Watercolour landscape illustration

:: 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?

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