Duckie
AI support agents that resolve tickets end to end. Duckie handles customer support autonomously, learning from your knowledge base to deliver instant, accurate responses 24/7.
About Duckie
Duckie lets customer support teams build their own AI agents in minutes!
With Duckie, support teams can translate their tasks and processes into predictable and reliable AI workflows that saves them time and money. Folks use Duckie to handle a wide range of use cases, from answers customers technical questions to processing refunds, and everything in between.
Products
The agentic platform for support teams to build AI agents that resolve tickets, investigate issues, and automate workflows behind support.
What customers say
“Being able to use the assistant to create things like runbooks, guidelines, and guardrails, and troubleshoot specific runs has made things quite a bit easier.”
“Managing the support team used to be about managing humans. Now it's about being someone who can manage an AI system.”
“Anyone can hop on Claude and try to build a chatbot. But to build one that's actually a full system like this? I don't think that's realistic as a one-man job at home.”
Grid uses Duckie to investigate payment ledgers, handle cancellations and answer account questions using live backend data. Duckie's case study reports 90% inquiry resolution across more than 70,000 monthly tickets and…
Case studyMedtelligent uses Duckie with Zendesk to build support workflows and configure sensitive-data handling. Duckie's case study reports workflow setup taking at most 30 minutes, compared with four to five hours using Zendesk…
Case studyAbbiamo uses an embedded Duckie widget for support, API integration questions and escalations to Linear. Duckie's case study reports that customer onboarding fell from over two months to just over four weeks.
Case study
Security and compliance
As reported by Duckie. Ask for audit reports before you buy.
- SOC 2In progress
- TLS for data transmission
- Encryption at rest
- Multi-factor authentication (MFA) for all employee remote access
- Principle of least privilege access controls
- Role-based access control (RBAC)
- Access deprovisioning within 24 hours of employee departure
- Customer data not accessible from public internet
- Siloed data storage per customer environment
- Network IDS/IPS in production
- Database logging and auditing
- Access Control Lists (ACLs)
- IAM policies in production
- Monitoring and alerting systems
- Backup and recovery procedures
- Quarterly vulnerability assessments
- Annual penetration testing
- OWASP secure development guidelines
- Automated security testing in CI/CD pipeline
- Disaster recovery plan with multiple US-based failover sites
- Regular data backups and failover procedures
- Security incident and breach response plan
- Customer email notification for security incidents
- Zero-day data retention policy with OpenAI
- Anthropic does not use customer data for training
- AWS Bedrock zero-retention policy option
- No personal data used to train LLMs across any deployment option
- Open-source models do not share data with third parties
- Self-hosted deployment option with data sovereignty
- Dedicated administrative web interface for customer data management
- Custom LLM model endpoint support in self-hosted deployment
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