Salesforce Development, Integrations & AI

Use the platform before adding complexity

Not every problem needs code. Before building custom components, we assess what standard capabilities and declarative development can solve.

Standard capabilities and configuration

Objects, fields, security, business rules, interfaces, and functionality available in the platform.

Declarative development

Flow and other configurable capabilities that automate processes and build solutions without necessarily requiring code.

Programmatic development

Apex, Lightning Web Components, and other custom components when requirements, volume, user experience, or architecture justify them.

We balance functionality, maintainability, scalability, and technical complexity.

Process automation with Flow

Less manual work. More traceability.

Flow is a primary tool for automating Salesforce processes without moving directly to programmatic development. We can design automation for:

• record assignment;
• approvals and information updates;
• notifications;
• task creation and tracking;
• sales processes and case management;
• validations;
• guided user interactions;
• coordination with external systems.

Before automating, we review exceptions, responsibilities, volume, and expected behavior. Poorly designed declarative automation can also create complexity and technical debt.

Programmatic Salesforce development

When the need requires code

Some requirements need logic, interfaces, or behavior that standard capabilities and declarative development cannot adequately provide.

Apex

Business logic, processing, services, integrations, and functionality running within the platform.

Lightning Web Components

Specialized experiences and interfaces for processes requiring greater customization.

Asynchronous processing

Processes handling large volumes, integrations, or tasks outside the main transaction.

Technical services and interfaces

Reusable components and services that extend Salesforce or connect it to other platforms.

Automated tests

Validation of expected behavior beyond meeting deployment requirements.

Enterprise integrations

Salesforce connected to real operations

Salesforce data and processes also live in ERP, internal applications, digital channels, contact centers, ecommerce, databases, and other systems.

We design integrations considering:

• REST and SOAP APIs;
• secure authentication;
• Named Credentials and OAuth;
• information synchronization;
• synchronous and asynchronous processing;
• events and decoupled architectures where appropriate;
• error handling and retries;
• traceability and idempotency;
• monitoring and data volumes.

An integration should operate reliably, recover from errors, and remain maintainable over time.

Data that can be used

An intelligent platform needs a reliable foundation

Projects seeking better reporting, automation, or artificial intelligence often uncover data-quality problems. We can review:

• duplicate records;
• incomplete information and inconsistent fields;
• data distributed across systems;
• ownership and responsibility for information;
• permissions and knowledge sources;
• data availability for automation or agents.

The quality of results depends on the quality and context of the information used.

Agentforce and artificial intelligence

Start with a concrete use case

Artificial intelligence can support service, productivity, and automation in Salesforce when it starts with a specific need. We can explore:

• customer guidance;
• frequently asked questions;
• assistance for sales and service teams;
• knowledge search and use;
• support for repetitive tasks;
• controlled automation of actions.

Depending on the context, we can use Agentforce, bots, or other Salesforce capabilities.

Prepare before implementing

Before building an agent, we review the problem, its users, information and sources, allowed actions, permissions, human intervention, usefulness metrics, and applicable requirements or licenses.

An agent does not automatically fix poor data or undefined processes.

Implement with control

We begin with a bounded scope: use case, users, authorized sources, allowed actions, acceptance criteria, exceptions, and escalation to people. This lets us test value before expanding.

Validate before scaling

We review response quality, executed actions, exceptions, security, permissions, traceability, usage costs, and supervision. Artificial intelligence needs the same engineering judgment as any critical platform capability.

Integrations + data + AI

An agent may need ERP information. An automation may depend on another system’s data. A sales process may update both Salesforce and an external platform.

We approach development, integrations, data, and artificial intelligence as parts of the same architecture when the problem requires it.

Quality from development onward

Every implementation should be testable, understandable, and able to evolve. Depending on the project, we include:

• acceptance criteria and unit tests;
• functional validation and exception handling;
• documentation and code review;
• version control and change traceability;
• deployment preparation.

When delivery requires greater control, we work with our specialized Salesforce DevOps & Release Management capability.

Explore Salesforce DevOps

AI in how we build

We use artificial intelligence tools to support analysis, development, test generation and review, documentation, and other engineering tasks when they improve productivity or quality.

Technical decisions and deliverables remain under human review. Client information is used only through tools and conditions authorized for each project.