The Quantum + AI Tech Show brings together people working on the practical adoption of emerging technologies across industry, government, research and infrastructure. Having companies in the room that are already applying AI to real business problems is an important part of that conversation.
Why we’re excited
Helperfy brings a practical perspective on how AI can become part of everyday business operations. Its AI technical support platform connects to a company’s live database, CRM, documentation and ticketing systems, allowing support teams to work with current, company-specific information.
For the Quantum + AI Tech Show, this is a valuable example of what applied AI looks like in practice. Much of the discussion around AI focuses on models and capabilities. The next stage is about integrating those capabilities into existing systems, workflows and teams, with the right approach to accuracy, security and human oversight.
Helperfy is working in this space. Its platform can automatically resolve technical support tickets, retrieve information from live systems and escalate requests to a human when the AI does not meet a defined confidence threshold. The platform also includes PII anonymisation, continuous quality assurance and an audit trail for each response.
This makes Helperfy a strong addition to the community we are building around Quantum + AI Insiders. The event is focused on real-world adoption, and we want the organisations involved to bring examples of technology being put to work today.
Who are Helperfy?
Helperfy is an AI technical support platform designed for teams that need accurate answers based on their own business data.
The platform connects with databases, CRM systems, documentation and ticketing platforms such as Zendesk, Jira, Salesforce, HubSpot, Intercom and ServiceNow. It combines retrieval-augmented generation with real-time data access, allowing the AI agent to work with information such as order status, account data, error logs, knowledge bases and previous support tickets.
Security and data handling are built into the platform. Names, email addresses and other identifiable information can be anonymised before data reaches an LLM, while confidence thresholds determine when a request should be passed to a human. Each response can also retain its sources, confidence level and review information for audit purposes.
Helperfy reports that up to 85% of tickets can be auto-resolved, with a median full response time of around three seconds. Its platform is designed to go into production within around two weeks, starting with a limited ticket queue and expanding once the results have been tested.
The company is also focused on the economics of AI deployment. Its token optimisation technology is designed to reduce inference costs, while predictive analytics can identify recurring issues and patterns in customer support data that may be useful for product teams.
Helperfy’s approach reflects an important part of the wider AI adoption landscape: making AI useful inside the systems businesses already rely on, while keeping data, quality, security and people in the process.