Orquesta Labs

CRM & Platform Development

Build custom CRM functionality using scalable architecture, automation, custom components, and business logic.

Who it’s for

These engagements fit teams in situations like these:

Teams that have outgrown declarative tools and need Apex, LWC, or advanced Flow patterns done carefully.
Businesses with unique pricing, quoting, fulfillment, or compliance rules that standard Salesforce cannot express cleanly.
Organizations that want custom UX components without accumulating unmaintainable code.
Companies preparing API-driven features or Agentforce actions that require solid, tested backend logic.
Companies that need Apex or LWC for a specific business rule, with tests, documentation, and a handoff their admin can maintain after launch.
Product owners who want CRM customizations estimated from real edge cases, with sandbox demos before production, so spend stays tied to business outcomes.

What’s included

A clear scope of consulting work your team can understand and adopt.

Architecture before code We decide what belongs in Flow, what belongs in Apex, and what should stay declarative. Custom development starts with maintainability: naming, layering, and boundaries so future admins are not trapped by opaque code.
Apex business logic Triggers, services, and asynchronous jobs implement rules that configuration cannot handle safely. Logic is tested, bulk-safe, and documented so volume growth and concurrent users do not create silent data corruption.
Lightning Web Components Custom interfaces support guided selling, specialized intake, operational consoles, or embedded workflows where standard pages fall short. Components stay focused on a clear job rather than becoming a second CRM inside the platform.
Advanced Flow and hybrid patterns When Flow is the right tool, we design patterns that stay readable and invocable. When Flow alone is fragile, we combine it with Apex services so complex steps remain testable without abandoning admin-friendly entry points.
API and platform extension Custom endpoints, callouts, and platform events support integrations and AI-agent-related actions when required. Interfaces are designed with authentication, error handling, and logging as first-class concerns.
Testing and quality gates Unit tests, scenario validation, and peer review reduce the risk of regressions. We define what “done” means before shipping — not after a production surprise.
Deployment and documentation Changes move through environments with clear release notes, admin guidance, and rollback thinking. Code is handed over as a product your team can operate, not a black box that only the original developer understands.
Governance for AI-adjacent features Where custom code supports agents or automation, we keep human review points, permission checks, and auditability in the design. Development accelerates the business without removing accountability.

How it works

Discover, Design, Build, and Improve—scoped to this service.

Discover We clarify the business rule, volume expectations, edge cases, and whether a declarative approach already exists. Discovery prevents writing code for problems that better fields, Flow, or process redesign would solve more cheaply.
Design Technical design covers data model impacts, transaction boundaries, error behavior, UX flow, security, and test strategy. You approve the approach — including what will not be built — before implementation starts.
Build Development happens in sandbox with iterative demos against real scenarios. Tests, documentation, and admin notes are part of the build, not an afterthought when the deadline arrives.
Improve After release we monitor errors, gather user feedback, and refine performance or UX. Custom features enter the same improvement cadence as the rest of the CRM so they do not become orphaned technical debt. When business rules change, the code path is revisited with the same architecture discipline used on day one.

Typical deliverables

Concrete outputs you can use after the engagement.

Technical design document with declarative vs code decisions
Apex and/or LWC solution with tests appropriate to the risk
Sandbox validation evidence and scenario checklist
Deployment package or change set with release notes
Admin and developer documentation for ongoing ownership
Error handling and logging approach for support teams
Backlog notes for follow-on enhancements and AI agent hooks if relevant

FAQs

When do we need custom CRM development instead of declarative automation?

When business rules are complex, volume is high, transactions span many records, or UX needs cannot be met cleanly with standard tools. We recommend code only when declarative options would be fragile, slow, or impossible to maintain.

Will custom code lock us into one developer forever?

Not if it is written with clear architecture, tests, and documentation. Boutique delivery includes handoff materials so your team or another trusted partner can maintain the work.

Do you follow platform coding and security best practices?

Yes. Bulkification, sharing awareness, least privilege, and test coverage are part of the engagement. Shortcuts that “work in a demo” and fail under load are not acceptable delivery.

Can development support AI agent use cases?

When agents need reliable actions against CRM data, custom services and guarded APIs can help — after the use case and permissions are clear. We treat Agentforce-related code as governed product work, not experimental scripts in production.

How do you estimate development work?

Estimates follow discovery of edge cases, data volumes, and integration touchpoints. Fixed scopes are preferred for well-bounded features; exploratory work is phased so you control spend as certainty increases. We share assumptions in writing so scope changes are visible early rather than buried in a surprise invoice.

Consultation

Build a stronger CRM foundation

Talk through your current environment, business goals, and practical next steps.

Discuss custom CRM development