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Coforge: Where AI engineering meets industry expertise.
Learn about our company, our vision and values, and the 45,000+ professionals enabling businesses to harness the power of AI.
Learn more about Coforge
Learn about our company, our vision and values, and the 45,000+ professionals enabling businesses to harness the power of AI.
Learn more about Coforge
Main
Coforge: Where AI engineering meets industry expertise.
Learn about our company, our vision and values, and the 45,000+ professionals enabling businesses to harness the power of AI.
Learn more about Coforge
Learn about our company, our vision and values, and the 45,000+ professionals enabling businesses to harness the power of AI.
Learn more about Coforge

Agentforce Catalyst is Coforge's accelerated Agentforce implementation offering designed to help organizations move from a business use case to a working AI agent in production.
Powered by Agentforce and Salesforce Platform capabilities, the offering enables customers to adopt AI agents through flexible implementation options, including an SDR Agent for sales, a Case Triage Agent for service operations, and custom business agents for specific process needs. The final implementation is shaped based on the customer’s priorities, requirements, and use-case mix, allowing one or more agent capabilities to be combined into a practical, business-aligned solution.
It combines use-case validation, agent configuration, workflow integration, governance controls, testing, and deployment into a structured implementation approach.
Designed for sales, service, and business transformation teams, Agentforce Catalyst helps organizations adopt AI through practical business use cases rather than broad transformation programs. By combining standardized implementation assets with controlled customization, the offering enables organizations to deploy agent-driven capabilities while maintaining governance, transparency, and operational oversight.
Slow and Inconsistent Lead Qualification
Sales teams often rely on manual reviews and inconsistent qualification processes, delaying lead engagement and handoff.
Manual Case Intake and Routing
Service teams spend significant effort analyzing requests, classifying cases, and determining the correct route for resolution.
Difficulty Converting AI Ideas into Working Solutions
Organizations may identify AI opportunities but lack a clear implementation path and delivery framework.
Unpredictable AI Implementation Efforts
Custom AI initiatives can create uncertainty around scope, timeline, cost, and delivery outcomes.
Governance and Adoption Concerns
Business teams require transparency, oversight, auditability, and escalation controls before introducing AI into operational workflows.
Disconnected Data and Process Execution
AI agents need controlled access to Salesforce records, workflows, and business processes to deliver meaningful outcomes.
What it does: Supports lead engagement, qualification, routing, CRM updates, follow-up activities, and sales handoffs.
How it helps: Improves lead response speed and qualification consistency while reducing repetitive SDR effort.
What it does: Analyzes inbound service requests, determines intent and urgency, classifies cases, and recommends routing actions.
How it helps: Reduces manual triage effort and improves case handling consistency.
What it does: Configures Agentforce around a customer-defined business process, including workflows, actions, integrations, and controls.
How it helps: Extends AI capabilities into business-specific operational scenarios.
What it does: Defines business objectives, users, data requirements, success measures, and implementation boundaries.
How it helps: Creates alignment on expected outcomes before implementation begins.
What it does: Configures agent topics, actions, prompts, workflows, and user interactions for the selected use case.
How it helps: Accelerates deployment while keeping agent behavior aligned with business requirements.
What it does: Connects agents to Salesforce records, knowledge, automation workflows, and approved integrations.
How it helps: Enables agents to execute business processes using real business context.
What it does: Establishes approval points, confidence thresholds, escalation paths, auditability, and exception handling.
How it helps: Maintains operational control and supports responsible AI adoption.
What it does: Validates response quality, actions, routing, record updates, and user acceptance before deployment.
How it helps: Reduces risk and improves confidence in production use.
50-70%
60-80%
30-50%
40-60%
2-3x