Sii Poland
SII UKRAINE
SII SWEDEN
Sii Poland
SII UKRAINE
SII SWEDEN
Sii designs, configures, integrates, and develops AI agents in Salesforce to automate business processes, support employees in their daily tasks, and serve customers across multiple channels.
Ready-made Salesforce templates, actions, components, and industry data models reduce the amount of work that needs to be built from scratch. Sii selects the right elements for specific use cases, configures them to match business processes, and integrates them with the existing environment to move faster from concept to the first working Agentforce scenarios.
Agentforce goes beyond generating responses. It can analyze data, prepare recommendations, initiate tasks, and perform actions according to business rules. Sii designs the agent’s role, instructions, available actions, and escalation rules, enabling automation of entire process stages rather than individual tasks.
Repetitive tasks don’t need to occupy specialists’ time. Sii configures AI agents to support activities such as prioritizing cases and leads, preparing summaries, generating quotes, monitoring orders, and recommending next steps. This allows employees to spend more time on activities that require expertise, decision-making, and direct customer interaction.
Reducing service times requires not only the right technology but also a well-designed process. Sii implements Agentforce to handle selected stages of the service process, from case classification to response preparation, and defines rules for handing cases over to employees whenever human intervention is required.
Automating repetitive activities makes it possible to handle a higher volume of cases and processes without proportionally increasing team involvement. Sii identifies scenarios with the greatest business potential and expands Agentforce with additional use cases, helping organizations scale automation as their business needs grow.
Effective use of AI agents requires clear rules for data access and monitoring. Sii configures Agentforce in line with existing Salesforce permissions, using Einstein Trust Layer mechanisms as well as access and escalation rules to maintain control over responses, actions, errors, and solution costs.
Many business processes span more than one system. Sii integrates Agentforce with ERP systems, e-commerce platforms, WMS solutions, and other data sources, enabling agents to use broader business context and support activities across the organization’s application ecosystem.
Sii combines the experience of more than 120 Salesforce experts holding over 650 certifications with expertise in AI, data, integrations, and testing. This gives clients access to a team that understands both the Salesforce platform and the requirements of implementing AI agents in enterprise environments.
Sii manages the implementation from discovery and use case selection through data and process readiness assessment, agent design, configuration, integrations, and testing to go-live, monitoring, and ongoing optimization. This helps maintain alignment between business objectives and the way the solution operates.
Sii designs Agentforce around specific processes, user roles, and business rules. We define the responsibilities of agents and subagents, available actions, permissions, safeguards, and escalation rules so that AI performs tasks in a controlled way and supports the organization’s actual workflows.
Sii integrates Salesforce with ERP systems, data warehouses, and other platforms and supports migrations to new environments. Agentforce is designed with existing roles, permissions, dependencies, and business rules in mind, reducing the risk of automating processes that have not been properly structured.
See how we do it step by step
Read our FAQ
Salesforce Agentforce is an AI agent platform built into the Salesforce ecosystem. It combines language models, business data, instructions, rules, and approved actions so AI agents can respond to users, recommend next steps, and perform selected tasks. Agents can work with Salesforce CRM data as well as information from connected systems and use natural language to interact with employees and customers.
Key features of Agentforce include AI-powered reasoning, process automation, access to CRM and enterprise data, reusable actions and industry-specific components, integration with external systems, and controls for permissions and security. Depending on the use case, an Agentforce AI agent can analyze information, prepare summaries and recommendations, update records, trigger workflows, and complete approved actions.
Sii supports the full Agentforce implementation lifecycle: discovery and use case selection, data and process readiness assessment, AI agent and subagent design, configuration, integrations, testing, go-live, monitoring, and ongoing optimization. The scope also covers instructions, permissions, safeguards, business rules, approvals, and escalation paths so the agent operates within a controlled business process.
Agentforce can automate or support use cases across sales, customer service, marketing, HR, finance, and business operations. Typical scenarios include lead qualification, case prioritization, preparing meeting and data summaries, generating quotes, monitoring orders, answering customer questions, recommending next steps, and triggering approved actions. Sii prioritizes use cases based on business value, process maturity, data readiness, integration requirements, and operational risk.
Salesforce provides industry-specific Agentforce capabilities for sectors including automotive, financial services, retail, healthcare, education, and manufacturing. Examples include scheduling service appointments in automotive, supporting document collection in financial services, handling returns in retail, and assisting with patient registration in healthcare. Sii selects and adapts relevant components to the organization’s processes, data model, and business requirements.
Yes. Agentforce can use Salesforce data and information made available through APIs, connectors, MuleSoft, Data 360, and other integrations. This makes it possible to connect AI agents with ERP systems, e-commerce platforms, WMS solutions, data warehouses, and industry applications. Sii designs the integration and permission model so the agent receives the context required for the use case and performs only approved actions.
Agentforce operates within Salesforce access controls and security mechanisms and works with the Einstein Trust Layer. Data sent through the Trust Layer to external language models is subject to zero-data-retention policies and is not used by those providers to train their models. Sii also defines permissions, allowed actions, safeguards, approvals, and escalation rules and verifies them during testing.
Sii tests response accuracy, actions, permissions, business-rule compliance, edge cases, errors, and escalation paths before go-live and during ongoing operation. Monitoring can cover response quality, task completion, handling time, usage, costs, user satisfaction, errors, and escalations. These insights are then used to improve instructions, actions, integrations, and additional Agentforce use cases.
The timeline depends on the number and complexity of use cases, data quality, process maturity, integration scope, security requirements, channels, and testing needs. Sii defines the implementation plan after discovery and readiness assessment. A focused, measurable use case is usually the best starting point before Agentforce is expanded to additional processes.
Agentforce costs depend on the Salesforce licensing and usage model, expected volume, channels, users, integrations, data requirements, and implementation scope. The total cost should also include data preparation, configuration, testing, deployment, and ongoing optimization. Sii can estimate the implementation effort and target architecture once the priority use cases and expected usage are defined, while current licensing terms should be confirmed with Salesforce.
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