Make AI and Automation Work in Salesforce
We fix broken automation and disconnected AI use cases, or design them to scale from day one.
Most organisations don’t have an AI problem; they have a structure problem.
AI and automation fail when data is fragmented, processes are unclear, and systems aren’t designed to support decision-making.
AI is being added everywhere. But in most environments, it’s layered on top of broken processes and unreliable data.
The result:
- Automations that don’t behave as expected
- AI outputs that can’t be trusted
- Teams that ignore both
Cloud Genii helps you implement AI and automation in a way that works, whether we’re fixing an existing setup or designing it properly from the start.
Technologies we work with
We work across the Salesforce ecosystem to design solutions that fit your current setup and future direction.
Salesforce’s AI layer that enables agents to take action, support teams, and drive intelligent execution.
We design Agentforce use cases that operate within workflows, assisting teams, automating decisions, and improving outcomes over time.
Salesforce’s automation engine for orchestrating processes and triggering actions.
We use Flow to build structured, event-driven automation that is reliable, scalable, and aligned to real business processes.
A real-time data platform that provides the signals and context for automation and AI.
We use Data Cloud to trigger automation, feed AI decisioning, and ensure actions are based on accurate, up-to-date information.
Fix Broken Automation.
Automation often becomes overly complex, fragile, and difficult to maintain.
We simplify and stabilise your existing automation by:
- Removing unnecessary flows and logic
- Fixing inconsistent triggers and dependencies
- Aligning automation with real business processes
- Ensuring data inputs are reliable
The goal is simple: automation you can trust.
From Rules to Intelligent Systems
In new implementations, the biggest mistake is overengineering too early.
We design automation that is:
- Structured and easy to understand
- Aligned to business processes
- Scalable as complexity grows
- Maintainable without constant rework
So your system evolves without becoming fragile.
Design Automation That Scales
In new implementations, the biggest mistake is overengineering too early.
We design automation that is:
- Structured and easy to understand
- Aligned to business processes
- Scalable as complexity grows
- Maintainable without constant rework
So your system evolves without becoming fragile.
Make AI Operational with Agentforce
AI should not sit in dashboards or recommendations. It should take part in execution.
We design Agentforce use cases that operate directly within your Salesforce processes. For example:
- Automated case handling agents: triage, categorise, and resolve service requests using real-time context
- Deal support agents for sales teams: surface risks, suggest actions, and assist with next steps inside opportunities
- Client engagement agents: respond to inbound queries or trigger personalised outreach based on behaviour
- Internal support agents: assist teams with data retrieval, process guidance, and decision support
- Real-time campaign response agents: detect engagement signals (email clicks, website visits, content interactions) and trigger personalised follow-ups, adjust journey paths, or notify sales based on intent
- Content personalisation agents: dynamically select and adapt messaging, offers, and content blocks based on customer behaviour, lifecycle stage, and interaction history, ensuring every touchpoint is context-aware
These are not standalone AI tools. They are embedded into your workflows, working alongside your teams.
AI is Only as Good as Your Data
AI doesn’t fix bad data. It amplifies it.
We ensure your data foundation is structured, unified, and reliable so AI can operate with:
- Full customer context
- Real-time signals
- Accurate inputs
Without this, AI produces noise. With it, AI becomes operational.
Connect AI, Automation, and Data
AI, automation, and data should not exist in isolation.
We design systems where they continuously reinforce each other.
In practice:
- Data Cloud captures real-time behaviour and context
- Flows and event-based automation trigger actions
- Agentforce evaluates and decides what should happen next
- Actions generate new data, which feeds back into the system
This creates a continuous feedback loop:
- Data triggers action
- Action generates new data
- AI improves decisions over time
The result is a system that becomes more effective as it runs, not more complex.
Enable Teams, Not Replace Them
AI should support your teams, not create confusion. We design systems that:
- Provide clear recommendations
- Reduce manual effort
- Improve decision-making
- Keep humans in control where it matters
The result is better execution, not just more technology.
Trying to Layer AI on Top of a Broken System?
We design and optimise Salesforce environments where automation is reliable, AI is practical, and everything works together as one system.
