent answered, why, and with what confidence

What We Did

A knowledge layer the model could trust

Consolidated help center articles and internal macros, added metadata, and created a "single truth" knowledge base with a deprecation process.

Retrieval + grounded responses (RAG)

The agent only answered from approved sources. If it couldn’t find support, it asked clarifying questions or escalated to a human with a structured summary.

Guardrails and human handoff

Implemented confidence scoring, refusal rules, redaction for sensitive fields (tokens, emails), and escalation routes based on intent.

Observability

Every answer logged with source articles used, prompt version, and outcome (resolved, escalated, reopened).

Challenges & Solutions

Hallucination risk

Solution: Required citations in every answer and blocked "free-form" responses when sources were weak.

Messy historical docs

Solution: Set up weekly doc reviews and ownership rules—support content became a maintained product asset.

Tone consistency

Solution: Created a small style guide and validated responses with support leads before launch.

Key Outcomes
  • 60% of incoming tickets handled end-to-end for top categories
  • Median first response time reduced from 4 hours to 5 minutes
  • Fewer "ping-pong" follow-ups due to better clarifying questions

Deliverables

  • AI agent (production) + admin controls
  • Knowledge ingestion pipeline + approval workflow
  • Monitoring dashboard for quality, safety, and deflection rate

Services Provided

AI agent buildKnowledge/RAGSupport workflow automationSecurity controls

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