1000+ Employee Legal firm accelerates Ramp-Up by 51% and Strengthens Compliance Readiness with AI Roleplays
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The national law firm is focused on the preservation and promotion of creditors’ rights.
Founded
1991
Industry
Legal
51%
2,803
93
See How Outdoo Turns Practice Into Performance with AI Roleplays?
Book a DemoThe firm provides bankruptcy, commercial collections, consumer collections, and litigation services to leading financial institutions.
With multiple offices and over 1,300 employees, Zwicker operates a high-volume, compliance-driven call environment where performance, consistency, and regulatory precision are critical.
The Challenge
As Zwicker expanded its collections operations across multiple locations, maintaining consistent onboarding standards became increasingly complex. New hires undergo a structured three-week training program, but much of their call preparation relied on manual roleplays and trainer-led simulations. This created variability across offices and limited the number of realistic practice opportunities each rep received before going live.
Additionally, collectors must strictly adhere to regulatory scripts and disclosure requirements. Any deviation can create compliance risk. Training needed to reinforce not only negotiation skill but also precision and consistency in regulated conversations.
Without scalable, repeatable simulation, ramp time extended and call performance varied by trainer and location. Managers lacked objective data to measure readiness before reps transitioned to live calls. Coaching was largely reactive—correcting mistakes after they occurred on the floor rather than preventing them in advance. As hiring volumes increased, this model became unsustainable.
The Solution
Zwicker implemented Outdoo’s AI Roleplays and Coaching platform to standardize onboarding and build a closed-loop coaching system. The team integrated AI-powered simulations directly into the three-week training flow, allowing new hires to practice real-world collection scenarios repeatedly before handling live customers. Managers gained real-time scoring, performance visibility, and structured remediation workflows.
AI Roleplays for Multiple Personas and Scenarios
Zwicker designed tiered AI roleplay scenarios aligned to their call scripts—beginner, intermediate, and advanced—each mapped to progressively rigorous scorecards. New hires begin practicing core compliance and call-opening fundamentals by day three of training and build toward full negotiation conversations by week two.
The team customized AI personas to mirror real debtor behavior, including skeptical, time-constrained, or frustrated callers. They also introduced environmental realism such as background noise and varied tone. In the first rollout alone, teams completed 2,803 AI roleplays, totaling approximately 93 hours of structured practice.
“If we see someone struggling on live calls, we move them back into the simulator. They’ve already practiced these conversations dozens of times before they ever hit the floor. ”
Post-Sales Roleplays for Continuous Coaching
Beyond onboarding, Zwicker leveraged AI roleplays for remediation and ongoing performance improvement. Dedicated workspaces were created for client-specific portfolios and skill-based reinforcement. Reps demonstrating gaps in compliance or negotiation could be placed into targeted practice tracks without disrupting production operations.
The platform also enabled mid-call scenario resumes, allowing reps to rehearse only the most challenging negotiation moments instead of repeating full simulations.
“Once we integrated AI roleplays into the training flow, usage and outcomes improved significantly. We’re now using it not just to train, but to reinforce and continuously refine performance. ”
AI Coaching for Objective Performance Measurement
Every roleplay is automatically scored using Zwicker’s customized compliance and performance scorecards. The AI evaluates disclosure delivery, call structure, objection handling, and negotiation outcomes. Managers can review transcripts, scoring breakdowns, and behavioral insights without manually listening to every session.
This closed-loop coaching model shifted Zwicker from subjective observation to objective performance measurement. Analytics also revealed patterns across teams, enabling focused enablement interventions where foundational skill variance existed.
“The visibility into real performance data changed how we coach. Instead of guessing where someone needs help, we design targeted learning paths based on measurable gaps. ”
The Impact
With Outdoo, Zwicker modernized its onboarding and coaching infrastructure. The firm replaced manual, inconsistent roleplays with scalable AI-driven simulations tied directly to measurable performance standards.
51% Faster Ramp with Higher Readiness
New hires reached floor productivity 51% faster by practicing high-volume, realistic scenarios during training. Reps entered live call environments confident, structured, and compliance-ready.
Compliance-Driven Consistency Across Locations
Standardized AI scorecards reduced variability between offices. Foundational compliance behaviors improved, and advanced outbound scorecards demonstrated strong performance across teams. Managers now replicate high-performing team models more systematically.
Scalable Coaching Built on Measurable Practice
With 2,803 roleplays and ~93 hours of simulation completed in a single month, Zwicker effectively saved the equivalent of 12 working days of trainer-led mock calls. AI scoring enabled data-backed coaching conversations and targeted remediation without increasing management overhead.
By integrating AI roleplays with real performance measurement, Zwicker & Associates transformed onboarding from a manual training function into a scalable, performance-driven enablement engine—ensuring every collector is prepared before the conversation counts.
