Pitcher Launches Catalyst AI App Builder for Custom, Data-Connected Sales Apps in Minutes

Pitcher debuts Catalyst, an AI app builder that lets RevOps spin up data-linked sales apps in minutes using plain English, no code. Build, refine, and deploy inside Pitcher.

Categorized in: AI News Sales
Published on: Mar 14, 2026
Pitcher Launches Catalyst AI App Builder for Custom, Data-Connected Sales Apps in Minutes

Pitcher Launches Catalyst AI App Builder for Custom Sales Apps

Pitcher announced Pitcher Catalyst on March 13, 2026 - an AI-driven app builder that lets admins and revenue operations teams create custom, data-connected sales apps in minutes using natural language. No code. Describe the app, review the generated design, fine-tune it, and deploy directly inside the Pitcher platform for reps to use immediately.

The goal is simple: cut the time from idea to working tool from months to minutes. Catalyst ships apps through Pitcher's App Marketplace, so anything you build follows the same security and infrastructure standards the platform already uses.

What it means for Sales and RevOps

Teams can stand up focused micro apps fast - account views, pre-call planners, approval helpers, or territory dashboards - without waiting on long dev cycles. A chat interface handles creation and updates, so you can iterate by prompt until the app fits the workflow.

  • Build with natural language, no coding required
  • Deploy instantly inside the Pitcher environment
  • Connect to your CRM and external data for accurate, current information
  • Iterate quickly through conversational prompts
  • Distribute via Pitcher's App Marketplace, including to partners and SIs

Why reps will care

Apps show up where reps already work inside Pitcher, so there's less tab-switching and fewer manual updates. With live CRM data and external sources connected, reps get cleaner context, faster prep, and tighter follow-through.

AI-native sales execution built to scale

Catalyst is built on leading AI coding models and is architected to evolve as AI advances. It's structured for enterprise use: governance, data integrity, and performance stay within existing IT standards.

"At the enterprise level, it can take months for organizations to plan, build, approve, and deploy custom applications to meet the precise needs of their field sellers," said Kevin Chew, CEO at Pitcher. "Catalyst allows admins and teams to build the solutions needed for superior sales performance with agility and speed, all within the security models and data integrity rules of their enterprise IT Governance models and fully within Pitcher."

"For years, the gap between what sales teams need and how or when IT can deliver has slowed performance," said Jim Franzel, VP of Product at Pitcher. "Catalyst closes that gap with natural language app creation and quick deployment inside Pitcher. It's the fastest path from a sales requirement to a working solution that improves rep performance, improves follow-through, and ultimately improves revenue outcomes."

Practical use cases you can spin up fast

  • Account planning assistant with next-best actions and open risks from CRM
  • Pre-call planner that pulls recent activity, stakeholders, and objections
  • Pricing and approvals helper that routes requests and logs decisions
  • Competitive battlecards that refresh from approved content sources
  • Territory health dashboard with pipeline, coverage, and whitespace
  • Post-meeting notes that summarize key points and sync tasks to CRM
  • Compliance or field-visit checklists with offline support and audit trails

Getting started checklist

  • Pick one blocker that slows deals (approval lag, prep time, data entry)
  • List the data sources needed (CRM objects, pricing tables, content hubs)
  • Draft a clear prompt: users, workflow steps, rules, required fields
  • Add guardrails: permissions, data visibility, and audit needs
  • Build a pilot app, test with five sellers, collect feedback, iterate
  • Publish in Pitcher's App Marketplace and train managers on the workflow
  • Track adoption, cycle time, and win-rate lift; then scale to the next use case

Where to learn more

Explore practical plays, tools, and case studies: AI for Sales. For leaders planning rollouts and governance, see the AI Learning Path for Sales Managers.


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