# Case Study: Ideal

**IDEAL automates 24 / 7 Tier-1 support with raia’s AI Agentic Workforce**

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**Snapshot**

|                      | Before raia               | After raia                                 |
| -------------------- | ------------------------- | ------------------------------------------ |
| First-response time  | 2-4 h during office hours | **<60 s, 24 / 7 live-chat**                |
| Ticket resolution    | 0 % automated             | **50 % solved end-to-end by AI**           |
| Agent triage quality | Manual note-taking        | AI pre-diagnoses remaining 50 % for humans |
| Staffing demand      | Team capped at 10 reps    | AI output ≈ **5 FTEs** worth of capacity   |

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#### 1 | Company & Challenge

**IDEAL**, a Constellation Software business unit, provides vertical ERP and point-of-sale software to hundreds of equipment dealers across North America. A growing catalogue of products and always-on dealerships drove three pain points:

1. **Night-time & weekend queries** that waited hours for a response.
2. **Fragmented knowledge** spread over 10 k support articles plus thousands of historical tickets.
3. Rising ticket volume outpaced the Tier-1 team’s headcount budget.

IDEAL needed an always-available support channel that could surface precise answers from deep product documentation and integrate with its existing ticketing stack.

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#### 2 | Why IDEAL chose raia

* **Launch Pad & Vector Store** ingest large knowledge bases in minutes and index them for semantic search, turning 10 k Markdown articles and legacy transcripts into AI-ready context .
* **CoPilot human-feedback loop** lets support reps rate and correct answers during pilot mode, rapidly improving accuracy .
* **Live-chat skill out-of-the-box** meant zero custom code to embed chat on IDEAL’s customer portal .

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#### 3 | Solution Design

| AI Agent                 | Role                                                                                               | Key Integrations                         |
| ------------------------ | -------------------------------------------------------------------------------------------------- | ---------------------------------------- |
| **Tier-1 Support Agent** | Resolve common “how-to”, licensing and configuration questions via live-chat; escalate edge-cases. | Knowledge Base Vector Store, Zendesk API |
| **Copilot Shadow Mode**  | Used internally for 90 days to draft answers and collect thumbs-up / corrections.                  | CoPilot feedback UI                      |

**Deployment timeline**

1. **Week 1-2 – Data prep**: Content engineering team cleaned and bulk-converted articles & tickets to Markdown, then uploaded to Launch Pad .
2. **Week 3 – Pilot in CoPilot**: Support reps used AI-drafted responses inside Zendesk; feedback loop refined prompts & gaps.
3. **Week 12 – Public go-live**: Chat widget released to all customers.

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#### 4 | Measurable Impact (90 days post-launch)

* **50 % of inbound tickets fully resolved by AI**—equal to five full-time agents.
* **100 % of remaining tickets pre-diagnosed**, with reproduction steps and knowledge-article links attached, cutting triage time by 40 %.
* **Customer CSAT +12 points** (4.1 → 4.6) driven by instant answers after hours.
* **Ops saving:** \~$350 k annualised labour and overtime costs.

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#### 5 | Lessons for Prospective Clients

1. **Start in shadow mode.** CoPilot let IDEAL iterate safely before exposing customers to AI, accelerating trust and quality .
2. **Invest in knowledge hygiene.** Converting legacy PDFs & transcripts to clean Markdown ensured high-precision retrieval .
3. **Let AI triage, not just solve.** Even unsolved tickets reached human reps with contextual breadcrumbs, boosting Tier-2 productivity.

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#### 6 | What’s Next

* Expand the Agent to proactive **in-app guidance** (surfacing tips based on user behaviour).
* Add a **billing & licensing Pack** so AI can execute licence upgrades without human touch.
* Integrate sentiment analytics to flag at-risk accounts for success managers.

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#### 7 | Key Takeaway

IDEAL’s experience shows that **raia turns sprawling support knowledge into a self-service frontline**, delivering round-the-clock answers, happier customers and a 50 % reduction in human ticket load—all within a single quarter.

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