:: Salesforce / Agentforce implementation
Agentforce implementation, from first use case to agents your team trusts
Agentforce lets AI agents work inside Salesforce: answering customers, qualifying leads, updating records. The hard part is not switching it on. It is choosing the right job, getting the data ready and setting limits on what an agent may do. That is the work we do.
Use case picked on value
Grounded in your CRM data
Guardrails and testing
:: What we do
What our Agentforce work covers
We usually start with one agent for one job, prove it works, then add more.
01
Readiness and use-case choice
We check data quality, permissions and processes, then pick the first agent job with the clearest payback.
02
Agentforce for Service
Agents that answer customers from your knowledge base, check order or case status and hand off to a person with context.
03
Agentforce for Sales
Agents that research and qualify inbound leads, book meetings and draft follow-ups for reps to approve.
04
Topics, actions and prompts
Agent topics, Flow and Apex actions and prompt templates, built so the agent only does what it should.
05
Data Cloud grounding
Bring in data from outside Salesforce, such as orders or usage, so agents answer with the full picture.
06
Testing and monitoring
Test conversations, accuracy checks and usage tracking before and after launch, with changes made on evidence.
:: Agentforce use cases
Agentforce use cases that pay off first
The best first agent handles a frequent, well-defined job where the data already lives in Salesforce. These are the ones we see deliver soonest.
Service
Case triage and routing
The agent reads new cases, sets type and priority, pulls account context and routes them to the right queue with a summary.
Read the blueprint
Service
Customer self-service
Answers order, account and policy questions on your site or portal from knowledge articles and records, and hands off to a person when needed.
Sales
Lead qualification
Replies to inbound leads, asks qualifying questions, books meetings and updates the lead, so reps start with context.
Sales
Account research and follow-ups
Summarises account history and recent activity before a call, then drafts the follow-up email for the rep to review.
Field service
Job preparation
Gives technicians a summary of the asset, past visits and parts before they arrive.
Read the blueprint
Internal
Agents in Slack
Staff ask Salesforce questions in Slack, such as pipeline for a region or open cases for an account, without opening a report.
:: How Agentforce works
How does Agentforce work?
Agentforce is not a chatbot bolted onto Salesforce. It reasons over your data and acts through the tools you allow. This is what happens on every request.
01
A request arrives
From a customer on your site, an employee in Salesforce or Slack, or an event such as a new case or lead.
02
The agent picks a topic
Salesforce’s reasoning engine matches the request to one of the topics you defined, such as order status or lead qualification.
03
It follows your instructions
Each topic has plain-language instructions and limits: what to do, what to ask, and what never to do.
04
It uses allowed actions
Actions are Flows, Apex, prompt templates or API calls you approve. The agent can only do what these actions permit, under the user’s permissions.
05
The Trust Layer checks the data
The Einstein Trust Layer masks sensitive data before it reaches the language model, checks responses and keeps an audit trail.
06
It answers or hands over
The agent replies or completes the task, and passes anything outside its limits to a person with a summary of the conversation.
:: Side by side
Agentforce or a custom AI agent?
Both can work. The right choice depends on where your data and your people live.
Agentforce
Custom AI agent
Where it runs
Inside Salesforce
Your cloud, next to any system
Best when
Work and data are mostly in Salesforce
Work spans many systems or none is Salesforce
Licensing
Salesforce Agentforce pricing
Model and hosting costs only
Model choice
Salesforce-managed models
Any model: OpenAI, Claude, Gemini, open source
Time to first agent
Weeks, if the data is ready
Weeks to a few months
If your process lives outside Salesforce, see our AI agent development services.
:: How it works
How an Agentforce implementation runs
A first agent usually goes live in six to ten weeks.
Weeks 1 to 2
Assess
Data, permissions and processes reviewed, and one use case chosen with a clear success measure.
Weeks 3 to 5
Build
Topics, actions, prompts and data grounding configured in a sandbox.
Weeks 6 to 8
Test
Hundreds of test conversations, edge cases and a pilot with a small group of real users.
Weeks 8 to 10
Launch
Go-live with monitoring and hand-off rules, then a review of results after 30 days.
:: Cost and timeline
How much does an Agentforce implementation cost?
Typical prices for our Agentforce work, based on a senior team at $25 to $35 an hour. Agentforce usage is licensed separately by Salesforce, and its pricing changes, so confirm current rates with your account executive.
Pilot agent
$8k – $20k
4 to 8 weeks
One use case with topics, actions and guardrails, tested on real cases and launched to a small group.
Production rollout
$20k – $50k
2 to 4 months
Several topics or channels, data clean-up, integrations through Flow or MuleSoft, monitoring and handover.
Agents with Data Cloud
$50k – $120k+
3 to 6 months
Agents grounded in data from outside Salesforce through Data Cloud, across service, sales or field teams.
What it costs to run
Running cost is mainly Salesforce’s Agentforce usage charges, which depend on conversations or actions. We estimate volumes during the pilot so you can budget before rolling out further.
What moves the price
Number of topics and channels
How clean your data and knowledge articles are
Actions that need custom Flow or Apex
Data from outside Salesforce (Data Cloud)
Testing and approval steps your risk team needs
:: Readiness checklist
Is your org ready for Agentforce?
Agents repeat whatever your data and permissions allow. Check these before you build.
Ready to start
One clear use case with a measurable goal
Knowledge articles that are current and owned
Few duplicate accounts and contacts
Permission sets that match what each user should see
Processes already automated in Flow where possible
A person who reviews agent conversations weekly
Fix these first
Duplicates and empty fields in key objects
Loose sharing rules that expose too much data
Knowledge articles nobody has updated in years
No agreed point where the agent hands over
Launching to every customer on day one
:: Why Sterling
What you get
A first agent live on one clear job
Data and permission fixes it needed
A test set you can re-run after each change
Usage and accuracy reporting
A shortlist of the next agents worth building
:: Tools we use
Agentforce
Agent Builder
Prompt Builder
Data Cloud
Einstein Trust Layer
Flow
Apex
Knowledge
Slack
4.9
Average rating on Clutch · 350+ projects since 2019
:: Questions
Questions about Agentforce
What does an Agentforce implementation include?
How does Agentforce work?
How much does Agentforce cost?
Do we need Data Cloud for Agentforce?
Is our data ready for Agentforce?
What is Agentforce?
What are the most common Agentforce use cases?
How does Agentforce protect personal data?
How do you enable Agentforce in Salesforce?
Can Agentforce work in Slack?
How long does it take to launch a first Agentforce agent?
:: Related Salesforce services
Other ways we can help
Send us your brief. We’ll help turn it into reality
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