Frequently asked questions

Especially then. Most architecture work is retrofit: mapping what exists, deciding what the model should be, and sequencing the path between the two without stopping the business. Starting from a live org is the normal case, not the exception.

Usually, yes. Most orgs don't need a rebuild, they need an audit, the worst debt removed, and the key processes reworked. We recommend a full rebuild only when the foundation genuinely can't support where you're going.

We prefer native configuration and Flow wherever it's practical, it's cheaper to maintain and easier for your admin to own. We reach for Apex or LWC only when the requirement genuinely exceeds what declarative tools handle well.

That's the point. We build to native patterns, keep automation legible, and hand off documentation and training so your admin isn't dependent on us for routine changes.

Not always. Plenty of teams are best served by native quoting plus well-designed price books and Flow. We recommend full CPQ/Revenue Cloud only when configuration and pricing complexity genuinely warrant it, and we'll tell you when it doesn't.

Yes. Discount thresholds trigger approval workflows automatically, with a full audit trail of who approved what and why.

If it exposes an API, a database, or even a scheduled file export, we can almost always integrate it. Where there's no clean interface, we design a middleware layer or staged sync rather than forcing a brittle direct connection.

Failures are caught, retried, and logged, with alerts so someone knows. We design integrations assuming things will occasionally break, the goal is fast, visible recovery, not silent drift.

Almost always because the underlying data or metric definitions are inconsistent, the same word means different things in different reports. We fix the definitions and the data model first; the dashboards then agree by construction.

Yes, either by integrating the data into Salesforce or by reporting across sources. Cross-system reporting is often the point, and it depends on clean integration underneath.

Yes, that's a design requirement, not an afterthought. We ground AI in your data with appropriate controls, keep sensitive data handling explicit, and use enterprise-grade models and Salesforce-native AI where data residency and privacy matter.

Not for anything that needs judgment. We keep a human in the loop on consequential actions and reserve full automation for high-volume, low-risk tasks like classification and first-draft generation.

We measure it, accuracy against real cases and hours saved in production. If a use case doesn't clear the bar, we don't ship it.

You work with the same senior team that knows your org, not a rotating queue. Fixes get to root cause, and the relationship is proactive, we're improving the org, not just closing tickets.

Yes. We monitor release notes, flag anything that affects your org, and handle required changes ahead of the release so nothing breaks.