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Skillet launches AI commercial training platform for life sciences teams

Skillet emerged from stealth on June 12, 2026, with an AI commercial excellence platform for pharmaceutical, biotech and medical device teams. The product focuses on roleplay, manager coaching and call prep, with early customers already including a top-20 global drugmaker and a Fortune 500 medtech company. Why it matters: - Life sciences sales teams face strict compliance rules, shifting labels and highly technical customer questions. - Skillet is designed to help reps and managers practice those conversations before they happen. - The platform targets launches, label expansions, loss-of-exclusivity response and other high-stakes commercial moments. What happened: - Skillet emerged from stealth on June 12, 2026, as an AI commercial excellence platform for pharmaceutical, biotech and medical device teams. - The company is headquartered in Marina del Rey, California. - Early customers include a top-20 global pharmaceutical company and a Fortune 500 medical technology company. - Skillet is available now to commercial teams in life sciences. - More information is available at Skillet’s website . The details: - The initial product suite includes AI roleplay, manager coaching and call prep. - AI roleplay lets sales reps practice HCP conversations with simulated healthcare providers. - The simulations surface real objections, personas and clinical nuance from field interactions. - Manager coaching lets front-line sales managers rehearse coaching, feedback and difficult conversations. - Call prep lets reps plan for a specific call on demand, including by voice from the road. - The platform is built around approved labeling, claims and customer documents in a Closed Knowledge Ecosystem for each product. - Optional MLR approval flows let medical, legal and regulatory reviewers sign off on key inputs. - Skillet is ISO 27001 compliant and GDPR compliant. - SOC 2 Type II certification is in progress. - Customer content is logically isolated and is never used to train external AI models. - Skillet provides single sign-on plus CRM and LMS integrations. - Commercial teams are using the platform for product launches, competitive defense, loss-of-exclusivity response, label expansions, messaging refreshes, new-hire onboarding, leadership development and ongoing performance improvement. - The team says approved practice scenarios have reached the field within 48 hours of a market event. Between the lines: - The product is built for the day-to-day workflow of reps, not a generic enterprise training use case. - The compliance and content-guardrails features are central to the pitch because life sciences buyers need AI that stays within approved claims. - Skillet is backed and built by Wayground, a learning and engagement company founded in 2015. - Wayground says its products support more than 50 million users per month in over 100 countries. - Skillet extends Wayground’s learning infrastructure into a regulated market with tighter privacy and security requirements. - Connor Pierson said the goal is to make objection handling feel close to live manager coaching. - Aditi Soni said AI training tools for life sciences need to understand label, clinical data, claims and indication-specific context. - Ankit Gupta, CEO of Wayground, said Skillet brings the company’s learner-motivation work into a higher-stakes industry. What’s next: - Skillet is positioning itself for broader adoption across pharmaceutical, biotech and medical device commercial teams. - The company is continuing to design scenarios for partners. - The product roadmap includes completing SOC 2 Type II certification. - Life sciences buyers evaluating AI training tools will likely focus on compliance controls, approval workflows and data isolation before rollout. The bottom line: - Skillet is betting that regulated commercial teams will pay for AI training that is tightly bounded to approved content and tailored to life sciences workflows.

Disclaimer: This article was produced by AGP Wire with the assistance of artificial intelligence based on original source content and has been refined to improve clarity, structure, and readability. This content is provided on an “as is” basis. While care has been taken in its preparation, it may contain inaccuracies or omissions, and readers should consult the original source and independently verify key information where appropriate. This content is for informational purposes only and does not constitute legal, financial, investment, or other professional advice.

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