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Configuring objects and automation before agreeing on lifecycle stages, handoffs, data standards, and decisions.
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Turn on the AI you're probably already paying for — scoring, forecasting, and Agentforce configured to your data and guardrails.
Turn on the AI you're probably already paying for — scoring, forecasting, and Agentforce configured to your data and guardrails.
The goal is not simply to complete a list of tasks. It is to remove a specific operational or customer constraint, prove the result, and leave clear ownership after delivery.
One accountable team connecting the decisions, quality checks, and handoff required for a durable result.
Salesforce ships increasingly capable AI that most orgs never activate — because activation requires data hygiene, thoughtful configuration, and change management. We make the AI features earn their line item.
The platform mirrors historical spreadsheets and departmental silos instead of the desired customer lifecycle.
Data definitions, ownership, permissions, automation, and reporting differ across teams and integrations.
Users work around the system because required fields and workflows add effort without returning useful context.
We connect diagnosis, scope, execution, validation, and operational ownership. The package changes the depth and scale—not the discipline of the delivery system.
We confirm the desired outcome, users, current state, dependencies, risks, and evidence of success before prescribing salesforce einstein & ai configuration.
We translate aI-readiness data quality assessment and einstein feature configuration (scoring, insights) into visible decisions, responsibilities, milestones, and review criteria.
Delivery moves through reviewable increments with quality checks, exception handling, and stakeholder decisions recorded before they become rework.
We complete team enablement on AI workflows, confirm handoff and escalation paths, and leave a practical measurement and improvement plan.
Every tier keeps the core controls below. Package level changes the volume, depth, complexity, or operating cadence.
AI-readiness data quality assessment
Einstein feature configuration (scoring, insights)
Prompt and agent setup (Agentforce)
Guardrails and permission design
Team enablement on AI workflows
The visible deliverable is rarely the whole system. These are the recurring gaps we design out before they become delay, rework, or risk.
Configuring objects and automation before agreeing on lifecycle stages, handoffs, data standards, and decisions.
Migrating duplicates, obsolete fields, and inconsistent history without rules for reconciliation and validation.
Launching with technical training but no role-specific adoption, governance, backlog, or reporting ownership.
Our advantage is not a claim that trade-offs disappear. It is the ability to connect the decisions other providers often split apart, make quality visible, and leave ownership clear.
The operating process and decision model are designed before the platform is configured.
Data, permissions, integrations, automation, reporting, and adoption are planned as one implementation.
Migration and launch use rehearsal, reconciliation, acceptance tests, and a controlled support period.
Scope advantage: The scope makes aI-readiness data quality assessment explicit, then connects it to einstein feature configuration (scoring, insights); those dependencies are less likely to disappear between separate vendors.
Final targets are set during alignment, using a baseline, a named owner, and a realistic measurement window. Typical measures include:
Adoption and required-data completeness
Handoff time and automation success
Pipeline, service, or lifecycle reporting accuracy
Activate
Intelligence
AI Operations
Not sure which package fits? Build a guided project brief. We will use your goal, current stage, timing, and investment range to recommend the right package or a strategy session.
The readiness audit answers that first — scoring models trained on garbage make confident garbage. Sometimes the honest first step is a data cleanup sprint.
It varies by feature and edition; part of the Activate tier is mapping what your current licenses already include before you buy add-ons.
With guardrails, scoped permissions, and human escalation — yes, incrementally. We deploy in observe mode first, then expand authority as trust is earned.
