Solidroad Raised $25M For Its Solidroad AI-driven QA Platform
Edited by Adam Harrie — April 28, 2026 — Tech
This article was written with the assistance of AI.
References: prnewswire & thenextweb
Solidroad launched an AI-driven QA (quality assurance) platform for customer support teams, created by Intercom alumni Mark Hughes and Patrick Finlay. The San Francisco and Dublin startup raised $25 million to apply automated scoring and analysis to 100% of voice, chat and email interactions, featuring end-to-end review designed to surface agent coaching opportunities.
The platform ingests transcripts and recordings, scores conversations against client rubrics, highlights performance patterns and generates coaching prompts and onboarding metrics. Customers named in the round include Ryanair, Crypto.com and Oura, and Solidroad holds SOC 2 and ISO 27001 certifications to meet enterprise security requirements.
This matters because traditional QA sampled only 1%–3% of interactions, leaving most performance unseen; Solidroad’s approach gives contact centers full visibility that can shorten onboarding, raise CSAT and systematize agent development. As AI handles more frontline tasks, comprehensive QA becomes essential to maintain service quality.
Image Credit: Solidroad
The platform ingests transcripts and recordings, scores conversations against client rubrics, highlights performance patterns and generates coaching prompts and onboarding metrics. Customers named in the round include Ryanair, Crypto.com and Oura, and Solidroad holds SOC 2 and ISO 27001 certifications to meet enterprise security requirements.
This matters because traditional QA sampled only 1%–3% of interactions, leaving most performance unseen; Solidroad’s approach gives contact centers full visibility that can shorten onboarding, raise CSAT and systematize agent development. As AI handles more frontline tasks, comprehensive QA becomes essential to maintain service quality.
Image Credit: Solidroad
AI QA for Customer Support: Usage and Adoption
Helps decide whether to adopt AI-driven QA, switch QA vendors, or expand QA coverage in the next 1–2 weeks.
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How often do you review support interactions for QA today?
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How likely are you to try AI-based QA scoring in the next 2 weeks?
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Which would you be more likely to use next for improving agent coaching?
Trend Themes
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Comprehensive AI QA — Full visibility across 100% of voice, chat and email interactions enables systematic identification of performance gaps previously hidden by sampling.
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Automated Interaction Scoring — By converting transcripts and recordings into rubric-based scores, platforms can quantify agent performance and surface consistent coaching signals at scale.
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Coaching-driven Analytics — The synthesis of performance patterns and generated coaching prompts creates a data-rich feedback loop that can shorten onboarding and improve CSAT metrics.
Industry Implications
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Contact Center Operations — Contact centers stand to be reshaped by continuous, automated QA workflows that provide granular insight into agent behavior and customer outcomes.
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Enterprise Security and Compliance — SOC 2 and ISO 27001–aligned QA platforms introduce opportunities for secure, auditable handling of sensitive interaction data across regulated customers.
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HR Learning and Development — Learning teams can leverage interaction-derived metrics to build competency-based training paths and measure the impact of coaching on agent progression.
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