InTouchNow has raised £2.3m in seed funding to expand artificial-intelligence voice technology already being used by more than 150 GP practices to handle patient calls and routine administration.
The round was led by Ada Ventures, with participation from Exceptional Ventures and Kadmos Capital. The funding will support further product development and expansion of the company’s technology across UK primary care.
InTouchNow provides voice agents designed specifically for general practice. The system can answer calls around the clock, book and change appointments, collect triage information, process routine administrative requests, and direct clinical or more complex issues to practice staff.
The company says its system typically resolves between 50% and 70% of calls without human intervention. Patients are told when they are speaking to AI and can request a human receptionist, while frustration detection can also trigger escalation.
The operating problem is significant. Telephone access remains one of the most visible sources of pressure in general practice, particularly during morning demand peaks when reception teams must handle appointments, prescription queries, triage information, administration, and patients needing more complex support.
Independent analysis cited by InTouchNow examined NHS cloud-telephony data from 18 practices covering 240,000 registered patients. Following deployment, the proportion of calls answered increased from 55.9% to 65.6%, while calls answered within two minutes rose from 50.7% to 67%.
Mean waiting time fell by 32%, from 181 seconds to 123 seconds. One Surrey practice was reported to have cleared its telephone queue and returned 411 hours of reception-team time over four months.
Daniel Park, founder of InTouchNow, said: “InTouchNow was built to handle the repetitive, time-consuming calls so reception teams can focus on the patients who really need a person.”
The business began as a human-led call-centre operation serving GP practices in 2019 before moving into voice AI. That background gives the company experience of the workflows it is attempting to automate rather than approaching primary care solely as a software market.
Healthcare is becoming an important test of applied AI because the potential productivity gains are large while tolerance for poor governance or inaccessible services is low. Administrative automation can release staff time, but deployments must also address patient privacy, record accuracy, accessibility, escalation, language, and clear boundaries around clinical judgement.
The UK is already using AI procurement programmes to target operational NHS problems, part of a wider shift from general experimentation towards systems intended to deliver measurable service improvements.
Voice technology has a particular advantage in primary care because it can operate through a channel patients already use. It does not require a new application or portal, potentially making it more accessible to people who struggle with digital interfaces.
That familiarity also raises expectations. Patients may assume a voice system can provide clinical advice when its intended role is administrative, making transparent disclosure, escalation, and task boundaries essential to safe operation.
Practices must also understand how call data are handled, how information enters clinical systems, how errors are identified, and where responsibility sits when automated workflows interact with patient records.
The commercial case for InTouchNow rests on taking repetitive demand away from reception teams while retaining human support where judgement, reassurance, or clinical escalation is required. Scaling from more than 150 practices will test whether that balance can be maintained across organisations with different populations, staffing models, telephony systems, and workflows.
The investment reflects a broader shift in AI funding towards products attached to measurable operating problems. In primary care, the benchmark is unlikely to be model sophistication alone; deployment will be judged on whether patients get through more easily, staff recover useful time, and service quality remains reliable as automation expands.
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