Fixed scope
Automation consolidation
Untangle overlapping triggers, flows and process builders on your core objects into one documented, order-controlled automation layer with tests.
Services / Salesforce Development
Salesforce platforms that outlive the admin who inherits them.
Governor-safe Apex, tested triggers, automation a new admin can read.
- Typical first engagement
- 4–8 weeks, fixed scope
- Starts with
- Org audit — automation map and technical debt register
- Ends with
- Test coverage, deployment pipeline and documented data model
The problem
What this practice is actually for.
Anyone can ship a flow. Fewer people can tell you why three generations of automation all fire on the same object, in an order nobody controls, at quarter end.
We treat an org as production software: version control, deployment pipelines, real test coverage, an automation map. The measure is whether your admin can change it safely six months after we leave.
- One automation strategy per object instead of four competing ones
- Apex written against governor limits, bulk-tested at realistic volumes
- Integrations that fail loudly and retry, rather than dropping records silently
- Deployment through a pipeline, not by clicking in production
In the work
What Salesforce code looks like when we write it.
Running
0.0s
pipeline
main
● live run
Bulk-safe, governor-aware, actually tested.
One query, one DML, tested at ten thousand records — not the two that clear a coverage gate. Metadata in version control, deployed through a pipeline.
Capabilities
Salesforce Development — the full stack.
6 capability groups
- Development
- Apex, Lightning Web Components (LWC), triggers with a single-handler pattern, Batch Apex, Queueable and scheduled jobs
- Automation
- Flow automation and process optimisation, consolidation of legacy Process Builder and Workflow Rules
- Data
- SOQL optimisation, data modelling, custom objects, fields, validation rules, large-data-volume strategy
- Integration
- REST API integrations from Salesforce to external systems, Platform Events, middleware patterns, retry and reconciliation
- Clouds
- Sales Cloud customisation, Experience Cloud development, B2B Commerce Cloud support
- Engineering discipline
- Version-controlled metadata, CI deployment pipelines, Apex test coverage that asserts behaviour rather than lines
Typical engagements
How this work usually starts.
Indicative scope and duration
Fixed scope
Integration build
Bidirectional integration between Salesforce and an ERP, billing system or data warehouse — with idempotency, retries, reconciliation reporting and alerting.
Embedded
Salesforce capacity for a product team
A senior Salesforce engineer inside your sprint process for teams shipping continuously against the platform without a full-time hire.
What you get
Deliverables, every time.
01
Automation map
Every trigger, flow and rule on your core objects, what fires when, and which ones are redundant or actively fighting each other.
02
Deployment pipeline
Metadata under version control with CI validation, so changes move through sandboxes instead of being clicked in production.
03
Test coverage that means something
Bulk-safe Apex tests asserting real behaviour at realistic volumes — not coverage padding written to clear a deployment gate.
04
Admin handover
A written walkthrough of the data model, integration contracts and known constraints, aimed at the person who owns the org next.
Questions
What clients ask before they commit.
No, and you should be wary of anyone who says yes. Admins own configuration, users and process; we handle the engineering layer — Apex, LWC, integrations, deployment and performance. The best outcome is your admin ending the engagement with more confidence to make changes, not less.
With an audit, priced separately and small. Two to three weeks produces an automation map, a technical debt register ranked by risk, and a recommendation on sequence. That artefact is useful whether or not you continue with us, and it means the build phase is scoped against reality rather than optimism.
Flow where admins should own the logic and the volume is modest. Apex where you need bulk safety, complex branching, external calls or testable business rules. The failure mode we see most often is complex logic pushed into Flow because it felt faster, then hitting limits at quarter end with no tests to refactor against.
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