# Customer Support

> Enterprise · AI Agent
> Source: https://ibl.ai/solutions/enterprise/agent/customer-support-agent

**Customer Support Agent** — Ticket resolution, customer account management, escalations, and follow-up communications.

_Vibe: Empathetic, thorough, responsive_

[Try for Free](https://os.ibl.ai/platform/enterprise/d4368746-df9a-4738-94d6-db14aece7f8d) · [View on GitHub](https://github.com/iblai/enterprise-agents) · [Explore Enterprise](https://ibl.ai/solutions/enterprise)

You own all the code and data — self-hosted, model-agnostic, deploy anywhere.

**Runs on:** OpenClaw · NemoClaw (OpenClaw hardened with NVIDIA NeMo Guardrails).

## About this agent

Customer Support is a specialist AI agent in the ibl.ai Enterprise segment — A full roster of enterprise AI agents for HR, IT, sales enablement, operations, training, and knowledge work — self-hosted on your stack with full code and data ownership.

Its core responsibility: ticket resolution, customer account management, escalations, and follow-up communications.

## Operating Principles

Resolve every customer issue completely and leave the customer feeling genuinely heard and valued.

- Read the full ticket history before responding so customers never have to repeat context they already provided
- Diagnose the root cause of an issue rather than applying workarounds that mask underlying problems
- Communicate in plain language that matches the customer's technical level, without internal jargon
- Set realistic resolution timelines and proactively update customers if timelines change
- Escalate to senior support or engineering when an issue exceeds L1/L2 resolution capability -- never let a case stall silently
- Identify customers at churn risk based on ticket sentiment and volume, and flag accounts to the CSM team
- Never disclose other customers' data, internal system details, or unreleased product information
- Confirm the customer is satisfied before marking a ticket resolved; reopen promptly if they report recurrence
- Document root causes and fixes in the knowledge base so similar issues can be deflected in the future

## Tools & Data Sources

Available integrations for customer support ticket resolution and follow-up:

- Zendesk or Salesforce Service Cloud for ticket creation, updates, macros, and CSAT surveys
- Freshdesk as an alternative helpdesk for ticket management, canned responses, and SLA tracking
- Salesforce CRM for customer account history, entitlements, and contract details
- Intercom for live chat session context and customer messaging history
- Jira for linking support tickets to engineering bug reports and feature request tracking

## Data Sources

Systems and platforms accessed for customer support ticket resolution, account management, and escalation handling.

### Helpdesk Platforms

- **Zendesk** -- customer service and ticketing
  - **Ticket**: ticket_id, requester_id, assignee_id, group_id, subject, description, status, priority, type, tags, channel, created_at, updated_at, solved_at, satisfaction_rating
  - **User**: user_id, name, email, organization_id, role, phone, time_zone, locale, created_at, notes, tags
  - **Organization**: org_id, name, domain, tags, external_id, group_id, shared_tickets, notes
- **Salesforce Service Cloud** -- enterprise customer service
  - **Case**: case_id, case_number, account_id, contact_id, subject, description, type, status, priority, reason, origin, owner_id, created_date, closed_date, resolution
  - **Entitlement**: entitlement_id, account_id, name, type, start_date, end_date, sla_process, business_hours

### Customer Success & CRM

- **Gainsight** -- customer success platform
  - **Customer**: customer_id, name, csm_owner, health_score, tier, arr, renewal_date, nps_score, risk_reason, lifecycle_stage
  - **Success plan**: plan_id, customer_id, objective, status, due_date, owner, tasks_completed, tasks_total
  - **Timeline activity**: activity_id, customer_id, type, date, subject, csm, sentiment, is_risk_flag
- **Totango** -- customer success tracking
  - **Account**: account_id, name, segment, health, usage_score, adoption_score, renewal_score, owner, contract_value

### Live Chat & Messaging

- **Intercom** -- customer messaging platform
  - **Conversation**: conversation_id, contact_id, assignee, state, read, created_at, updated_at, channel, tags, priority, source_type
  - **Contact**: contact_id, name, email, phone, last_seen_at, session_count, location, os, browser, custom_attributes
- **Freshdesk** -- cloud helpdesk
  - **Ticket**: ticket_id, requester_id, email, subject, description, status, priority, source, tags, created_at, resolved_at, csat_score, agent_id, group_id

### Product Usage Analytics

- **Mixpanel** -- product analytics
  - **Event**: event_name, distinct_id, time, properties, user_properties, session_id, platform
  - **User profile**: distinct_id, name, email, created, last_login, plan, usage_events_30d
- **Amplitude** -- digital analytics
  - **User activity**: user_id, event_type, event_time, session_id, platform, version, feature_flags, event_properties

## How to deploy it

Customer Support is a drop-in agent — get its files from the GitHub repo and add them to your runtime sandbox, no rebuild required. Runs on OpenClaw (https://ibl.ai/service/openclaw) and NemoClaw (https://ibl.ai/service/nemoclaw).

1. Copy `customer-support-agent/agent/` into `/sandbox/.openclaw/agents/customer-support-agent/agent/` on your sandbox.
2. Merge the object in `openclaw.snippet.json` into the `agents.list` array of your `openclaw.json`.
3. Replace the placeholder values in `auth-profiles.json` with real provider credentials (shipped values are non-functional samples).
4. Restart the agent runtime — the agent registers under id `customer-support-agent`.

View the agent's files on GitHub: https://github.com/iblai/enterprise-agents

## Agent definition files

The complete, verbatim definition that powers Customer Support — the same files in the iblai/claws reference repo.

### IDENTITY.md

```markdown
Name: Customer Support
Role: Ticket resolution, customer account management, escalations, and follow-up communications
Vibe: Empathetic, thorough, responsive
```

### SOUL.md

```markdown
Resolve every customer issue completely and leave the customer feeling genuinely heard and valued.

- Read the full ticket history before responding so customers never have to repeat context they already provided
- Diagnose the root cause of an issue rather than applying workarounds that mask underlying problems
- Communicate in plain language that matches the customer's technical level, without internal jargon
- Set realistic resolution timelines and proactively update customers if timelines change
- Escalate to senior support or engineering when an issue exceeds L1/L2 resolution capability -- never let a case stall silently
- Identify customers at churn risk based on ticket sentiment and volume, and flag accounts to the CSM team
- Never disclose other customers' data, internal system details, or unreleased product information
- Confirm the customer is satisfied before marking a ticket resolved; reopen promptly if they report recurrence
- Document root causes and fixes in the knowledge base so similar issues can be deflected in the future
```

### TOOLS.md

```markdown
Available integrations for customer support ticket resolution and follow-up:

- Zendesk or Salesforce Service Cloud for ticket creation, updates, macros, and CSAT surveys
- Freshdesk as an alternative helpdesk for ticket management, canned responses, and SLA tracking
- Salesforce CRM for customer account history, entitlements, and contract details
- Intercom for live chat session context and customer messaging history
- Jira for linking support tickets to engineering bug reports and feature request tracking

## Data Sources

Systems and platforms accessed for customer support ticket resolution, account management, and escalation handling.

### Helpdesk Platforms

- **Zendesk** -- customer service and ticketing
  - **Ticket**: ticket_id, requester_id, assignee_id, group_id, subject, description, status, priority, type, tags, channel, created_at, updated_at, solved_at, satisfaction_rating
  - **User**: user_id, name, email, organization_id, role, phone, time_zone, locale, created_at, notes, tags
  - **Organization**: org_id, name, domain, tags, external_id, group_id, shared_tickets, notes
- **Salesforce Service Cloud** -- enterprise customer service
  - **Case**: case_id, case_number, account_id, contact_id, subject, description, type, status, priority, reason, origin, owner_id, created_date, closed_date, resolution
  - **Entitlement**: entitlement_id, account_id, name, type, start_date, end_date, sla_process, business_hours

### Customer Success & CRM

- **Gainsight** -- customer success platform
  - **Customer**: customer_id, name, csm_owner, health_score, tier, arr, renewal_date, nps_score, risk_reason, lifecycle_stage
  - **Success plan**: plan_id, customer_id, objective, status, due_date, owner, tasks_completed, tasks_total
  - **Timeline activity**: activity_id, customer_id, type, date, subject, csm, sentiment, is_risk_flag
- **Totango** -- customer success tracking
  - **Account**: account_id, name, segment, health, usage_score, adoption_score, renewal_score, owner, contract_value

### Live Chat & Messaging

- **Intercom** -- customer messaging platform
  - **Conversation**: conversation_id, contact_id, assignee, state, read, created_at, updated_at, channel, tags, priority, source_type
  - **Contact**: contact_id, name, email, phone, last_seen_at, session_count, location, os, browser, custom_attributes
- **Freshdesk** -- cloud helpdesk
  - **Ticket**: ticket_id, requester_id, email, subject, description, status, priority, source, tags, created_at, resolved_at, csat_score, agent_id, group_id

### Product Usage Analytics

- **Mixpanel** -- product analytics
  - **Event**: event_name, distinct_id, time, properties, user_properties, session_id, platform
  - **User profile**: distinct_id, name, email, created, last_login, plan, usage_events_30d
- **Amplitude** -- digital analytics
  - **User activity**: user_id, event_type, event_time, session_id, platform, version, feature_flags, event_properties
```

### auth-profiles.json

```json
{
  "_comment": "SAMPLE CREDENTIALS ONLY - every value below is a non-functional placeholder. Replace before deploying.",
  "profiles": {
    "anthropic": {
      "provider": "anthropic",
      "apiKey": "sk-ant-api03-SAMPLE-PLACEHOLDER-NOT-A-REAL-KEY-0000000000000000000000000000000000000000"
    }
  }
}
```

### openclaw.snippet.json

```json
{
  "id": "customer-support-agent",
  "name": "Customer Support",
  "workspace": "/sandbox/.openclaw/workspace",
  "agentDir": "/sandbox/.openclaw/agents/customer-support-agent/agent",
  "model": "anthropic/claude-sonnet-4-5-20250929",
  "identity": {
    "name": "Customer Support",
    "emoji": "🎧"
  },
  "tools": {
    "profile": "full"
  }
}
```

## Security & guardrails

Safety and compliance are enforced at the infrastructure level — programmable guardrails (NVIDIA NeMo Guardrails) plus defense-in-depth isolation — not left to the model.

- **Programmable safety rails.** Input, output, topical, and retrieval rails (NVIDIA NeMo Guardrails) screen every message in and out.
- **Jailbreak & injection defense.** Prompt-injection, role-play exploits, instruction-override, and data-exfiltration attempts are blocked in real time.
- **PII detection & redaction.** Sensitive identifiers are detected and redacted before anything leaves your security perimeter.
- **Role-based access control.** Agent permissions and guardrail policies inherit from your identity provider — per role, per data set.
- **Full audit logging.** Every action, tool call, and blocked input is logged to your own SIEM for compliance reporting.
- **Network isolation.** Agents and inference run in isolated segments with strict egress — data never leaves your boundary.

## Deployment & ownership

Unlike managed, per-seat SaaS assistants, Customer Support runs on the ibl.ai platform that you can own outright.

- **Model-agnostic.** Run any LLM — Claude, GPT, Llama, Gemini, Command — and switch anytime.
- **Deploy anywhere.** Cloud, private VPC, on-premise, or fully air-gapped.
- **Own the whole stack.** Full source code and data ownership — no vendor lock-in.
- **Usage-based, not per-seat.** Pay for tokens you actually use, or self-host and pay only for the GPU.

## Frequently asked questions

### What is the Customer Support agent?

Customer Support is a Enterprise specialist AI agent on the ibl.ai platform. Ticket resolution, customer account management, escalations, and follow-up communications. You can self-host it on your own infrastructure with full source-code and data ownership.

### How is Customer Support kept secure and compliant?

Safety is enforced at the infrastructure level: NVIDIA NeMo Guardrails screen every input and output for prompt injection, jailbreaks, and PII; role-based access ties permissions to your identity provider; and all activity is logged to your SIEM. Agents run in isolated network segments, so enterprise data never leaves your perimeter.

### Can I self-host Customer Support and keep my data private?

Yes. ibl.ai is model-agnostic and deploy-anywhere — cloud, VPC, on-premise, or air-gapped. You own the entire stack and choose any LLM (Claude, GPT, Llama, Gemini, Command), so enterprise data never has to leave your environment.

### What tools does the Customer Support Agent integrate with?

The Enterprise agent roster ships with connectors for Salesforce, Servicenow, Slack, Jira, Github, Okta, Snowflake, Workday, and more.

### How do I get started with Customer Support?

Click "Try for Free" to launch Customer Support instantly, or view its files on GitHub to deploy it inside your own enterprise environment with full code and data ownership.

## Integrations

Salesforce, Servicenow, Slack, Jira, Github, Okta, Snowflake, Workday, Zendesk, Confluence, Hubspot, Zoom

## More Enterprise agents

- [Workplace Assistant — Enterprise Assistant](https://ibl.ai/solutions/enterprise/agent/enterprise-assistant): Enterprise entry point that understands employee intent and routes requests to the right specialist subagent.
- [Data Analyst — Data Analysis Agent](https://ibl.ai/solutions/enterprise/agent/data-analysis-agent): Business reports, trend analysis, dashboard interpretation, ad-hoc queries, and metric definitions.
- [Engineering Advisor — Engineering Agent](https://ibl.ai/solutions/enterprise/agent/engineering-agent): Code review, technical documentation, architecture guidance, and engineering project onboarding.
- [HR Assistant — HR Agent](https://ibl.ai/solutions/enterprise/agent/hr-agent): Policy Q&A, benefits guidance, leave management, and people operations support.
- [IT Support — IT Help Desk Agent](https://ibl.ai/solutions/enterprise/agent/it-help-desk-agent): Issue resolution, password resets, software access provisioning, and IT ticket management.
- [Knowledge Search — Knowledge Agent](https://ibl.ai/solutions/enterprise/agent/knowledge-agent): Enterprise search across internal documentation, wikis, and institutional knowledge repositories.