Solidroad

What Solidroad does

Solidroad is an AI-native quality assurance and training platform designed for modern customer support teams. It automatically evaluates 100% of customer interactions across human and AI agents, identifying risks, skill gaps, and triggering personalized coaching in real-time. The platform provides complete visibility into customer interactions across various channels like phone, live chat, video, and email. Solidroad's AI model is trained on a team's real conversations, policies, and scorecards to ensure scoring aligns with their specific voice, workflows, and expectations. It helps scale QA coverage from 1% to 100%, identifies high-risk interactions, and automates coaching tasks to improve agent performance and accelerate time to proficiency.

Products

• Auto QAAutomated Quality Assurance that scores 100% of interactions, surfaces issues, and routes targeted training. It provides complete visibility across channels, flags high-risk issues for review, and helps improve support agent performance.
• Coaching & FeedbackDelivers personalized feedback automatically and creates lifelike customer support simulations. It allows for precise performance evaluation and automates tedious coaching tasks like role-plays and transcript reviews.
• Training SimulationsBuilds lifelike simulations across every channel (chat, email, phone, video) with realistic personas and backend tools that mirror the support environment. It evaluates performance against custom rubrics and helps agents practice operational precision.
• AI EvaluationScores every AI interaction automatically, catches errors and hallucinations before they reach customers, and uses findings to refine AI models. It provides visibility into AI-generated responses and flags high-risk AI responses instantly.

Key capabilities

• Automated evaluation of 100% of customer interactions
• Identification of risk and skill gaps
• Real-time personalized coaching
• Visibility across phone, live chat, video, and email support
• Customizable AI model trained on specific conversations, policies, and scorecards
• Scaling QA coverage from 1% to 100%
• Pattern detection and scoring logic for high-risk interactions
• AI simulations for agent coaching
• Automated scoring of simulations
• Personalized coaching insights
• Automation of manual coaching tasks (role-plays, transcript reviews, written feedback)
• Realistic, dynamic simulations for agent practice
• Generation of realistic scenarios across personas, support channels, difficulty levels, and languages
• Mirroring and training on agents' support stack and workflows
• Automated scoring of AI-generated responses
• Flagging of high-risk AI responses
• Integration with CRM and Support tools
• Integration with AI Support Agents (Decagon, Sierra, Fin)
• Integration with Knowledge Management platforms (Guru, Notion)
• ISO 27001:2022 compliance
• SOC 2 compliance
• Single Sign-On (SSO) support
• Data encryption at rest
• Established data retention, classification, and deletion policies

Use cases

• Automated quality assurance for customer support interactions
• Identifying skill gaps in customer support agents
• Triggering personalized coaching for agents
• Reviewing 100% of customer interactions in seconds
• Generating custom trainings for agents
• Coaching reps with AI simulations
• Improving customer satisfaction (CSAT)
• Reducing average handling time (AHT)
• Validating candidate quality at scale in hiring processes
• Achieving consistent quality measurement across global teams
• Evaluating performance of AI agents
• Catching errors and hallucinations in AI agents
• Refining AI models with targeted feedback
• Onboarding new customer support agents
• Continuous performance improvement for customer support teams
• Ensuring compliance with customer interaction policies
• Reducing interview time in recruitment
• Auditing candidate quality in hiring

AI approach

Solidroad uses AI to automate quality assurance and training for customer support teams. Their AI model is trained on customer conversations, policies, and scorecards to score interactions, identify high-risk issues, and generate personalized coaching and simulations. They also use AI to evaluate the performance of other AI agents.

Tech named: AI model, Pattern detection, Scoring logic

Industries served

• Software Development
• Customer Support
• Airlines
• Financial Services

What it says sets it apart

• AI-native platform built for modern customer support teams
• Automatically evaluates 100% of customer interactions (human and AI agents)
• Surfaces risk and identifies skill gaps in real-time
• Triggers personalized coaching automatically
• Built to fit existing tech stacks with various integrations
• AI model trained on specific conversations, policies, and scorecards for tailored QA
• Scales QA coverage from 1% to 100% (no sampling, no backlog)
• Automates tedious coaching tasks, freeing up trainers for higher-impact development
• Provides realistic, dynamic AI simulations for agent practice and readiness verification
• Offers consistent quality measurement across global teams
• Validates candidate quality at scale, cutting hiring time
• Scores AI agent interactions to catch errors and hallucinations before they reach customers
• Certified to industry standards: ISO 27001:2022 and SOC 2 compliant

Funding rounds we track

From the AI funding tracker — rounds as reported by the linked publications.