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Interprefy is a global provider of live interpretation services. Demand for their solutions grew rapidly, and with it came a high-quality problem: too many inbound enquiries for the sales team to process efficiently.
Reps were spending more time sorting through unqualified leads than speaking with high-value prospects. Interprefy attempted to reduce noise by adding more qualification fields to their web forms, but this increased friction for prospects and conflicted with their friendly, supportive tone of voice. It also failed to deliver the structured information the sales team needed.
As enquiry volumes increased, the challenge shifted from operational to technical. Interprefy needed a more advanced method to capture, enrich and route inbound data within HubSpot. Standard forms and workflows could not support the level of qualification accuracy, data consistency or routing logic required.
A custom multi-system solution was needed to streamline qualification, protect the user experience and scale with future demand.
Insert any constraints Vani confirms — workflow limitations, volume handling issues, challenges with property mapping, etc.
Interprefy explored a new model for qualification: using an AI agent to manage early-stage discovery, while Huble supported CRM automation and HubSpot alignment. The goal was simple. Let AI handle the repetitive, structured work so the sales team could focus on meaningful conversations.
A short, frictionless web form captured inbound enquiries directly into HubSpot. Ask Breeze enriched the contact record using the “Tell us more about your inquiry” field, providing context that would later help the system identify mis-fit enquiries.
From there, Make.com launched automations immediately after a form was submitted. These automations triggered outbound AI phone calls through Vapi. Within minutes, the AI agent “Brad” contacted the prospect, explained Interprefy’s services and asked a structured set of qualifying questions. Responses were captured in real time.
Once each call ended, Vapi compiled the structured conversation data and full transcript, then sent them into n8n via webhook. n8n processed these inputs and updated the relevant HubSpot properties, creating a detailed record comparable to an SDR’s introductory qualification notes.
HubSpot remained the source of truth throughout the journey. Information flowed continuously between Make.com, Vapi and n8n, ensuring every contact record was enriched with accurate, timely and structured qualification data.
A streamlined form captured inbound data in HubSpot. The Ask Breeze integration enriched key properties using the open text field, helping identify mis-fit enquiries early.
If the call went unanswered, the system sent a follow-up email asking the same critical questions via a short form.
Interprefy’s Agentic AI Agent was made possible through the integration of a powerful technology stack, with each tool playing a vital role in automating and elevating the lead qualification process.
Interprefy’s Agentic AI Agent was powered by a coordinated stack of Vapi, n8n, Make.com, and HubSpot—tools that together transformed lead qualification from a manual process into a dynamic, real-time engagement channel. The system delivered instant, personalized responses to prospects while equipping the sales team with data-rich insights to confidently prioritize high-value opportunities.
The result was an AI-driven lead management solution that boosted efficiency and created a modern brand experience prospects remembered. Together, these tools formed a custom workflow where AI-generated insights were parsed, mapped, and written into HubSpot via n8n, enabling automated segmentation, routing, and follow-up workflows.
The journey began with HubSpot, where the website form captured inbound inquiries. Rather than burden prospects with endless qualification questions, the form was intentionally kept short—creating a smooth, user-friendly entry point into the sales pipeline.
“Huble’s team was invaluable during the pilot phase, helping optimize the HubSpot processes and ensuring smooth CRM integration with our AI solution.”
After two months of testing, the results from the AI-powered solution were impressive. Interprefy’s AI solution, supported by HubSpot automation, helped reduce the noise in the lead pipeline, enabling the sales team to focus on higher-quality leads with a greater likelihood of converting into customers. Moreover, leads were wowed and delighted by the experience of chatting with an AI Agent.
“We saw an immediate improvement in efficiency. Sales reps were spending less time sorting through irrelevant leads and more time working with high-value prospects. It was a relief for the team, and we saw conversion rates rise.”
“We’ve seen instances where conversations lasted much longer than expected (18 minutes), with people tending to forget that they’re interacting with a robot.”
The integration of AI with HubSpot provided a data-driven qualification system that improved efficiency at scale. Interprefy is now looking to scale and enhance the AI solution further—with Huble continuing to support CRM and automation alignment.
Near term:
“The beauty of this system is its adaptability. The more data we gather, the more insights we gain, allowing us to continuously refine the AI’s learning, adjust call scripts, and enhance its effectiveness. With each interaction, the system improves, ensuring it evolves to meet changing market demands.”
This pilot demonstrated the potential of combining AI-led engagement with CRM automation to streamline sales qualification. Here are the key takeaways from our journey:
As more companies begin to explore AI-driven sales solutions, Interprefy’s story provides a powerful example of how AI can enhance the sales process, empowering teams to be more effective, efficient, and focused on the right opportunities.
“By embracing AI, we took a calculated risk that paid off. The feedback from our sales team has been overwhelmingly positive, and the ability to focus on high-quality leads has transformed our sales process. We're excited to refine and scale the solution to meet future demands.”