Drillbit

What

Drillbit is an AI operations and revenue automation platform for home service businesses, trades companies, franchisees, and franchisors. It is positioned as a hands-off system that manages customer-facing execution from lead capture through scheduling and payment collection, while working on top of an existing CRM rather than replacing it.

The core workflow described on the page covers inbound lead qualification, multichannel follow-up, appointment booking, use of technician calendar availability, re-engagement of past customers, and unpaid invoice collection. The product appears to be aimed at businesses that want to scale job volume and margins without adding call center headcount, training burden, or major process changes.

Features

• Inbound lead capture and qualification: Drillbit turns phone calls, website visits, paid leads, ads, and other inbound requests into structured leads and adds them to the CRM.
• Multichannel communication and scheduling: The AI agent texts, emails, and calls leads, then uses CRM data and technician calendars to help convert them into booked appointments.
• CRM-overlay deployment: The product is presented as working with existing systems, which reduces the need for a CRM migration or major retraining.
• Past-customer reactivation and opportunity mining: Drillbit uses historical customer data to identify upsell, cross-sell, and re-engagement opportunities that may create additional jobs.
• Invoice follow-up and collections: After work is completed, the system can send payment requests, follow up on unpaid invoices, and route funds to a connected bank account.
• Scale-oriented automation model: The platform is described as suitable for both single-location operators and franchise networks, with 24/7 AI handling intended to reduce missed opportunities and administrative workload.

Helpful Tips

• Verify workflow fit before rollout: For this type of platform, confirm how lead routing, calendar logic, collections steps, and exception handling match your existing field operations.
• Review CRM and data hygiene early: Because the product relies on existing systems and past customer data, cleaner records and standardized statuses will likely improve automation outcomes.
• Pilot on one service line or location first: A controlled rollout can help measure booking quality, operational impact, and staff handoff requirements before broader deployment.
• Assess brand and customer communication rules: If AI is handling calls, texts, and emails, define tone, escalation rules, and disclosure practices to align with your customer experience standards.
• Treat performance claims as case-specific: The page includes strong revenue and margin outcomes, but buyers should validate expected results against their own lead mix, seasonality, and service economics.