CoachQA extends that AI workforce into quality assurance and risk oversight, enabling institutions to evaluate 100% of customer interactions against their own standard operating procedures.
Posh has announced the launch of CoachQA, a foundational component of its Agentic AI Workforce, a unified suite of AI agents serving customers and employees across the enterprise.
Designed specifically for banks, credit unions, and financial services, CoachQA extends that AI workforce into quality assurance and risk oversight, enabling institutions to evaluate 100% of customer interactions against their own standard operating procedures.
For most financial institutions, quality assurance still relies on manual sampling. Managers review a small percentage of calls, often less than 1% of total volume, and use that limited visibility to assess compliance gaps, fraud exposure, coaching opportunities, and operational performance, including sales effectiveness.
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The majority of interactions, typically over 99%, go unexamined.
“Financial institutions are making high-stakes decisions about compliance, risk, and customer experience based on extremely incomplete information,” said Karan Kashyap, CEO of Posh.
“CoachQA introduces continuous, AI-powered oversight, ensuring every conversation is evaluated against the standards that matter to each institution.”
John Miller, Vice President, Call Centre Operations & Strategy at Citadel Credit Union, said, “Traditional quality assurance has often felt disconnected from Net Promoter Score results. When only a small fraction of calls can be reviewed, it becomes difficult to determine whether service quality is truly being measured.”
“Posh CoachQA changes that by using AI and call transcriptions to analyse far more interactions, allowing organisations to directly connect agent performance to how members actually experience service.”
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From Sampling to Continuous Oversight
CoachQA serves as the oversight and governance agent within Posh’s Agentic AI Workforce.
Unlike traditional QA tools that rely on static scorecards, keywords, or generic scoring models, CoachQA dynamically retrieves and applies each institution’s own SOPs, scripts, compliance requirements, and best practices to every interaction.
At the core of the platform is a novel technique that Posh calls Retrieval-Augmented Evaluation (RAE). RAE analyses each conversation for salient topics, identifies relevant institutional standards, retrieves applicable procedures, and evaluates the interaction against those criteria.
The result is a structured, auditable evaluation aligned to how the institution actually operates, not a one-size-fits-all framework layered on top.
Compared to alternative QA solutions that are not purpose-built for financial services and tend to operate at a surface level, CoachQA leverages fine-tuned reasoning models (LLMs) to power “deep QA” at scale.
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Five Critical Oversight Functions in One Platform
CoachQA consolidates multiple oversight responsibilities into a single governed system:
- Detecting compliance gaps before audit exposure
- Flagging fraud and social engineering attempts
- Surfacing missed revenue opportunities at scale
- Delivering institution-specific coaching grounded in actual SOP adherence
- Providing voice-of-the-customer trend intelligence across 57+ categories
For contact centre leaders, this shifts QA from retrospective sampling to proactive risk management and performance optimisation. CoachQA includes real-time anomaly detection and alerting to ensure managers and leaders stay proactively informed across 100% of interactions.
Even the highest-performing agents have calls where they could have done better. Like elite athletes who still benefit from coaching, even the most tenured and top-producing reps will have interactions, spread across hundreds of calls, where an opportunity was missed or a best practice wasn’t followed.
Because CoachQA evaluates every interaction rather than a random sample, it surfaces those moments regardless of an agent’s seniority or track record, making it a valuable tool for developing the entire team, not just underperformers.
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Engineered for Regulated Financial Environments
CoachQA was built with governance and security as foundational design principles. The platform includes:
Data Protection Controls
- Zero PII persistence with automatic redaction
- Encryption at rest and in transit
Governance & Auditability
- Full audit trails for every score, flag, and AI-generated recommendation
- SOC 2 architecture
Operational Integration
- CCaaS-agnostic deployment with no rip-and-replace required
“Continuous oversight is no longer optional in financial services,” said Kashyap. “As AI advances, institutions need infrastructure that strengthens governance, not increases complexity. CoachQA delivers visibility, accountability, and scale in one unified system.”
Changing the Economics of Quality Assurance
People are among a financial institution’s largest expenses and most valuable assets. Banks and credit unions invest heavily in hiring, onboarding, training, and retaining their agents. CoachQA is designed to maximise the return on that investment, improving coaching outcomes, reducing fraud exposure and regulatory fines, and driving measurable revenue growth across the contact centre.
“Posh’s QA tool empowers us to monitor every member interaction, ensuring every experience is consistent and exceptional. With expanded oversight, we can quickly identify emerging trends and respond proactively to meet our members’ evolving needs.”
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“Access to more data and quicker insights drives smarter decisions, helping us raise the bar for member satisfaction,” said Stephanie Harney, SVP Member Experience at Chartway Credit Union.
By automating evaluation across 100% of interactions, CoachQA reduces the operational burden of manual review while expanding visibility into compliance, fraud detection, and revenue performance.
For every 20 agents in a contact centre, the platform can generate an estimated $1.9 million in annual value through automating (at total scale) manual review time alone, excluding incremental revenue lift and risk mitigation impact.
More importantly, executives gain confidence that performance and risk decisions are grounded in complete data, not just random samples.
Connecting Oversight to Continuous Improvement
CoachQA is a core component of Posh’s Continuous Learning Cycle.
While CoachQA evaluates live interactions and surfaces institutional performance gaps, the Posh Simulator enables agents to practice high-risk scenarios, reinforce compliance requirements, and improve cross-sell effectiveness in realistic, AI-driven simulations.
Together, these systems create a tight feedback loop, connecting real-time evaluation with targeted skill development and measurable performance improvement.
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