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Agents that deliver real resultsare built on Agentforce.

With Agentforce, you don't just automate work. You scale. Join thousands of companies building intelligent agents that serve customers, support employees, and drive measurable results across every team.

Falabella Stat Card

Grupo Falabella scales WhatsApp support 5x, resolving 60% of enquiries autonomously.

Engine Stat Card

Engine keeps 1M travellers moving, cutting handle time 15% and saving $2M doing it.

Finnair Stat Card

Finnair takes off, doubling first-contact resolution in four months.

Reddit Stat Card

Reddit makes advertiser support the front door to revenue, resolving chat enquiries 84% faster.

Built anywhere. Trusted everywhere.

With 12k+ customers across 39 countries, Agentforceis at work around the world. From banking to retail to travel, companies are reimagining what's possible with AI.

Global map showing logos of companies that use Agentforce

Momentum you can measure.

Companies around the world save time, scale revenue, and elevate employees with agents that actually work — powered by Agentforce.

Customers share tips for a successful Agentforce deployment.

Scaling AI that works doesn't happen overnight. Our customers built it — one prompt, one workflow, one iteration at a time. Here's what they've learnt along the way.

Engine consolidated related topics to prevent confusion.

Engine consolidated related topics to prevent confusion.
Engine

Nexo made sure their data and knowledge were agent-ready.

Nexo made sure their data and knowledge were agent-ready.
Nexo

Safari365 got hands-on and used rapid iteration.

Safari365 got hands-on and used rapid iteration.
Safari365

OpenTable built flexibility into their escalation logic.

OpenTable built flexibility into their escalation logic.
OpenTable

Endress+Hauser trained their agent like a new hire.

Endress+Hauser trained their agent like a new hire.
Endress+Hauser

reMarkable aligned early with their partners and executives.

reMarkable aligned early with their partners and executives.
reMarkable

See how Salesforce runs on Agentforce.

Read our latest earnings report.

Explore Enterprise AI Usage Data.

Take the next step with Agentforce.

Frequently Asked Questions

Over 12,500 companies across 39 countries currently use Agentforce to build intelligent agents and reimagine possibilities with AI.

Yes, across industries, Agentforce is helping businesses of every size and type to save time and money. From sales and service assist agents, to travel and recruiting agents, there are powerful, time-saving options for you.Check out our use case library for inspiration.

Agentforce isn't just siloed agents. It's interwoven across your entire Salesforce ecosystem, from core apps to third-party integrations. Plus, Salesforce arms customers with resources, training, and service options to achieve long-term success and growth with their Agentforce agents.

Agentforce is already used at scale and delivers real results for many global customers.See all customer stories here.

Agentforce‘s built-in trust layer handles data privacy, mitigates bias, and prevents hallucinations, so every interaction is reliable. With trust and governance built in, Salesforce ensures your AI and business scale securely, reliably, and with confidence. Learn more about theTrust Layer.

Salesforce AI encompasses predictive, generative, and agentic AI. Agentforce uses all three, working together to deliver results for customers.

Grupo Falabella goes from 40,000 conversations a month to 216,000

Engine consolidated related topics to prevent confusion.

Together with managed services partner Astound Digital, Engine launched Eva in just 12 days. As they expanded the agent’s abilities, they noticed something surprising during testing. When too many similar topics existed — for instance, separate topics for “book a car,” “change a car,” and “update passengers" – Agentforce struggled to identify the right customer intent.

The fix was surprising yet effective. Instead of adding or changing Eva’s topics, Engine reduced them. They consolidated separate smaller topics into broader categories such as “car management,” and organized multiple related actions beneath each one. This approach gave Agentforce clearer choices, reduced response times, and made ongoing tuning easier for administrators.

Takeaway
More isn’t always better. Grouping related topics into broader categories can improve the speed and accuracy of agents, and make them easier to maintain long term.

See more tips from Engine:
Engine implementation story

Nexo made sure their data and knowledge were agent-ready.

Before the release of Agentforce, Nexo recognized where Salesforce (and technology more broadly) was headed and took early steps to clean up their data. As Nexo Salesforce Architect Kostadin Stoev said, “It’s really important for everyone to know that you won’t get good results unless you have clean data.”

But clean data was only part of the equation. Once Agentforce went live, Nexo discovered that the agent also needed clearer context to understand and respond accurately. It struggled to interpret help articles written for crypto-savvy users. This content made sense to customers and support agents, but not to a language model starting from scratch. To solve this, Nexo worked with their client care team to rewrite the articles with both human readers and the agent in mind, adding foundational crypto context to guide Agentforce’s behavior and improve its accuracy.

Takeaway
Clean data is essential, but not enough. Your content also needs to be written with humans and AI in mind so Agentforce has the context to understand and respond accurately.

See more tips from Nexo:
Nexo implementation story

Safari365 got hands-on and used rapid iteration.

Safari365 started with internal agents so they could monitor everything closely. It was an intentional, iterative process: They would test a conversation with Agentforce Testing Centre, spot an issue, then tweak the instructions or adjust the topics. Early on, for example, the agent began pulling internal notes like “Customer isn't ready to book” into messages meant for travellers. Because Safari365 built their internal agent with a human-in-the-loop, nothing went out, but it served as a strong reminder to pay close attention and ensure proper guardrails were in place.

Because Agentforce is configured in (and understands) natural language, Safari365 CEO Marcus Brain could make changes himself without waiting on developer time. In fact, Brain built two of their agents personally. Being able to build agents and refine them independently made Agentforce the fastest time-to-value of any Salesforce product they have deployed: just six weeks from signing to live.

To this day, Safari365 keeps a tight feedback loop. If someone catches a hallucination or issue, the team can jump in and fix it right away.

Takeaway
Safari365 attributes its success to the simplicity of the tools and a mindset of radical ownership. Brain can sit down and create 10 iterations of a conversation in the time it would've taken to schedule one dev meeting. That level of control keeps them close to both the customer experience and the risk.

See more tips from Safari365:
Safari365 interview

OpenTable built flexibility into their escalation logic

While building OpenTable's AI agents with Agentforce, RoseTree and OpenTable tackled one of the trickiest challenges in AI service design: knowing when to escalate a chat to a human. They created the deflection score, a real-time metric that tracks sentiment and intent throughout the conversation.

Every chat session starts with a baseline score. From there, the Atlas Reasoning Engine adjusts the score dynamically based on the diner's inputs. For example, asking for help carries a score of 5, and requesting a rep is a score of 10. Typing in all caps and extreme frustration take the score all the way up to 20. Agentforce uses this live score to determine whether to continue helping, create a case, or escalate to a human.

The best part is that the deflection score is a living metric. OpenTable's team can adjust escalation thresholds at any time. If staffing is tight, they can increase the threshold to reduce escalations, and during high-stress times like holidays, they can ease the threshold to offer more human support. A companion tenor score helps track how sentiment changes throughout the conversation, offering a full picture of what's working and where to improve.

Takeaway
Build flexibility into your escalation logic to match your staffing levels, customer sentiments, and seasonality. The bonus is that this will also help your AI agent improve with every chat.

See more tips from OpenTable:
OpenTable implementation story

Endress+Hauser trained their agent like a new hire.

Endress+Hauser treated Agentforce like a new teammate, not just a tool you could turn on and expect to work perfectly. From the beginning, they focussed on teaching the agent how to answer questions in the right way, what tone to use, and which parts of long help articles were most important. They gave real examples of customer questions so the agent could learn how to respond like a helpful team member. The team carefully checked the answers it gave, looking for anything that was confusing, too general, or didn't match what customers needed. If the agent gave a weak or wrong answer, the team fixed the instructions and tested it again.

They kept track of every change using a shared checklist, and nothing went live until it was fully reviewed. But during this training, the team also discovered something else: Many of the knowledge articles Agentforce used were outdated or too hard to understand. That made it harder for both people and the agent to find the right answers. So the team took time to clean up those articles, rewrite parts, and organise the information better. This restructuring of their existing content ensured Agentforce had clean, accurate information to draw from.

Takeaway
Just like any new hire, Agentforce improved with hands-on training, regular feedback, and better resources. The more it learnt, the more consistent it became at delivering clearer, more accurate answers with every iteration.

See more tips from Endress+Hauser:
Endress+Hauser customer story

reMarkable aligned early with their partners and executives.

reMarkable's deep partnership with Salesforce made it possible for them to launch Mark on their Experience Cloud site in just three weeks. Collaboration on everything from vision-setting to implementation and enthusiastic executive sponsorship helped the team meet their ambitious launch goal despite an intense workload and tight deadlines.

That early alignment paid off when the work got hard. It helped them overcome initial growing pains such as long hours, unexpected agent behaviour, and manual workarounds, and provided the necessary support to build a strong foundation for future growth.

“Having Salesforce Professional Services, who knew more than us, was great because then we could move faster," said reMarkable's System Manager Pernille Bucher-Johannessen. “Working with the people who are closest to the product was super valuable.”

Takeaway
Close collaboration with your implementation partner and strong executive support will speed up your launch and help you take your agents from good to great.

See more tips from reMarkable:
reMarkable implementation story

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